Road Safety Research Report No. 79
Central Scotomata and Driving
F. G. Rauscher, C. M. Chisholm, D. P. Crabb, J. L. Barbur and D. F. Edgar
Applied Vision Research Centre,
The Henry Wellcome Laboratories for Vision Sciences,
City University, London
G. T. Plant
Department of Neuro-Ophthalmology,
Moorfields Eye Hospital NHS Foundation Trust and Vision Research Group,
National Hospital for Neurology and Neurosurgery, Queen Square, London
M. James-Galton and A. Petzold
Vision Research Group,
National Hospital for Neurology and Neurosurgery, Queen Square, London
M. C. M. Dunne and L. N. Davies
Ophthalmic Research Group, Aston University, Birmingham
G. J. Underwood and N. R. Phelps
School of Psychology, University of Nottingham, Nottingham
A. C. Viswanathan
Glaucoma Research Unit, Moorfields Eye Hospital NHS Foundation Trust, London
December 2007
Department for Transport: London
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CONTENTS
ABBREVIATIONS
6
EXECUTIVE SUMMARY
7
1
INTRODUCTION
15
1.1
Background
15
1.2
Definition of the visual field
15
1.3
Definition of a scotoma
16
1.4
Prevalence of visual field defects
16
1.5
The impact of paracentral scotomata on driving
17
1.5.1
17
1.6
Medical conditions that may cause binocular central scotomata
19
1.6.1
Retinal conditions
19
1.6.2
Conditions affecting the optic nerve
21
1.6.3
Conditions affecting the chiasma
21
1.6.4
Conditions affecting the post-geniculate visual pathway
21
1.7
Licensing visual field requirements
22
1.8
The Esterman binocular visual field test
22
1.8.1
23
1.9
Stimulus array
The functionally-relevant visual field of a car driver
1.9.1
2
Simulated scotomata
Relationship between the functionally-relevant visual field
and the Esterman stimulus array
23
25
METHODS
26
2.1
Methodology
26
2.1.1
26
2.2
Literature reviews
Experimental studies
27
2.2.1
Sample
27
2.2.1.1 Patient group
27
2.2.1.2 Control group
28
3
Central Scotomata and Driving
2.2.2 Data collection
3
2.2.2.1 City University test battery
28
2.2.2.2 Comparison of the standard tests of vision with the
new tests developed for use at City University
34
2.2.2.3 Data analysis
35
RESULTS
37
3.1
Driving status of the patient group
38
3.1.1 Driving status according to Esterman pass/fail
38
3.1.2 Driving status according to IVF pass/fail
39
3.1.3 Esterman test taken as the ‘gold standard’ compared with
other tests
39
3.1.4 Agreement between the Esterman and the Integrated Visual Field
40
3.1.5 IVF compared with the Esterman test in glaucomatous and
non-glaucomatous patients
41
3.1.6 UFOV test taken as the ‘gold standard’ compared with
other tests
42
3.1.7 HPT test taken as the ‘gold standard’ compared with
other tests
44
3.1.8 UFOV test taken as the ‘gold standard’ compared with HPT
48
3.1.9 AVA tests
48
3.2
4
28
3.1.9.1 Contrast detection test
49
3.1.9.2 Contrast acuity
50
3.1.9.3 Motion discrimination
51
3.1.9.4 Colour vision
52
Data from sample patients
54
3.2.1 Patient 31
54
3.2.2 Patient 55
56
3.2.3 Patient 17
57
3.2.4 Patient 90
59
3.2.5 Patient 103
60
4
DISCUSSION
4.1
Design of studies to assess the effects of visual field defects on driving
safety
64
4.2
Design of the current study
64
4.3
Driving status questionnaire
64
4.4
Tests used
65
4.4.1
The Esterman Test
65
4.4.2
Integrated Visual Field test
65
4.4.2.1 Agreement between IVF and a binocular HFA test
67
4.4.3
The Useful Field of View test
67
4.4.4
The Hazard Perception Test
71
4.4.5
The AVA tests
72
4.5
5
6
64
Which test should be the gold standard?
73
4.5.1
Esterman as the gold standard
74
4.5.2
UFOV as the gold standard
74
4.5.3
HPT as the gold standard
75
4.6
Index of Good Vision
75
4.7
Compensatory head and eye movements
76
RECOMMENDATIONS
77
5.1
Current practice
77
5.2
Developments for the future
77
REFERENCES
79
5
ABBREVIATIONS
% missed
APP
AVA
CA
CAD
CT
EES
HFA
HPT
IOGV
IVF
MPT
POAG
RT
SITA
UFOV
VTA
6
Percentage of hazards missed
Advanced Perimetry Program
Advanced Vision Assessment
Contrast Acuity
Colour Assessment and Diagnosis Test
Contrast Threshold
Esterman Efficiency Score
Humphrey Field Analyser
Hazard Perception Test
Index of Good Vision
Integrated Visual Field
Motion Perception Test
Primary open angle glaucoma
(Mean hazard) response time
Swedish Interactive Threshold Algorithm
Useful Field of View
Visual Task Analysis
EXECUTIVE SUMMARY
Background
There is no question that, once binocular scotomata in certain locations within the
visual field reach a critical size, they must affect driving performance. The difficulty
is determining the level at which binocular visual field loss in the presence of good
visual acuity begins to impact on driving safety. The majority of publications in this
area have failed to find a strong correlation between the driver’s visual field and
driving safety. This is due, in part, to methodological problems, some of which are
inherent to research into driving safety, but is also due to the difficulty in assessing
driving performance in a group of individuals who are not legally able to drive.
Currently, Group 1 (ordinary cars) licensing decisions with respect to the visual field
are based on the outcome of the binocular Esterman test, normally carried out on the
Humphrey Field Analyser (HFA). The Esterman test presents a bright stimulus at
each of the 120 locations within the visual field, arranged in a pattern that was
originally designed to predict an individual’s mobility (walking), not their driving
performance. It is not surprising, therefore, that the number of locations tested
within the functionally-relevant area of a driver’s visual field is very limited, with
only 34 locations tested within the central 208 of the visual field, no locations
within the central 7.58, and a predominance of these central locations falling in the
lower half of the visual field, an area that generally overlays the dashboard display
when fixating on the road ahead. In addition, the use of a bright (10 dB) fixedintensity stimulus prevents the Esterman test from detecting all but the densest of
scotomata. An alternative approach to the Esterman test for the central visual field
could be the Integrated Visual Field (IVF; Crabb et al., 2004). The IVF approach
takes the data from each eye of the ‘gold standard’ full threshold, central visual field
tests carried out on the HFA and combines these to produce a prediction of the
central binocular visual field. This has proved to be a useful approach in patients
suffering from glaucoma. The IVF approach has the particular advantage over the
Esterman test of assessing more points within the functionally-relevant central 208
of the visual field (44), including (16) locations within the central 108 visual field,
which is an area largely untested on the Esterman test. Combining the threshold
values from each eye avoids binocular testing, which can be affected by fusion
problems in some patients. The use of the IVF approach has identified patients who
would have been classified as fit to drive by the Esterman criteria yet had significant
defects within the central 208.
Aims of the project
The project had four aims:
1. To study the implications for driving safety of paracentral scotomata.
The definitive study to determine the relationship between paracentral scotomata
7
Central Scotomata and Driving
and driving is not possible because licensing regulations in the United Kingdom
forbid those who are not legal to drive from participating. Even the use of a
simulator or on-road tests is questionable for those no longer legal to drive
because their driving skills may have atrophied. In addition, many hours of
driving under varied conditions are needed to cover a reasonable percentage of
the situations in which visual field loss might handicap driving performance.
Therefore, we had to use what some consider proxy measures of driving safety.
The only available candidates were the Useful Field of View (UFOV –
associated with crash risk) and Hazard Perception Tests (HPTs – related to
driving performance).
2. To examine the usefulness and limitations of currently available field tests
and the proxy measures of driving safety.
This involves comparison of the visual field outcomes (Esterman and IVF) with
other measures of visual performance and the development of standard normal
observer data for the proxy measures of driving safety. Individual patients can
then be considered in relation to these normal ranges.
3. To quantify the reduction in visual performance resulting from impairment
of other aspects of visual function within the central 208.
This involved the development of the Advanced Vision Assessment (AVA) tests
to assess contrast detection, contrast acuity, motion perception and colour
discrimination. They have in common the potential for being important visual
functions for driving and yet are not currently assessed.
4. To examine the relationship, if any, between measures of visual performance
and the proxy measures of driving safety.
This involves comparison of the UFOV and HPT outcomes with those from the
visual field tests and the AVA tests.
Methodology
The project is a large multi-centre study that completed literature reviews and
experimental studies in order to address the aims of the project.
Literature reviews
Four major literature reviews were undertaken during the course of this project:
1. The clinical spectrum of ophthalmological and neurological diseases related to
monocular, binocular and central visual field defects has been reviewed. Where
the data are available, reference is made to driving ability within each condition.
Particular emphasis is given to binocular paracentral scotomata with preserved
acuity. Such cases would not be disqualified from driving on the basis of
binocular visual acuity. The potential for progressive visual field loss needing
reassessment is also discussed.
8
2. The current techniques for assessing monocular and binocular visual fields are
outlined and critically reviewed with regard to drivers’ visual fields.
3. The current standards for visual field testing and licensing requirements of
driving authorities in Australia, Europe and the US have been summarised and
tabulated.
4. The use of artificial (simulated) scotomata to study the effects of binocular
visual field loss on driving performance has been critically reviewed. The main
advantage associated with the use of artificial scotomata is that it allows
functional visual performance to be assessed in a sufficiently large number of
participants with identical field defects, something that cannot realistically be
achieved by studying patient’s actual visual field defects. None of the current
studies on simulated field defects in the context of driving consider isolated
scotomata, concentrating instead on peripheral visual field constriction only. The
report concludes that studies of artificial scotomata cannot be confidently used to
inform the debate on central visual field requirements for driving.
Experimental studies
Sixty patient volunteers were involved in the study. They had a cross-section of
binocular visual field defects affecting the central visual field within 208 of
fixation and resulting from a wide range of ophthalmological and neurological
conditions. Seventy-two age-matched non-visually-impaired volunteers (controls)
were also recruited. They were evenly distributed across the age range of 20–85 and
generated the data used to determine the normal range of results for each test used
so that comparisons could be made.
All volunteers had their visual fields assessed using the HFA. The field tests
conducted on the HFA were the binocular Esterman test, a binocular full threshold
test, and the monocular full threshold plots which allowed the IVF to be generated.
A more detailed plot of the central 208 was carried out using the Advanced
Perimetry Program (APP), specially designed for this project. Advanced Vision
Assessment was undertaken to examine other aspects of visual performance at five
fixed locations within this central visual field.
Participants also completed a self-report driving questionnaire to ascertain their
current driving status and accident history. They also performed the UFOV and the
HPT tests used in this study as proxy measures of driving safety.
Results and discussion
None of the 60 patients reported accidents in the previous three years. A zero
accident rate is improbable in this sample, and may reflect the unreliability of
accident self-reporting, which is subject to various sources of error, such as recall
bias and socially-desirable responding.
9
Central Scotomata and Driving
The relationship between driving status and the outcome of the current Driver and
Vehicle Licensing Agency (DVLA) visual field criteria for driving was analysed for
both the Esterman plot and the equivalent IVF test. The analysis focused on the
performance of the Esterman passed and Esterman failed subgroups on other
tests, including the proxy measures of driving (UFOV and HPT). Of the 56 patients
who underwent Esterman testing, 33 passed and 23 failed the current DVLA visual
field criteria for driving. Seven of the 23 Esterman fails had a UK licence, and two
of these seven patients were still driving. Both these patients failed as a result of
having an inadequate peripheral visual field.
Agreement between the Esterman and the IVF outcomes was assessed with 2 3 2
frequency tables and kappa agreement (the agreement beyond what would be
expected by chance alone). In our patient group, the Esterman/IVF agreement is
very good (kappa ¼ 0.84). A similar level of agreement between these tests was
found for primary open angle glaucoma subjects (Crabb et al., 2004) and kappa ¼ 1
for the subgroup of 20 glaucoma patients in this study, supporting the suggestion
that the IVF test could perform a valuable screening role in the assessment of
glaucoma patients’ fitness to drive. Of particular interest are three patients (6%) who
passed the IVF but failed the Esterman test. All three had cortical lesions with visual
field loss that was peripheral but extended into the central 208. This suggests that the
IVF may misclassify patients with peripheral loss alone, such as those with certain
neurological anomalies. One patient passed Esterman but failed the IVF. The
inability of the Esterman test to detect the field defect probably resulted from the
inadequate number of locations tested within the central 208 of the visual field, and
from the absence of fixation monitoring on the Esterman. The IVF, with its superior
sampling density, revealed the patient to have a significant binocular defect in the
inferior visual field (see Section 3.2.1 patient 31). Therefore, the IVF needs to be
supplemented by an Esterman test in non-glaucomatous patients suspected of having
significant field defects that may affect the peripheral field. Employing different
assessment methods depending on the presenting pathology is not practical,
particularly given that dual pathology is not uncommon among patients.
In a separate study involving 40 of our patient group, we investigated the agreement
between the IVF and binocular visual fields assessed using the HFA. Concordance
between the binocular test and the IVF in the location and general shape of
binocular visual field defects was good, and this suggests that the IVF is a good
predictor of significant defects in the central binocular fields. However, when
individual locations in the field were analysed, the binocular testing tended to
overestimate the measured sensitivity values compared with the IVF, leading to an
underestimation of the severity of the field defect.
Control group data on each of the UFOV, HPT and AVA tests resulted in the
production of ranges for a ‘control observer’ in each age group for that test. This
allowed us to generate a pass/fail outcome for each test and to grade each patient
10
accordingly. The currently accepted pass/fail criterion for the UFOV (40% loss) was
also used to grade each patient.
Based on the standard UFOV pass/fail criterion of 40%, there was limited agreement
between the UFOV and Esterman tests (65%, kappa ¼ 0.22) and the UFOV and IVF
tests (69%, kappa ¼ 0.23), with the UFOV only identifying 33% of patients who
would be considered unfit to drive based on the current UK visual field
requirements. These findings should not be too surprising since the UFOV test was
designed to reveal loss of divided and selective attention and not loss of visual field.
Taking the total number of UFOV failures in the patient group into consideration,
there was a similar proportion of patients who failed the UFOV whose condition was
neurological in origin (5/20) rather than retinal/optic nerve in origin (7/21),
suggesting that their UFOV failure was caused by visual deficits associated with the
visual field defect rather than attention problems associated with a more global
neurological deficit. The main predicting factor for UFOV failure appears to be age,
with the youngest UFOV failure among the patient group being 57 years of age, the
next 60 years of age, with the remainder being over 70. All three normal participants
who failed the UFOV were over 70 years of age.
As part of this study we have calculated age-matched limits for 100 normal
observers on the UFOV test and established the normal range of UFOV scores for
each decade of life. This allowed the recalculation of the agreement between UFOV
and the Esterman and IVF tests. Agreement remains poor. Considering those
patients who passed the Esterman test, 12% who passed on the standard 40% UFOV
criteria lay outside the age-matched limits for controls, while three of the four
patients who failed by the standard UFOV criteria lay within the age-matched limits
for controls. A similar disparity was noted for patients who failed the Esterman test.
All this raises the question of the validity of the widely used current cut-off criterion
on the UFOV test, which is set at a standard level independent of the subject’s age,
for this group of patients. If the UFOV test were ever to be adopted as the definitive
‘vision’ test for determining fitness to drive, a significant proportion of older drivers
exhibiting visual function within the age-matched normal range would lose their
licence.
The UFOV study (based on the analysis of results from the 100 controls and 54
patients) reveals very poor correlation between visual field sensitivity loss and
UFOV pass/fail rate. The results show that 85% of patients with paracentral
scotomata had UFOV scores that fell within the age-based normal limits. This is not
surprising as only relatively dense and extensive paracentral visual field loss would
be expected to influence the UFOV score because of its employment of large highcontrast targets. However, the mean total UFOV score was significantly higher for
the patient group than the normal group, although the difference (6.6%) was only
just larger than the variability of the UFOV test (5.5%).
11
Central Scotomata and Driving
HPT performance was judged in terms of the percentage of hazards missed (%
missed) and the mean hazard response time (RT). Eye movement parameters, such
as fixation duration, saccade length and horizontal variance of fixation, were
investigated. In our study, agreement between the Esterman test and the HPT for %
missed was only 61% with a very poor kappa value (0.09). This lack of agreement
was most clearly revealed by the 37% of patients (n ¼ 14) who failed the Esterman
test yet passed the HPT. A similar level of agreement exists for the IVF (64%, kappa
¼ 0.11), with 31% (n ¼ 11) of patients failing the IVF test but passing the HPT.
Agreement between the Esterman test and RT (HPT) was fair (65%, kappa ¼ 0.22),
highlighted by the 32% of patients (n ¼ 11) who failed the Esterman test but passed
the HPT for this measure of performance. Agreement was slightly better between
the IVF and RT (71%, kappa ¼ 0.32), with 24% (n ¼ 8) of patients failing the IVF
but passing the HPT. The poor agreement between the HPT and visual field tests is
likely to relate to the unchallenging nature of the HPT test in its current form.
Neither mean log10 percentage of hazards missed nor mean fixation duration
differed significantly between the patient and normal groups. Whether or not an
individual responded to a hazard was found to be affected by the participants’
personality make-up, with the average control subject failing to detect/recognise
16% of hazards. Mean log10 hazard response time, mean saccadic amplitude (in
degrees) and mean horizontal variance of fixation were significantly higher for the
patient group compared with the normal group. This analysis of eye movements
suggests that some patients compensate for their paracentral visual field loss by
increasing their scanning of the visual scene. This may improve an individual’s
chance of detecting a hazard but is also likely to lead to an increase in mean time to
detection. Whether such scanning strategies improve or degrade driving safety
depends very much on the characteristics of the hazard and the particular visual
context. Given the relatively small difference between the patient and normal groups
for hazard response time and eye movements, it is unlikely that many of the patients
in this study have adopted these strategies, particularly since so many showed
complex central field loss that would be difficult to overcome by modifying eye
movements.
When the Esterman test is taken as the gold standard, both the UFOV and HPT show
low sensitivity and high specificity consistent with the conclusion that the proxy
measures pass too many patients who should not be driving. However, it is also
consistent with the conclusion that the Esterman test is an inadequate gold standard
which fails too many patients who are fit to drive. Analysis of the detailed results of
these participants does not support this conclusion, with most of these participants
having Esterman and other visual field test results which should preclude driving.
There is little evidence from our study to support the view that either the UFOV or
the HPT tests should replace the Esterman test as the gold standard for pass/fail
decisions on visual fields required for driving safety. When compared with the
Esterman test, our results demonstrate that both the UFOV and the HPT tests are
12
unreliable indicators of visual field outcome. When added to the other disadvantages
of the two proxy methods, discussed later in this report, we conclude that neither
existing tests of divided and selective attention, such as the UFOV, nor the HPT
(which does have the advantage of being a test that participants can easily relate to
the driving task) can be used in isolation as good indicators of driving performance.
However, both the UFOV and HPT hazard response time were able to identify
differences between the patient and normal groups, suggesting that some features of
each test may be useful in a future test.
Simple measures of perimetric sensitivity on the Esterman or the HFA can only
provide a limited measure of vision loss. The majority of patients demonstrated
considerable damage to visual function within the paracentral visual field, as
identified by the contrast acuity, motion and colour sensitivity tests, in regions
classed as being normal by the perimetric tests. Assuming that a key function of this
paracentral region of the visual field is to detect novel events that can be used to
trigger eye/head movements, these losses in visual performance leave a level of
residual vision that could have a significant impact on driving safety.
Recommendations
Our results indicate that interpretation of visual field plots alone is an inadequate
method of assessing drivers’ vision. However, in the short-term, visual fields are
likely to remain the arbiter for screening purposes until an acceptable alternative
becomes available. Therefore we recommend that, in future, a more complete visual
assessment should be employed for borderline cases.
Although it is desirable that the perimetric test used for licensing requirements
should be carried out binocularly, there is a major problem for many patients
regarding binocular fusion of the fields of the right and left eyes at the usual testing
distances of around 33 cm. This tends to lead to the underestimation of visual field
loss by the binocular Esterman test. Despite this, for the standard screening of
drivers we recommend that a modified Esterman test is developed with many more
central locations tested, but bearing in mind the remaining limitations of this test,
including the fusion difficulties and the inability to monitor fixation. For patients
with known visual field defects, the IVF (based on monocular data) could be used if
supported by the Esterman performance for the peripheral field.
A new composite test that incorporates suitable material to indicate the levels of
visual performance, distributed attention and motor responses within an interactive
driving environment could be developed. Although the majority of patients passed
both proxy measures of driving performance, the fact that the patient and normal
groups differed in terms of UFOV score, and mean hazard response time and certain
eye movement parameters (HPT), suggests that certain features of these tests, such
as paracentral crowding (UFOV) and free eye movements (HPT), could be usefully
incorporated into such a new test which is likely to produce scores that correlate
13
Central Scotomata and Driving
more closely with driving performance. It is important that any new test is seen by
patients as clearly related to the driving task.
Fundamental to the development of any new tests is a wide-ranging Visual Task
Analysis (VTA), mapping the visual challenges faced by the normal driver, such as
has been previously undertaken for commercial aviation. This analysis would
consider a wide range of driving conditions and would allow the identification of
difficult visual environments, driving conditions and hazards that would be
incorporated into any subsequent test. Crucial to this VTA would be the input from
particular groups of drivers, for instance police drivers and driving instructors.
An important group of patients to study are those who already have longstanding
defects, including congenital defects. Information would be obtained on the degree
to which different patients develop strategies to cope with their visual field defect.
To inform this investigation it would also be useful to monitor patients soon after
they acquire a visual field defect and then at intervals subsequently to identify the
strategies employed to compensate for their defects, to assess the time course for
learning to compensate, and to chart the range of improvement in performance
across the patient group.
14
1
INTRODUCTION
1.1
Background
There is little doubt that the safe manoeuvring of a motor vehicle relies heavily on
the driver receiving visual input of sufficient quality and, therefore, any significant
reduction in visual performance is expected to adversely influence driving safety.
Although it is not difficult to identify the aspects of vision that are likely to play an
important role in driving, the majority of published studies have failed to show a
significant correlation between conventional measures of visual performance and
driving safety (North, 1985). The complexities of the driving task, the influence of
numerous external factors (e.g. driving conditions, driver fatigue, etc.), the influence
of compensation strategies, the method of measuring specific visual functions and
methodological inadequacies have all undoubtedly been factors contributing to the
failure to find significant correlates between individual visual functions and safe
driving.
1.2
Definition of the visual field
One of the aspects of vision thought to be important for driving is the extent of
vision, referred to as the visual field. The visual field is defined as ‘all the space that
one eye can see at any given instant’ (Tate and Lynn, 1977). On average, the normal
monocular visual field extends 608 up, 758 down, 1008 temporal and 608 nasal from
fixation, although this depends on the facial features of the individual. With both
eyes open, the visual field has a horizontal dimension in the region of 2008,
composed of approximately 608 of binocular overlap with a monocular temporal
crescent on each side (Figure 1.1).
Figure 1.1: The normal binocular visual field, approximately 1208 in horizontal
extent. Each monocular visual field contains a natural scotoma,
referred to as the blind spot
L
R
Left eye
Right eye
L
R
Binocular visual field
Central ⫾20°
15
Central Scotomata and Driving
1.3
Definition of a scotoma
The dictionary definition of a scotoma is an isolated area of depressed or absent
sensitivity. This loss can be either complete/absolute (i.e. no awareness of any
stimulus attribute in the corresponding region of the visual field) or it can represent
selective reduction of sensitivity to light flux increments, colour, contrast and/or
motion perception (a relative scotoma). All such losses will cause degradation of
vision that is very likely to affect driving performance, yet may spare central acuity
so that an individual can still pass the number plate test. A pathological scotoma
may involve any part of the visual field and may be of any shape, size or density. A
scotoma may include and enlarge the normal blind spot. A small scotoma, if it
happens to affect foveal vision, will produce a severe visual handicap, whereas a
large scotoma in the more peripheral part of a visual field may go unnoticed by the
bearer.
Every normal mammalian eye has a scotoma in each monocular field of vision,
usually termed the blind spot. This oval-shaped scotoma which typically subtends
5o horizontally by 8o vertically, is centred some 14 degrees from fixation in the
temporal field of each eye, (Figure 1.1). The presence of this normal scotoma does
not intrude into consciousness, even under monocular viewing, partly because of its
small size. However, its presence can be demonstrated by the simplest of clinical
methods.
Monocular individuals, who are allowed to hold a Group 1 (ordinary cars) driving
licence in the United Kingdom provided they meet the visual standards, effectively
have a defective visual field at all times (Petzold and Plant, 2005). This consists of
an absolute scotoma corresponding to the blind spot in the remaining eye and the
loss of one monocular crescent of the binocular visual field.
1.4
Prevalence of visual field defects
The prevalence of visual field defects specifically involving the central 208 of the
visual field is unknown. The most comprehensive study considering visual field loss
in general was undertaken by Johnson and Keltner (1983), who examined 10,000
drivers between the ages of 16 and 65 years. The authors detected monocular visual
field loss in 3–5% of subjects, 57.6% of whom were unaware of their defect. Visual
field loss in both eyes (not necessarily overlapping) was found in 1.1% of subjects.
This figure for monocular field loss is consistent with the frequency reported
elsewhere (Bentsson and Krakau 1979; Keeney 1974). Van Newkirk and colleagues
(2001) reported mild visual impairment due to field defects in 5% of patients with a
history of cerebrovascular accident (Van Newkirk et al. 2001).
16
1.5
The impact of paracentral scotomata on driving
A driver with normal or near-normal visual fields would be expected to detect and
identify peripheral and paracentral hazards more quickly than someone with
impaired fields. An association between visual field defects and increased risk of
motor vehicle accidents undoubtedly exists but the relationship between the two is
not clear cut. North (1985) reviewed the literature on this subject and reported no
significant relationship between visual field loss and driving safety. She attributed
this finding in part to the numerous methodological limitations of published papers,
which almost exclusively considered only the horizontal extent of the peripheral
binocular visual field and therefore have no direct relevance to this study.
The effect of real scotomata on driving is very difficult to study because it is
infeasible to control the visual field loss. Scotomata vary in terms of size and
location, as well as depth and aetiology. Therefore, there are very few studies that
have considered the implications of pathological paracentral visual field loss for
driving safety. Owsley et al. (1998a) did identify a link between reduced mean
visual field sensitivity within the central 308 and crashes resulting in injury, but this
finding was not replicated by a prospective study on the same group of drivers
(Owsley et al., 1998b). The crude method used to estimate the sensitivity of the
binocular visual field may have played a part in this discrepancy.
One option is to look at monocular drivers who all show an identical ‘binocular’
visual field defect resulting from the physiological blind spot. In monocular
individuals, the blind spot results in a scotoma of approximately 2 m in diameter at a
viewing distance of 20 m. Refixation during driving occurs in an area smaller than
the blind spot (Mourant and Rockwell, 1970). Theoretically this could affect the
perception of, for example, a hand signal from another driver within the monocular
driver’s blind spot (Mourant and Rockwell, 1970; Westlake, 2001). However, no
increase in accident rate has been found for monocular drivers (Johnson and Keltner,
1983; Kite and King, 1961; Leismaa, 1973).
1.5.1 Simulated scotomata
Since real scotomas are so difficult to study, the possibility of simulating scotomata
in normal subjects has been proposed. Such studies allow for a controlled
experiment and functional performance can be assessed in a sufficiently large
number of subjects with identical field defects. In addition, the influence of
particular variables, such as scotoma size or location, could, in theory, be examined.
Only a small number of studies have examined driving performance in the presence
of simulated scotomata. The series of studies undertaken by Wood and colleagues
used a crude obstruction technique to create constriction of the visual field (Wood et
al., 1993; Wood and Troutbeck, 1992; Wood and Troutbeck, 1994; Wood and
Troutbeck, 1995). They employed modified swimming goggles fitted with artificial
17
Central Scotomata and Driving
pupils, roughly adjusting the separation of the cups to prevent diplopia. This resulted
in some variation in the size of the binocular visual field between participants.
Another group used a cone of opaque paper mounted on an eye patch to simulate
constriction of the visual field in controls, before assessing their driving
performance using a simulator (Brooks et al., 2005).
A literature search failed to reveal any publications that have attempted to simulate
paracentral visual field loss and examine its effect on driving performance. It would
not be possible to mimic isolated scotomata using an obstruction technique due to
the shift in scotoma location with respect to fixation with eye movements. Isolated
scotomata can be created artificially, either by projecting a mask on to the retina
using a scanning laser ophthalmoscope or by modifying the stimulus to incorporate
a patch deprived of stimulation (Deweerd et al., 1995). Both techniques require
sophisticated equipment to allow the scotoma to maintain a constant relationship
with respect to fixation. Attempting to use such techniques in a driving simulator or
in an on-road test would create additional practical challenges.
Studies of the blind spot, a natural, monocular scotoma exhibited by all individuals,
have limited use in predicting the behaviour of pathological scotomata, since the
blind spot is, by definition, an absolute scotoma due to the absence of
photoreceptors.
Had work been undertaken to examine the effect of simulated paracentral scotomata
on driving safety, the findings could not be assumed to apply to individuals with real
scotomata for two reasons:
1. Real visual field loss cannot be precisely described, making it difficult to
simulate an equivalent scotoma:
• conventional perimetry can localise most scotomata but the information
provided about the full extent of a scotoma and the slope of its
margins is limited (Budenz et al., 2002);
• threshold measurements are greatly influenced by learning effects
(Wood et al., 1987) and fatigue, particularly for glaucoma patients
(Hudson et al., 1994; Wild et al. 1991);
• poor sampling density means that a relatively large scotoma may be
represented by only one or two missed points on the visual field test;
• suprathreshold screening tests, such as the Esterman test, do not
identify relative scotomata apart from those that are close to absolute;
• it is not possible for a simulated scotoma to replicate the more
complex visual loss associated with pathological scotomata. The true
extent of visual loss is frequently misrepresented because conventional
field tests only consider the ability of the visual system to detect the
presence of a stimulus. The discrimination of low contrast detail,
motion and colour can be selectively damaged by a range of conditions
(Hawkins et al. 2003; Westcott et al., 1998). Detection thresholds are
18
•
often the last component of visual function to be affected; and
simulated visual field loss cannot replicate the effects of blindsight,
thought to be present in some patients suffering from damage to the
striate cortex of the brain (Trevethan and Sahraie, 2005). Blindsight is
the ability to discriminate certain stimuli positioned in clinically blind
areas of their visual field (Sahraie et al., 1998; Weiskrantz, 1987;
Weiskrantz, 1996; Weiskrantz et al., 1999). This residual vision is
taken to reflect the properties of known subcortical and extrastriate
visual pathways, particularly the relatively good sensitivity for the
detection of abrupt, transient stimuli or fast-moving targets, which
could be particularly relevant to driving.
2. Paracentral visual field loss varies considerably between individuals:
• scotomata vary in size, depth and location. A scotoma of a particular
size at one location would not have the same impact as an identical
scotoma located further way from fixation;
• there is evidence to suggest that some individuals are able to adapt to
their visual field loss by making compensatory eye movements
(Lovsund et al., 1991). This has been shown to lead to safe driving
behaviour in certain individuals (Schulte et al., 1999). In studies that
simulate visual field loss in normal participants, adaptation cannot be
examined. The varied ability of patients to adapt to their visual field
loss makes it impossible to make assumptions about driving behaviour
from studies of artificial scotomata in normal subjects.
1.6
Medical conditions that may cause binocular central
scotomata
A wide range of ophthalmological and neurological conditions can give rise to
pathological scotomata (relative and/or absolute) within the central 208 that in some
cases are apparent under binocular viewing conditions. These conditions can be
categorised by aetiology but an alternative is to group them on the basis of the
location of the lesion, since the likelihood of the visual field loss being binocular is
strongly dependent on this factor.
1.6.1 Retinal conditions
When vision is damaged by retinal pathology, the area and type of visual deficit can
be different between the two eyes and it is the region of overlap of visual loss that
results in a binocular scotoma or scotomata.
Conditions involving the retina can be divided into three groups:
1. Conditions that will probably only ever affect one eye, such as a retinal
detachment resulting from unilateral trauma, or occlusion of a retinal blood
19
Central Scotomata and Driving
Figure 1.2: Monocular blindness (from any cause), in this case in the left eye,
results in a small scotoma (blind spot) in the paracentral ‘binocular’
visual field
L
Left eye
R
L
Right eye
R
Binocular visual field
Central ⫾20°
vessel (Bek 1991). Monocular field loss is the most likely outcome but if the
location of the defect coincides with the blind spot in the unaffected eye, a small
‘binocular’ scotoma results. In addition, the monocular visual field defect can
become relevant to driving if vision in the other eye is lost (Figure 1.2), either
completely independently of the vision loss in the first eye or indirectly linked
through underlying systemic disease. The occlusion of one eye to relieve double
vision has a similar effect.
2. Conditions that tend to progress to involve both eyes, with one of the most
common examples being primary open angle glaucoma (POAG). Elevated
intraocular pressure causes damage to the optic nerve head resulting in visual
field loss. Approximately 2–4% of the population over 40 years of age suffer
from POAG (Tielsch et al., 1990) and many are unaware of their condition.
Binocular visual field loss occurs when the scotomata from each monocular
visual field overlap (Figure 1.3).
Figure 1.3: A patient with a progressive binocular disorder, for example glaucoma
resulting in an accumulation of paracentral scotomata under binocular
viewing conditions
L
R
Left eye
Right eye
L
R
Binocular visual field
Central ⫾20°
20
3. Conditions that always affect both eyes, such as retinal dystrophies (cone
dystrophy, retinitis pigmentosa, etc.). A degree of asymmetry in terms of vision
loss is common as the condition progresses.
Certain retinal conditions tend to involve the macular region, resulting in a
reduction in visual acuity (e.g. age-related macular degeneration, diabetic
maculopathy). In such cases, if both foveas are involved, a driving licence is likely
to be revoked because of the failure to read the number plate rather than visual field
loss.
1.6.2 Conditions affecting the optic nerve
Conditions affecting the optic nerve can be divided into two groups:
1. Conditions affecting the anterior portion of the optic nerve of just one eye, such
as a localised tumour or infarct, will result in monocular field loss.
2. Conditions that may go on to affect the optic nerve of both eyes, caused by
underlying systemic disease, for example optic neuritis associated with multiple
sclerosis.
1.6.3 Conditions affecting the chiasma
1. A lesion of one optic nerve occurring close to the chiasma can involve crossing
fibres from the contralateral optic nerve, resulting in asymmetric visual field loss
that may overlap to give binocular field loss.
2. Lesions affecting the chiasma can result in heteronymous hemianopia. An
example would be a centrally-located pituitary adenoma that causes bitemporal
field loss but no binocular central field loss (Petzold and Plant, 2001). A binasal
defect has been known to result from an aneurysm of the internal carotid artery.
3. The optic tracts carry fibres from both eyes and therefore a lesion to one tract
will result in monocular field loss in both eyes and a corresponding binocular
field defect.
1.6.4 Conditions affecting the post-geniculate visual pathway
The conditions in question include central lesions (mainly of the primary visual area
of the cortex) when the localised visual impairment involves the visual field of both
eyes, often with a degree of congruence. Examples are space occupying lesions
(Horton and Hoyt, 1991) and cerebrovascular accidents.
A comprehensive review of all conditions that can lead to paracentral scotomata
together with the likelihood of progression is available on request from the authors
or from the Department for Transport.
21
Central Scotomata and Driving
1.7
Licensing visual field requirements
The functional scoring system developed by Esterman (Esterman, 1982) is the
current gold standard for testing binocular visual fields and is used by many national
driving authorities. National visual field requirements for fitness to drive differ
significantly between countries (Charman, 1997). Other than Germany, few
countries have any requirement relating to the central visual field. The German
Ophthalmological Society recommends that more than 25 points should be
recognised within the central 258. A report detailing the visual field requirements in
a number of other countries is available on request from the authors or from the
Department for Transport.
At the time of writing this report the visual field requirements in the United
Kingdom were as follows:
‘A minimum horizontal field of vision of 1208 and no significant defect
within 208 of fixation.’ (http://www.dvla.gov.uk/medical/ataglance.aspx)
In the UK for Group 1 (ordinary cars) licensing, the DVLA accepts the following
central loss (referring to the Esterman protocol):
•
•
scattered single missed points; and
a single cluster of up to three contiguous points.
A significant central loss is defined as:
1.8
•
a cluster of four or more contiguous points that is either wholly or partly within
the central 208 area;
•
loss consisting of both a single cluster of three contiguous missed points up to
and including 208 from fixation and any additional separate missed point(s)
within the central 208 area; and
•
central loss of any size that is an extension of a hemianopia or quadrantanopia.
The Esterman binocular visual field test
The Esterman binocular visual field test is most commonly run on the HFA. It is a
suprathreshold test that presents a single, very bright stimulus (10 dB) at each of
120 locations within the visual field. The subject is required to fixate centrally and
press a button when a stimulus is detected. By testing each point at a single, very
extreme suprathreshold level, only the deepest scotomas are revealed.
The Esterman test has the advantage of being relatively quick compared with other
‘full field’ tests (four to five minutes for a normal subject), and is by far the most
frequently available binocular field test in ophthalmology and optometry clinics.
22
1.8.1 Stimulus array
The 120 points in the stimulus array are spread over a large area extending
approximately 758 horizontally, 358 superiorly and 558 inferiorly (Figure 1.4(a)).
The sampling density is particularly sparse within the central 208, with 12
locations examined above the midline and 22 below, and no stimuli within 7.58 of
fixation (Figure 1.4(b)). The sensitivity to detect paracentral scotomata is lowest in
the upper visual field and close to fixation. A single cluster of three contiguous
points in the upper visual field would not prevent an individual from holding a
licence, despite the fact that such a pattern of missed points would probably
represent a substantial paracentral visual field loss due to the scarcity of points
tested in this area.
The stimulus array was designed to relate to personal mobility, with more locations
tested in areas judged to be of importance for negotiating obstacles when walking.
The Esterman Efficiency Score (EES) is simply based on the percentage of stimuli
seen, with the importance of the inferior visual field, for example, represented in the
EES by the greater density of stimuli within this area.
Figure 1.4: (a) The Esterman binocular visual field; and (b) each black dot
represents a tested location – the density of the tested locations is
higher within the central 208 and in the lower hemifield, therefore the
sensitivity to detect paracentral scotomata is lowest in the upper visual
field. Unfortunately, this area is of particular relevance to driving
1.9
The functionally-relevant visual field of a car driver
The functionally-relevant visual field is illustrated in Figure 1.5, showing the
importance of the central 208 field and the region along the horizontal meridian.
The lower visual field, beyond about 10–158, is not particularly relevant to driving
as it overlays the dashboard. The driver will be aware of the presence of the
dashboard display, but will only be able to resolve detail when fixation has
momentarily been transferred to the display area itself.
23
Central Scotomata and Driving
Figure 1.5: The functionally-relevant visual field of a driver, digitally corrected for
the effect of decreasing resolution towards the periphery
The image is Figure 1a (digital montage of traffic scene and vehicle cockpit without
superimposed unsharp mask), adapted from Schiefer, U. et al. (2000) ‘‘Perimetric
findings and driving performance. How much visual field does a motorist require?’’,
Ophthalmologe, 97, page 492
Zahl 1a (Digitale Bildmontage von Verkehrsszenario und Autocockpit ohne
uberlagerter Unscharfemaske), von Schiefer, U. zu verwenden u. a. (2000)
,,Perimetriebefund und Fahrtauglichkeit. Wieviel Gesichtsfeld braucht ein
Autofahrer?’’ Ophthalmologe, 97, Seite 492
For copyright reasons, the image cannot be reproduced in the web version of this
report, but can be viewed in the printed version
The visual field to the left is partially obscured between eccentricities of
approximately 20–358 by the window A-pillar. The upper visual field is obscured
within 30–458 by the rear-view mirror (Schiefer et al., 2000), although the exact
location of these obstructions varies between cars and with the position of the driver
(Vargas-Martin and Garcia-Perez, 2005).
An object such as a cyclist or pedestrian moving from the side into the driver’s path
is in danger of collision. Early recognition of such moving objects is important. This
requires a good visual field but recognition of objects within the field is also
influenced by speed smear (the linear reduction in useful visual field with driving
speed; Danielson, 1957). This effect is best illustrated by comparing the picture of
the artificial visual field of a driver who faces a pedestrian crossing the road (Figure
1.6(a)) with the ‘real-life’ visual field simulation incorporating both speed smear
and cortical magnification (Figure 1.6(b)). Recognition of the pedestrian is reduced
by the fact that the driver must concentrate on the other vehicles in his path. In this
particular scenario, one would predict that a binocular scotoma approximately 208 to
the left of fixation would considerably diminish the chances that the driver would
detect the pedestrian in time.
24
Figure 1.6: The effect of speed smear for the recognition of a pedestrian crossing
the road – (a) demonstrates the artificial visual field as assessed by
standard static perimetry and (b) the ‘real-life’ visual field. We should
point out that the car itself (i.e. window pillar) would not appear blurred
in real life. (Adapted from a picture created by Xavier Zanglonghi
(Laboratoire d’Exploration Fonctionelle de la Vision, 44000 Nantes,
France))
(a)
(b)
1.9.1 Relationship between the functionally-relevant visual field and the
Esterman stimulus array
In Figure 1.7 the Esterman stimulus array has been superimposed over the driver’s
visual field. Only 25% of the measured points fall within the eloquent area because
the Esterman overrates the lower field. However, in a driver’s setting, most of these
points fall outside the functionally-relevant area. Considering the scenario illustrated
in Figure 1.6, the Esterman visual field test only examines five points in the area
corresponding to the pedestrian, and, at the time of writing this report, the DVLA
defines a cluster of four or more missing points as significant, thus three missing
points in this area would still be compatible with driving.
Figure 1.7: The Esterman stimulus array overlaid on the driver’s visual field. Note
that most test points fall within the lower visual field, an area almost
completely overlaying the dashboard
25
2
METHODS
The project is a large multi-centre study that completed literature reviews and
experimental studies in order to address the four aims of the project:
1. To study the implications for driving safety of paracentral scotomata.
The definitive study to determine the relationship between paracentral scotomata
and driving is not possible because licensing regulations in the United Kingdom
forbid those who are not legal to drive from participating. Even the use of a
simulator is questionable for those no longer legal to drive because their driving
skills may have atrophied. In addition, many hours of driving under varied
conditions are needed to cover a reasonable percentage of the situations in which
visual field loss might handicap driving performance. Therefore, we had to use
proxy measures of driving safety. The only available candidates were the UFOV
test and the HPTs.
2. To examine the usefulness and limitations of currently available field tests
and the proxy measures of driving safety.
This involves comparison of the visual field outcomes (Esterman and IVF) with
other measures of visual performance and the development of standard normal
observer data for the proxy measures of driving safety. Individual patients can
then be considered in relation to these normal ranges.
3. To quantify the reduction in visual performance resulting from impairment
of other aspects of visual function within the central 208.
This involved the development of the AVA tests to assess contrast detection,
contrast acuity, motion perception and colour discrimination. They have in
common the potential for being important visual functions for driving and yet
are not currently assessed.
4. To examine the relationship, if any, between measures of visual performance
and the proxy measures of driving safety.
This involves comparison of the UFOV and HPT outcomes with those from the
visual field tests and the AVA tests.
2.1
Methodology
2.1.1 Literature reviews
Four major literature reviews were undertaken during the course of this project. The
key findings of each are noted in the introduction to this report but further
information is available from the authors on request. The reviews covered the
following topics:
•
26
the clinical spectrum of ophthalmological and neurological diseases related to
monocular, binocular and central visual field defects with data on driving ability
within each condition where available;
2.2
•
the current techniques for assessing monocular and binocular visual fields and
their relevance to drivers’ visual fields;
•
the current standards for visual field testing and licensing requirements of
driving authorities in Australia, Europe and the US; and
•
the use of artificial (simulated) scotomata to study the effects of binocular visual
field loss on driving performance.
Experimental studies
2.2.1 Sample
Two groups of volunteers were recruited to the study. First, we recruited patients
with normal visual acuity but binocular visual field loss within the central 208 of
their field (paracentral). Second, we recruited a group of age-matched visuallynormal participants.
2.2.1.1 Patient group
Volunteers (n ¼ 60) were recruited from several London hospitals:
•
•
•
•
the National Hospital for Neurology and Neurosurgery at Queen Square;
Central Middlesex Hospital (North West London Hospitals NHS Trust, NWLH);
Moorfields Eye Hospital Trust; and
the Fight for Sight Optometry Clinic at City University.
This allowed access to a wide range of ophthalmological and neurological
conditions that can cause discrete loss of vision within 20 degrees of fixation
under binocular viewing conditions.
Patient selection was regarded as crucial to the success of the study, and the team
aimed to achieve a representative cross-section of typical central visual field loss
attributable to pre-geniculate conditions (retinal and optic nerve diseases such as
glaucoma, optic neuritis and optic atrophy), optic radiation lesions and cortical
lesions (caused by conditions such as infarct and tumour). Only patients with a
consistent single diagnosis for the field loss in each eye were recruited.
The patient group ranged from 23 to 86 years of age, with the distribution skewed
toward the older age groups, reflecting the increased prevalence of central visual
field loss in the older population.
Prior to inclusion in the study, all patients had a full optometric eye examination
including visual fields. Patients were excluded if they produced unreliable fields at
27
Central Scotomata and Driving
this first visit.1 Visual acuity of at least 6/9 in at least one eye was required,2 with no
other significant disease reported other than the chief condition affecting the patient.
Unreported significant disease was ruled out by the standard optometric and neuroophthalmological examination.
2.2.1.2 Control group
A group (n ¼ 72) of non-visually impaired people, matched for age to the patient
group, was recruited via contacts and advertisements centred on City University
facilities (centres for the elderly, clubs, a university website advertisement, and the
Fight for Sight Optometry Clinic at City University).
A full eye examination, including visual fields, was carried out to rule out any
abnormality before a volunteer was accepted into the study. To be included in the
study, distance visual acuity of at least 6/9 was required for each eye. Volunteers
with ocular pathology were excluded.
2.2.2 Data collection
Data collection took place at several sites: City University, Nottingham University
and Aston University. At each site, the purpose and aims of our study were
explained and written informed consent was obtained from each volunteer after
reading the information sheet. Data collection at all sites involved clinical, neuroophthalmological or non-invasive psychophysical tests, the use of which was
approved by the appropriate ethical committees at City University, Aston University,
Nottingham University and the participating hospitals. Various tests were carried out
at the different sites.
At the City University site, where the majority of data were collected, each
volunteer’s refraction was assessed over a range of testing distances in order to
determine the appropriate correction that should be worn for each individual test.
The data were collected over the course of a year. Each subject normally attended on
two occasions separated by less than two weeks in order to complete all testing and
to minimise fatigue.
2.2.2.1 City University test battery
Standard visual field tests
The tests run on the Humphrey Visual Field Analyzer Model II (Humphrey
Instruments, Dublin, CA, USA) are:
28
1
Unsatisfactory False Negative, False Positive or Fixation Losses, as assessed by the
standard HFA criteria: >20% is considered unreliable.
2
All volunteers had acuity of 6/6- or better.
•
the Binocular Esterman test;
• a fixed intensity, suprathreshold test to screen the binocular visual field
for significant defects (threshold of less than 10 dB);
•
a monocular full threshold central field assessment (24-2 SITA (Swedish
Interactive Threshold Algorithm) Standard):
• this is the visual field test most commonly used by the hospital eye
service to monitor progression of any central visual field defect. The
detection threshold is determined at 32 locations within the central
208.
•
binocular full threshold central field assessment.
• fixation monitoring was disabled to allow thresholds to be determined
under binocular conditions using the 24-2 SITA Standard program.
The monocular full threshold field plots were merged using the Progressor software
to create the IVF (Figure 2.1). This provides an estimate of the central binocular
visual field without additional testing (Crabb et al., 1998, 2004; Crabb and
Viswanathan, 2005). For glaucoma patients, the comparison of locations with a
threshold ,10 dB has shown the IVF to be equivalent to the Esterman test but with
a slightly greater sampling of points within the central 208.
Figure 2.1: An image captured from the software developed to produce the IVF.
The example shows a patient with visual field defects in both eyes. The
left and right monocular fields are shown as Humphrey type
greyscales. The IVF is shown in the lower left panel. The lower right
panel is the same binocular reconstruction with superimposed
symbols denoting defects and indicating those with a sensitivity of less
than 10 dB. The superimposed blue circle indicates the limits of the
central 208 of field
29
Central Scotomata and Driving
Psychophysical tests
A series of testing tools designed to address some of the shortcomings of the
standard tests of vision has been developed for use at the City University site. The
tests are:
•
the Advanced Perimetry Program (APP):
• a high resolution visual field test capable of providing a detailed plot
of both absolute and relative scotomata within the central 208 of
visual field. Four suprathreshold levels are used and a sensitivity score
can be calculated for each quadrant.
•
the Advanced Vision Assessment (AVA) tests:
• Contrast Threshold Test (CTT);
• Contrast Acuity Test (CAT);
• Motion Perception Test (MPT); and
• Colour Assessment and Diagnosis (CAD).
For each of the AVA tests, visual function was assessed at the fovea and at four
locations paracentrally, with the stimulus centred at 68 eccentricity in the following
directions: 458, 1358, 2258, 3158or UR (upper right), UL (upper left), LL (lower left)
and LR (lower right) respectively (Figure 2.2). Use of the same locations for each of
the AVA tests facilitated data comparison between the patient group and the control
group. The selection of targets centred 68 from fixation focused on a central region
of the field neglected by the Esterman test yet likely to have an influence on driving
performance.
Figure 2.2: Examples of the motion perception stimuli, illustrating the five
locations assessed by the AVA tests
30
The new testing tools listed above were all run on the P_SCAN 100 system (Barbur,
1991; Barbur et al., 1987), which allows the presentation of visual stimuli of
specified colour and luminance contrast on a 21-inch high-resolution Sony Trinitron
monitor (model 500PS). A luminance calibration program was used monthly in
conjunction with an LMT 1003 luminance meter to calibrate the luminance
characteristics of the monitor. The monitor was allowed to warm up for a minimum
of 20 minutes before use to allow stabilisation of its luminance output.
A full description of these tests and their development is available on request from
the authors or from the Department for Transport.
Proxy measures of driving safety
The proxy measures of safe driving for all volunteers examined at City University
were:
•
driver history and recent adverse traffic event history self-report as declared on a
questionnaire;
•
•
the UFOV test; and
HPT.
At the Aston University site, 40 normal volunteers were recruited and assessed on
the UFOV test. These results were combined with those of the normal group
assessed at City University (n ¼ 60) to determine the normal range of results in
different age groups. At Aston University, a subgroup underwent repeat testing to
determine the repeatability of the UFOV test and to examine learning effects.
At the Nottingham University site, 72 normal volunteers were recruited to determine
the normal range of results for the HPT. A subgroup underwent repeat testing to
determine the repeatability of the HPT. Twenty-seven of these normal volunteers
completed both the HPT and UFOV tests.
None of the participants recruited at either Aston or Nottingham were included in
the normal group examined at City University. Patient volunteers recruited to the
patient group completed the UFOV test and HPT at City University.
The Useful Field of View Test
The UFOV test (Visual Attention Analyzer Model 2000, Visual Resources, Inc
Chicago, USA) is a computer administered test of visual attention. The test
expresses the patient’s UFOV score as a percentage reduction from the ideal. The
developers of the test have shown the UFOV score to be a predictor of crash risk in
elderly drivers (Ball et al., 1993; Owsley et al., 1998a, 1998b) and therefore the test
was included in this study as a proxy measure of driving safety. The original,
validated software presenting peripheral stimuli at three different eccentricities was
31
Central Scotomata and Driving
used (Ball et al., 1993) since the 3000 model had yet to be validated at the
commencement of this study (Ball et al., 2006).
The UFOV test consists of three parts:
•
Stage 1 (central vision processing speed) – the participant identifies a stimulus
(silhouette of a lorry or car) presented in the centre of a visual display screen for
a varying length of time.
•
Stage 2 (divided attention) – the participant identifies the central stimulus as
before but must also identify the direction in which a peripheral stimulus
(silhouette of a car) is located. This peripheral stimulus is displayed
simultaneously in any of 24 locations (eight possible directions at an eccentricity
of 108, 208 or 308, see Figure 2.3).
Figure 2.3: Example of a UFOV test layout for stage 2, showing the central lorry,
peripheral car and the 23 other possible locations for the peripheral
stimulus
•
Stage 3 (selective attention) – this is similar to stage 2, except that the
peripheral stimulus must be differentiated from 47 distracters (triangles), making
the task significantly more difficult.
Both central and peripheral stimuli are of high, positive suprathreshold contrast
(white targets on a black background), with a visual angle of 58. A chin rest was
used to maintain a constant working distance and visual angle throughout. Only the
introductory practice session was carried out before the data collection run.
Two identical set-ups allowed the UFOV test to be carried out on normal volunteers
(City and Aston University sites) and patient volunteers (City University). Identical
verbal instructions were given to all participants.
32
A full description of the UFOV test, including the normal range and repeatability, is
available on request from the authors or from the Department for Transport.
Hazard Perception Test
The HPT examines the ability to detect hazards in a series of videos of moving road
scenes. Twenty-six film clips were made available to the research team from a series
known to predict driver safety (Grayson and Sexton, 2002), therefore the test was
included in this study as a proxy measure of driving safety.
The videos covered a range of environments (dual carriageway, rural lane, busy
urban road, etc.) and each contained between one and three hazardous driving
events. The camera-car took the appropriate evasive action when reaching the
hazard (Figure 2.4).
Three main hazard types were defined:
•
•
•
movement of another object into the path of the driver (e.g. a cyclist);
unexpected actions of the vehicle in front (e.g. braking); and
hazardous actions of oncoming traffic (e.g. turning in front of the camera car).
Figure 2.4: Sample screen-dump from the HPT showing a hazardous event – the
parked car on the left requires the camera-car to pull-out, potentially
into the path of the approaching car
33
Central Scotomata and Driving
Two identical set-ups allowed the HPT to be carried out on normal volunteers at
Nottingham University and patient volunteers at City University. The same
instructions were given to participants at each of the two sites to ensure that all
participants had the same understanding of what constitutes a hazard, in an effort to
minimise variability. Following calibration of the eye tracker, each subject was
shown two introductory videos prior to the commencement of data collection, to
allow them to familiarise themselves with the task and the hazard response button.
A report providing further details of the HPT, including the normal range and
repeatability of results, is available on request from the authors or from the
Department for Transport.
2.2.2.2 Comparison of the standard tests of vision with the new tests developed
for use at City University
Tables 2.1 and 2.2 show some advantages and disadvantages of the standard and
new tests of vision included in this study.
Table 2.1: Some advantages and disadvantages of the standard tests of vision
included in this study
34
Test
Description
Some pros and cons
Esterman
binocular test
Conventional suprathreshold Simple, rapid assessment of visual field
Only detects dense scotomata
perimetry of the binocular
Sparse sampling, particularly within the
visual field
functionally-relevant area
No locations tested within central 7.58 of the
field
Fusional problems associated with binocular
testing
No assessment of visual functions other than
the ability to detect a target
IVF
Estimated binocular visual
field derived from HFA
monocular threshold plots
UFOV
Employs very large high-contrast targets
Visual attention test.
Examines the ability to locate Poor test strategy for use in participants with
scotomata
a peripheral target while
completing a centrallylocated visual task. Apparent
predictor of crash risk
HPT
Tests detection and
anticipation of hazardous
situations
Video-based test; free eye
and head movements
Reveals relative scotomata
Improved sampling density compared to
Esterman
Overcomes fusional problems associated with
binocular assessment
Tests only central area of field
No information on peripheral field
No assessment of visual functions other than
the ability to detect a target
Participants consider the test relevant to driving
Hazard cannot be mapped to the location of the
visual field defect
Response is very personality dependent
Undemanding visual task
Table 2.2: Some advantages and disadvantages of the new tests of vision
Test
Description
Some pros and cons
APP
Advanced Perimetry Program –
binocular central visual field test
with high sampling density
High resolution and four suprathreshold levels
provide a better description of visual field loss than
the Esterman
70 cm testing distance avoids fusional problems
Scoring system requires simplification
CTT
Contrast Threshold Test
Assess visual functions, other than luminance
difference threshold, thought to be relevant to
driving
CAT
Contrast Acuity Test
Show visual loss outside any scotoma and residual
vision within any scotoma
MPT
Motion Perception Test
More subtle visual loss can be detected
CAD
Colour Assessment and Diagnosis Assessment of all five locations is time consuming
Test
2.2.2.3 Data analysis
Statistical analysis was conducted using Minitab Version 14. The wide variation in
size, location and aetiology of the visual field loss in the patient group means that it
would be inappropriate to carry out any group analysis of the patient data from the
AVA tests and the visual field tests. Therefore, individual patients were categorised
as pass or fail for each test based on the established criteria (Esterman (DVLA,
2005), IVF (Crabb et al., 2004), UFOV (Owsley et al., 1998b)), or the 90th
percentile of the typical normal observer for his or her age group where such criteria
are not available (AVA tests, HPT). For the UFOV test, both the established pass/fail
cut-off of 40% loss of UFOV and the normal reference interval for each age group
were available. The number of normal volunteers in each age group was evenly
distributed across the decades from 20 to 90 years of age. Following the removal of
outliers,3 non-parametric statistics were used to establish the normal reference
intervals since the data tended not to be normally distributed for the older age
groups.
2 3 2 frequency tables were used to examine the degree of agreement between the
current gold standard (Esterman) and the other tests in the test battery. Kappa values
were calculated to assess the agreement beyond what would be expected by chance
alone. Sensitivity and specificity values were calculated to examine the ability of
alternative tests to predict the outcome of the gold standard. To investigate the
possibility that this reliance on the Esterman test is ill-founded, and that either the
UFOV or the HPT would be an improved gold standard, all our pass/fail driving data
for each test (including all the AVA tests) have been reanalysed with, first, the
3
Outliers were identified using the conservative 4* Stdev rule (Sachs, 2004).
35
Central Scotomata and Driving
UFOV test and then the HPT taken as the gold standard. The majority of participants
completed the whole test battery but the numbers completing each test vary slightly
due to a few individuals experiencing fatigue, or motion sickness (HPT), or not
being available for a further visit.
A two-way ANOVA was used to compare the patient and the normal group for the
UFOV test and also the HPT test. The results were adjusted for age where necessary.
36
RESULTS
The 60 volunteers who formed the patient group suffer from a wide range of
ophthalmological and neurological conditions, which provide a representative
sample of visual field loss within the central 208. This range is illustrated in Figure
3.1, a composite of all the monocular HFA grey scale plots for all the patients, and
Figure 3.2 which shows the distribution of Esterman Efficiency Scores (which can
range from 100%, representing no points missed on the Esterman test, to zero) for
all 60 patients.
Figure 3.1: Composite picture of monocular HFA grey scale plots for all 60
patients
Figure 3.2: Esterman Efficiency Scores for all 60 patients
30
25
20
Frequency
3
15
10
5
0
0⫺9
20⫺29
40⫺49
60⫺69
80⫺89
100
10⫺19
30⫺39
50⫺59
70⫺79
90⫺99
Esterman Efficiency Score (%)
37
Central Scotomata and Driving
3.1
Driving status of the patient group
Driving status, determined by means of self-reporting using a questionnaire,
established whether each volunteer held a current licence, whether they had lost or
never held a licence, the date of and reason for any loss of licence, whether those
eligible were currently driving and, if not, why not. Accident history was also sought
but no patients reported any accidents. The outcome of the driving questionnaire is
presented in Table 3.1. It also includes details of whether each patient passed or
failed the Esterman and IVF tests.
It should be noted throughout this results section that there are differences in the
number of patients who attempted each test conducted as part of our test battery.
Table 3.1: Questionnaire data on driving status and history. Driving status
according to performance on the Esterman and IVF tests is presented
Totals
Patients
(n 60)
Current UK licence holders
(n 36)
UK licence
Driving
Never
Current
11
36
Not currently
Currently
Not currently
20
16
13
Esterman test outcome
Esterman pass
Esterman fail
No Esterman
4
4
3
28
7
1
1
12
0
18
2
0
10
5
1
18
1
1
10
6
0
IVF test outcome
IVF pass
IVF fail
No IVF
6
4
1
28
7
1
4
8
1
3.1.1 Driving status according to Esterman pass/fail
Of the 56 patients who underwent Esterman testing, 33 passed and 23 failed the
current DVLA visual field criteria for holding a Group I driving licence. Much of
our analysis of results has focused on the performance of the ‘Esterman passed’ and
‘Esterman failed’ subgroups on other tests, including the proxy measures of driving,
the UFOV and HPT tests.
Of the 33 patients who passed the Esterman criteria for driving, 28 have a current
driving licence, one did not have a licence (which he had handed in himself because
he did not feel safe) and four had never driven. Of the drivers who held a UK driving
licence, 18 were driving and 10 were not.
38
Of the 23 patients who failed the Esterman criteria, seven had a UK licence, 12 did
not have a licence (five by DVLA action) and four had never driven. It is particularly
noteworthy that two patients who failed the Esterman criteria were still driving.
3.1.2 Driving status according to IVF pass/fail
Out of our total sample of 60 patients, 57 carried out the IVF testing procedure. Of
the 38 patients who passed the IVF criteria for driving suggested by Crabb et al.
(1998, 2004; Crabb and Viswanathan 2005), 28 had a driving licence, four did not
currently have a licence, and six had never driven. Of the licence holders, 18 were
driving and 10 were not, even though they had a licence.
Of the 19 patients who failed the IVF criteria, seven had a licence, eight did not
have a licence and four had never driven. One patient who failed on the IVF criteria
was still driving.
3.1.3 Esterman test taken as the ‘gold standard’ compared with other
tests
For each subject we analysed the agreement between the pass/fail decisions on
fitness to drive based on the current DVLA requirements in 2005 (Esterman test)
and the remaining battery of tests (Table 3.2). It should be noted that the Esterman
Table 3.2: Frequency tables showing pass/fail decisions on fitness to drive based on the
gold standard Esterman test compared with the remaining battery of tests
Esterman fail
(+ve)
Esterman
pass (–ve)
Agreement
(kappa)
Sensitivity
Specificity
IVF (n
54)
Fail (+ve)
Pass (–ve)
18
3
1
32
93%
(0.84)
86%
97%
CT (n
55)
Fail (+ve)
Pass (–ve)
21
2
25
7
51%
(0.12)
91%
22%
CA (n
53)
Fail (+ve)
Pass (–ve)
21
1
27
4
47%
(0.07)
95%
13%
Motion (n
50)
Fail (+ve)
Pass (–ve)
12
8
15
15
54%
(0.18)
60%
50%
Colour (n
47)
Fail (+ve)
Pass (–ve)
18
0
27
2
43%
(0.05)
100%
7%
Fail (+ve)
Pass (–ve)
7
14
4
27
65%
(0.22)
33%
87%
7
5
65%
39%
82%
22%
86%
UFOV (n
52)
HPT response
time
(n 46)
Fail (+ve)
Pass (–ve)
11
23
(0.22)
HPT % hazards
(n 46)
Fail (+ve)
Pass (–ve)
4
14
4
24
61%
(0.09)
39
Central Scotomata and Driving
visual field criteria used by the DVLA comprise criteria for central and/or peripheral
fields. However, pass/fail decisions for all the other tests in our battery are based on
results obtained solely from the central region of the visual field.
The percentage of observed agreements quoted in Table 3.2 is a crude measure of
agreement between any two tests. The kappa value assesses the agreement beyond
what would be expected by chance alone. There is excellent agreement between the
Esterman and IVF tests (kappa ¼ 0.84) and this is analysed further in Section 3.1.4.
Agreement was poor between all of the AVA tests (CT, CA, Motion or Colour) and
the Esterman pass/fail criteria. Noteworthy are the very high sensitivities and very
low specificities for CT, CA and Colour, with many participants failing these tests
despite passing the Esterman test. However, the pass/fail criteria we used for the
AVA tests were established on the basis of the 90th percentile normal limits of
performance for controls and are likely to be overly stringent.
The UFOV and HPT tests show very poor agreement with the Esterman test and
very low sensitivities, notably with 14 participants passing on the UFOV test but
failing the Esterman, and 14 passing the HPT test for hazard detection and failing
the Esterman. These proxy measures of driving are considered in more detail in
Sections 3.1.6 and 3.1.7.
3.1.4 Agreement between the Esterman and the Integrated Visual Field
The kappa value for the Esterman/IVF agreement is 0.84, which is classified as
‘very good’. 54 patients completed both the Esterman and IVF tests. Of particular
interest are three participants (6%) who passed the IVF but failed the Esterman test.
All three had cortical lesions with visual field loss that was peripheral but extended
into the central 208. In an earlier study on glaucoma patients (Crabb et al., 1998),
there were no participants who passed the IVF and failed the Esterman test.
Glaucoma patients tend, initially, to develop central binocular visual field loss, often
followed subsequently by peripheral field loss. This suggests that the IVF may
misclassify patients with peripheral loss alone, such as those with certain
neurological anomalies. Subdivision of our complete patient group into
glaucomatous and non-glaucomatous subsets allows for the further exploration of
this issue in Section 3.1.5.
In a separate study involving 40 of our patient group, we investigated the agreement
between the IVF and binocular visual fields collected using a ‘monocular’ test on the
HFA (using the SITA testing strategy) carried out with the patient keeping both eyes
open. Concordance between the binocular test and the IVF in the location and
general shape of binocular visual field defects was reasonable, and this suggests that
the IVF is a good predictor of significant defects in the central binocular fields.
However, point-wise agreement in sensitivity values in individual participants
ranged from acceptable to very poor and measured binocular sensitivity values were,
40
on average, significantly higher than predicted values (+1 dB), leading to measured
binocular scotomata appearing smaller than would be expected from the IVF.
Pointwise agreement in sensitivity values in individual participants ranged from
acceptable to very poor (95% limits of agreement from 4 dB to 18 dB). This
pointwise agreement also varied by threshold level, with acceptable agreement in
normal and very damaged areas of the visual field, but agreement was very poor in
locations where the measured threshold was between 5 dB and 20 dB – the range of
greatest interest. A high proportion of patients reported fusional problems during the
binocular full threshold measurement. A report detailing this study is available on
request from the authors or the Department for Transport.
It is worrying that two patients from our sample who are still driving failed the
Esterman test (both failed due to inadequate peripheral field).
3.1.5 IVF compared with the Esterman test in glaucomatous and nonglaucomatous patients
Table 3.3 illustrates the pass/fail decisions on fitness to drive based on the Esterman
and IVF critera.
Table 3.3: Frequency tables showing pass/fail decisions on fitness to drive based
on the outcomes of the Esterman and IVF tests for glaucoma and nonglaucoma patient subgroups
Glaucoma patients (n
23)*
Non-glaucoma patients (n
36)
Esterman fail
Esterman pass
Esterman fail
Esterman pass
IVF fail
5
0
13
1
IVF pass
0
15
3
16
Agreement
Kappa
100%
88%
1.00
0.76
Glaucoma patients (n 23)*
Esterman pass
Esterman fail
Agreement
Kappa
Non-glaucoma patients (n
36)
IVF pass
IVF fail
IVF pass
IVF fail
15
0
16
1
0
5
3
13
100%
88%
1.00
0.76
* Three glaucoma subjects did not complete the Esterman test
+ Three non-glaucoma subjects did not complete the IVF test, and one of these three also failed
to complete the Esterman test
41
Central Scotomata and Driving
3.1.6 UFOV test taken as the ‘gold standard’ compared with other tests
There was limited agreement between the UFOV and Esterman tests (kappa ¼ 0.22),
and the UFOV and IVF tests (69%, kappa ¼ 0.23). A high proportion of patients
failed the Esterman test but passed UFOV (27%) or failed IVF but passed UFOV
(21%). Therefore the UFOV test only identified 33% of patients who would be
considered unfit to drive based on the current UK visual field requirements, although
it correctly identified 87% of patients who would be considered fit to drive (Table
3.2). If the UFOV test were to be adopted as the gold standard, the Esterman
correctly identified 64% of patients who failed the UFOV and 66% of those who
passed the UFOV (Table 3.4).
Table 3.4: Frequency tables showing pass/fail decisions on fitness to drive based on the
UFOV as the gold standard compared with the remaining battery of tests
Esterman (n
52)
UFOV fail
(+ve)
UFOV pass
(–ve)
Agreement
(kappa)
Sensitivity
Specificity
Fail (+ve)
Pass (–ve)
7
4
14
27
65% (0.22)
64%
66%
IVF (n
52)
Fail (+ve)
Pass (–ve)
6
5
11
30
69% (0.23)
55%
73%
CT (n
56)
Fail (+ve)
Pass (–ve)
10
2
34
10
32% (0.03)
83%
17%
CA (n
51)
Fail (+ve)
Pass (–ve)
9
2
38
2
22% (–0.06)
82%
5%
Motion (n
47)
Fail (+ve)
Pass (–ve)
8
1
18
20
60% (0.24)
89%
53%
Colour (n
44)
Fail (+ve)
Pass (–ve)
10
0
33
1
25% (0.01)
100%
3%
Mean UFOV scores were not significantly different between those who passed both
the Esterman and IVF tests and those who failed both. It appears that for this group
of patients, the UFOV is unable to discriminate between those classified as fit to
drive and those classified unfit on the basis of visual fields.
Dividing the patient group into those whose field loss was retinal in origin and those
whose field loss resulted from a neurological lesion, a similar proportion of patients
in each group failed the UFOV (7/21 retinal, 5/20 neurological). This suggests that
UFOV failure in this group of patients was caused by functional deficits associated
with the visual field loss rather than a neurological deficit affecting attention.
The standard UFOV pass/fail criterion of 40% was used in Tables 3.4 and 3.7. As
part of this study we have calculated age-matched limits for 100 normal observers
on the UFOV test (a full description of this sub-study is available on request from
42
the authors or from the Department for Transport). Eighty-five per cent (46 out of
54) of the patients with central scotomata had a UFOV score that fell within the agematched limits (90th percentile) of the normal range. Agreement between the UFOV
and visual field tests remains poor when recalculated on the basis of these limits.
Considering those patients who passed the Esterman, 12% who passed on the
standard 40% UFOV criteria lay outside the age-matched limits for controls, while
three of the four patients who failed by the standard UFOV criteria lay within the
age-matched limits for controls. Considering those patients who failed the Esterman
test, only two of the fourteen fails had UFOV scores that were outside the agematched limit for controls, while three of the seven patients who failed by the
standard UFOV criteria had scores on the test that were within the age-matched
limits for controls (Figure 3.3).
Figure 3.3: Age stratified comparison of the total UFOV scores (%) recorded for 54
patients with central scotomata (circles) versus 100 standard normal
drivers (median values are shown as a solid line flanked by an upper
and lower dashed line representing the 10th and 90th percentiles,
respectively). The dotted and dashed line indicates the UFOV pass/fail
border (UFOV score of 40%)
100.0
90.0
80.0
Total UFOV score (%)
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
20⫺29
30⫺39
40⫺49
50⫺59
Age group (years)
60⫺69
70⫹
Despite the high proportion of patients whose UFOV score fell within the agematched normal range, statistical analysis indicates that the mean total UFOV score
was significantly higher in the patient group than the normal group. However, the
43
Central Scotomata and Driving
difference between the two groups barely reached clinical significance because the
variability of the UFOV test, expressed by the repeatability standard deviation, was
found to be 5.5% compared with a difference between the mean UFOV scores of
groups of 6.6%.
Agreement was poor between the AVA tests (Contrast Threshold, Contrast Acuity,
Motion and Colour) and the UFOV since the majority of patients passed the UFOV
but fell outside the 90th percentile of the normal range for each of the AVA tests
(fail).
3.1.7 HPT test taken as the ‘gold standard’ compared with other tests
HPT performance was judged in terms of the percentage of hazards missed (%
missed) and the mean hazard response time (RT). As demonstrated by Figures 3.3
and 3.4, neither of our HPT performance measures demonstrated a significant
relationship with age (two-way ANOVA, p . 0.1) and therefore we selected the 90th
percentile of the normal range (30.3% for % missed and 5054 ms for RT) as the
pass/fail boundary. The proportion of the patient group who fell within this range
was 81.3% (39/48) and 75.0% (36/48) for the % missed and the RT respectively.
Table 3.5: Frequency tables showing pass/fail decisions on fitness to drive based on the
HPT parameter hazard (percentage of hazards missed) as the gold standard
compared with the remaining battery of tests
HPT
% hazards missed
Esterman (n
46)
Agreement
(kappa)
Sensitivity Specificity
Fail (+ve)
Pass (–ve)
Fail (+ve)
Pass (–ve)
4
4
14
24
61% (0.09)
50%
63%
IVF (n
45)
Fail (+ve)
Pass (–ve)
4
5
11
25
64% (0.11)
44%
69%
CT (n
46)
Fail (+ve)
Pass (–ve)
8
0
30
8
35% (0.08)
100%
21%
CA (n
45)
Fail (+ve)
Pass (–ve)
7
1
33
4
24% (–0.01)
88%
11%
Motion (n
43)
Fail (+ve)
Pass (–ve)
6
2
17
18
56% (0.15)
75%
51%
Colour (n
42)
Fail (+ve)
Pass (–ve)
7
0
33
2
21% (0.02)
100%
6%
Agreement between the Esterman test and the HPT for % missed was only 61% with
a very poor kappa value (0.09) (Table 3.5). This lack of agreement was most clearly
revealed by the 37% of patients (n ¼ 14) who failed the Esterman test yet passed the
44
HPT. A similar level of agreement exists for the IVF (64%, kappa ¼ 0.11), with
31% (n ¼ 11) of patients failing the IVF test but passing the HPT. The mean
percentage of hazards missed by the normal group was 16%, highlighting one of the
limitations of the HPT.
Agreement between the Esterman test and RT (HPT) was fair (65%, kappa ¼ 0.22),
highlighted by the 32% of patients (n ¼ 11) who failed the Esterman test but passed
the HPT for this measure of performance (Table 3.6). Agreement was slightly better
between the IVF and RT (71%, kappa ¼ 0.32), with 24% (n ¼ 8) of patients failing
the IVF but passing the HPT.
Agreement was poor between three of the AVA tests (Contrast Threshold, Contrast
Acuity, and Colour) and the HPT for both parameters with very low specificities but
good sensitivities. However, the Motion test showed better agreement with the HPT
for both parameters, with sensitivities higher, though specificities lower, than
achieved with the Esterman and IVF, although the kappa value was still low (0.15).
Since a logarithmic transformation was needed to produce a normal distribution for
both measures of HPT performance, and allow the use of parametric statistics,
agreement figures were recalculated using the 90th percentile of the log10 HPT data
as the pass/fail boundary. In all cases, agreement was even weaker than before the
logarithmic transformation was applied.
Table 3.6: Frequency tables showing pass/fail decisions on fitness to drive based on the
HPT parameter time (mean hazard response time) as the gold standard
compared with the remaining battery of tests
HPT response time
Esterman (n
46)
Agreement
(kappa)
Sensitivity
Specificity
Fail (+ve)
Pass (–ve)
Fail (+ve)
Pass (–ve)
7
5
11
23
65% (0.22)
58%
67%
IVF (n
45)
Fail (+ve)
Pass (–ve)
7
5
8
25
71% (0.32)
58%
76%
CT (n
46)
Fail (+ve)
Pass (–ve)
11
1
27
7
39% (0.07)
92%
21%
CA (n
45)
Fail (+ve)
Pass (–ve)
10
1
30
4
31% (0.01)
91%
12%
Motion (n
43)
Fail (+ve)
Pass (–ve)
7
3
16
17
56% (0.15)
70%
52%
Colour (n
42)
Fail (+ve)
Pass (–ve)
10
0
30
2
29% (0.03)
100%
6%
45
Central Scotomata and Driving
Figures 3.4, 3.5, 3.6 and 3.7 illustrate the comparison between patient and control
groups for each of the two HPT performance measures. Mean log10 hazard response
time ( p ¼ 0.000), mean saccadic amplitude ( p ¼ 0.000) and mean horizontal
variance of fixation ( p ¼ 0.003) were significantly higher for the patient group
Figure 3.4: log10 hazard response time plotted against age for the patient group
and median age for the control group. The upper and lower dotted
lines show the 90th and 10th percentile limits for the control group
Median hazard response time (ms)
10,000
9,000
Control group
Patient group
8,000
7,000
6,000
5,000
4,000
3,000
2,000
20
30
40
50
60
Median age (yrs)
70
80
90
Figure 3.5: log10 %missed hazards plotted against age for the patient group and
median age for the control group. The upper and lower dotted lines
show the 90th and 10th percentile limits for the control group
Median percentage of hazards missed (%)
100
80
70
60
50
40
30
20
10
0
20
46
Control group
Patient group
90
30
40
50
60
Median age (yrs)
70
80
90
Figure 3.6: HPT – the percentage of hazards missed by the control and patient
groups do not differ significantly. The box indicates the 10th , 50th , and
90th percentiles
100
% of hazards missed
80
60
40
20
0
Normals (72)
Patients (49)
Figure 3.7: HPT – the mean response time to hazards is significantly longer for the
patient group than the control group. The box indicates the 10th , 50th ,
and 90th percentiles
Mean hazard response time (ms)
10,000
8,000
6,000
4,000
2,000
0
Normals (72)
Patients (49)
compared with the control group. This is despite the high proportion of patients
whose mean hazard response time fell within the 90th percentile of the normal
range. Neither mean log10 percentage of hazards missed nor mean fixation duration
differed significantly between the patient and control groups (two-way ANOVA, p ¼
0.825 and p ¼ 0.443 respectively). Age did not significantly affect any of the
measured HPT parameters (Figures 3.4 and 3.5).
47
Central Scotomata and Driving
3.1.8 UFOV test taken as the ‘gold standard’ compared with HPT
There is good agreement between the UFOV and HPT for the small sample (n ¼ 27)
of controls who underwent both tests. The one normal subject who passed the HPT
for both criteria that we employed, but failed the UFOV was aged 77 years.
Table 3.7: Frequency tables showing pass/fail decisions on fitness to drive based on the
UFOV as the gold standard compared with the HPT parameters % hazards
missed and hazard response time for both patient and normal groups
UFOV Fail (+ve) UFOV Pass
(–ve)
Patient
group
(n 46)
Normal
group
(n 27)
Agreement
(kappa)
Sensitivity Specificity
HPT %
missed
Fail (+ve)
Pass (–ve)
2
9
7
28
65% (–0.02)
18%
80%
HPT RT
Fail (+ve)
Pass (–ve)
5
6
7
28
72% (0.25)
55%
80%
HPT %
missed
Fail (+ve)
Pass (–ve)
0
1
1
25
93% (–0.04)
0%
96%
HPT RT
Fail (+ve)
Pass (–ve)
0
1
4
22
81% (–0.06)
0%
85%
For the patient group, agreement between the two proposed proxy measures of
driving safety was very poor for % missed (kappa ¼ -0.02) and fair for HPT RT
(kappa ¼ 0.25) (Table 3.7). Agreement appears to be significantly better for the
normal group due to the high pass rate for both proxy measures but the kappa values
indicates that the agreement is no higher than would occur by chance alone.
3.1.9 AVA tests
Data are presented for each test to demonstrate the variation in each parameter with
age, for both the foveal (Figures 3.8, 3.10, 3.12, 3.14, 3.15) and paracentral locations
(Figures 3.9, 3.11, 3.13, 3.16, 3.17). We had a particular interest in the patients’
performance on these tests in regions that lay outside the areas of scotoma identified
by conventional methods of field testing. Therefore, paracentral locations lying
within the scotomatous region identified by the Esterman test (,10 dB) have been
omitted from the following analysis. Within the scotoma, either the stimulus was not
detected at the phosphor limits of the display or the stimulus had to be close to the
phosphor limits of the display to be detected. The mean of the remaining locations
was plotted against age (Figures 3.8–3.17). Contrast detection and motion
perception were the least affected stimulus attributes in our patient group. Contrast
acuity and the ability to detect colour tended to be the most affected stimulus
attributes. The pass/fail criteria we used for the AVA tests were established on the
basis of the 90th percentile normal limits of performance derived from our small
age-matched normal groups. It is a feature of the AVA tests and clear from the poor
agreement with other tests, that these normal limits are likely to be overly stringent
and need revision.
48
3.1.9.1 Contrast detection test
Contrast detection increases with age at both the fovea and paracentrally for controls
and patients aged over 50 years. Many of the patients show thresholds outside the
90th percentile range for controls in areas of the paracentral visual field external to
the binocular scotomata (Figures 3.8 and 3.9).
Figure 3.8: Foveal contrast detection thresholds plotted against age for the
control group (10th , 50th and 90th percentiles) and the patient group
Contrast detection threshold (δL/Lb)
300
250
Fovea
Control group
Patient group
200
150
100
50
0
20
30
40
50
60
Median age (yrs)
70
80
90
Figure 3.9: Paracentral contrast detection thresholds plotted against age for the
control group (10th , 50th and 90th percentiles) and the patient group
Contrast detection threshold (δL/Lb)
350
300
Paracentral
Control group
Patient group
250
200
150
100
50
0
20
30
40
50
60
70
80
90
Median age (yrs)
49
Central Scotomata and Driving
3.1.9.2 Contrast acuity
Contrast acuity increases markedly with age at the fovea for controls and patients
aged over 50 years. A similar effect is observed at the paracentral locations where
the increase is more dramatic in both groups. Most of the patients lie outside the
90th percentile range for age-matched controls (Figures 3.10 and 3.11).
Figure 3.10: Foveal contrast acuity thresholds plotted against age for the control
group (10th , 50th and 90th percentiles) and the patient group
Fovea
Control group
Patient group
Contrast acuity threshold (δL/Lb)
700
600
500
400
300
200
100
0
20
30
40
50
60
Median age (yrs)
70
80
90
Figure 3.11: Paracentral contrast acuity thresholds plotted against age for the
control group (10th , 50th and 90th percentiles) and the patient group
Contrast acuity threshold (δL/Lb)
700
Paracentral
Control group
Patient group
600
500
400
300
200
100
0
20
50
30
40
50
60
Median age (yrs)
70
80
90
3.1.9.3 Motion discrimination
Compared with the other AVA tests, fewer patients have motion detection thresholds
outside the 90th percentile normal limits (Figures 3.12 and 3.13).
Figure 3.12: Foveal motion detection thresholds plotted against age for the
control group (10th , 50th and 90th percentiles) and the patient group
Motion detection threshold (%)
10
8
Fovea
Control group
Patient group
6
4
2
0
20
30
40
50
60
Median age (yrs)
70
80
90
Figure 3.13: Paracentral motion detection thresholds plotted against age for the
control group (10th , 50th and 90th percentiles) and the patient group
Motion detection threshold (%)
10
Paracentral
Control group
Patient group
8
6
4
2
0
20
30
40
50
60
Median age (yrs)
70
80
90
51
Central Scotomata and Driving
3.1.9.4 Colour vision
In all four colour figures (Figures 3.14–3.17), most of the patients lie outside the 90th
percentile range for controls for both blue/yellow and red/green colour discrimination
in areas of the paracentral visual field external to the binocular scotomata.
Figure 3.14: Foveal chromatic discrimination for blue-yellow plotted against age
for the control group (10th , 50th and 90th percentiles) and the patient
group
0.2
Chromatic displacement
Fovea
Control group
Patient group
0.15
0.1
0.05
0
20
30
40
50
60
Median age (yrs)
70
80
90
Figure 3.15: Foveal chromatic discrimination for red/green plotted against age for
the control group (10th , 50th and 90th percentiles) and the patient
group
0.2
Chromatic displacement
Fovea
Control group
Patient group
0.15
0.1
0.05
0
20
52
30
40
50
60
Median age (yrs)
70
80
90
Figure 3.16: Paracentral chromatic discrimination for blue-yellow plotted against
age for the control group (10th , 50th and 90th percentiles) and the
patient group
0.2
Chromatic displacement
Paracentral
Control group
Patient group
0.15
0.1
0.05
0
20
30
40
50
60
Median age (yrs)
70
80
90
Figure 3.17: Paracentral chromatic discrimination for red-green plotted against
age for the control group (10th , 50th and 90th percentiles) and the
patient group
0.2
Chromatic displacement
Paracentral
Control group
Patient group
0.15
0.1
0.05
0
20
30
40
50
60
Median age (yrs)
70
80
90
53
Central Scotomata and Driving
3.2
Data from sample patients
3.2.1 Patient 31
Patient 31 (Tables 3.8 and 3.9, Figures 3.18 and 3.19) is an example of a subject
who passes the current DVLA requirements but probably because of the poor design
of the Esterman test. The IVF and APP tests with their superior sampling density
reveal a significant binocular defect in the inferior visual field, just below fixation.
Visual acuity is unaffected. The patient still holds a UK licence although does not
drive for financial reasons.
Table 3.8: Details for patient 31
Age
36
Diagnosis
Bilateral optic nerve
compression (tumour)
UK Licence
Driving
Yes
No
Comment
Stopped 1998 due
to cost
Figure 3.18: Esterman plot for patient 31 indicating a pass since there were no
points missed within the central 208 area and the peripheral field
extends beyond 1208 in the horizontal meridian
The attempt to measure the binocular thresholds on the HFA reveals a very small
isolated scotoma close to fixation. Comparing this plot to the two monocular plots
indicates that this technique has significantly underestimated the visual field loss in
this patient, probably due to compensatory eye movements and fusional difficulties.
54
Figure 3.19: HFA threshold plots for patient 31 indicating an inferior ‘fingershaped’ field defect that lies very close to fixation: (a) monocular
threshold plot for the left eye indicating little residual central field;
(b) monocular threshold plot for the right eye; (c) measured binocular
thresholds, significantly underestimating the defect; (d) IVF (estimate
of binocular thresholds); and (e) seven data points with a threshold of
less than 10 dB indicating a fail on the IVF
Table 3.9: Results for patient 31
Patient
31
Pass/fail
Visual field tests
Esterman
IVF
Pass
Fail
UFOV
APP
Impaired
inferior
field
Pass
5%
HPT
AVA tests
Hazard
Time
CT, CA, Motion, Colour
Pass
Pass
Fail inferiorly but
fovea and superior
also impaired
The APP test, along with the AVA tests, indicate that areas of the central visual field
external to the scotoma also show considerable visual impairment (contrast
detection and discrimination, motion and colour perception all affected at the fovea
and in the superior hemifield in addition to the inferior hemifield).
The patient achieved a pass on the UFOV with a score of 5% (0,0,5), which lies at
the upper end of the results achieved by the normal age-matched population.
Performance on the HPT was within the normal range with no hazards missed but a
mean response time close to the upper limit for the normal age-matched population.
55
Central Scotomata and Driving
3.2.2 Patient 55
Patient 55 (Tables 3.10 and 3.11, Figures 3.20 and 3.21) is an example of a subject
who failed the current DVLA requirements (Esterman) due to a significant superior
visual field defect, yet passed the two proxy measures of driving performance. Only
five points are missed on the Esterman but the IVF result suggests that many more
would be missed if the Esterman sampled within the central 7.58. The APP field
test and the AVA tests indicate that visual function in the inferior field, external to
the defect identified by the Esterman and IVF, is also substantially impaired.
Contrast detection and discrimination, along with motion and colour perception,
were outside the age-matched normal range at both the fovea and in both inferior
quadrants.
Table 3.10: Details for patient 55
Age
Diagnosis
UK licence
Driving
Comment
57
Glaucoma 15 years
Revoked
No
–
Figure 3.20: Esterman plot for patient 55 indicating a fail due to a cluster of three
adjoining points with additional scattered points within the central 208
area
56
Despite the extent of the paracentral scotomata, the patient achieved a pass on the
UFOV with a score of 30% (0,5,25). This lies close to the upper limit for the normal
age-matched reference range. Performance on the HPT was within the normal range
with only two hazards missed, although one of them was the police car which is seen
to approach from straight ahead over a number of seconds before turning round the
roundabout in front of the camera car.
Figure 3.21: HFA threshold plots for patient 55 indicating a significant binocular
superior field defect and relative loss in the inferior field: (a) and (b)
monocular threshold plots for left and right eyes respectively; (c) IVF
(estimate of binocular thresholds); and (d) 19 data points with a
threshold of less than 10 dB, indicating a fail on the IVF
Table 3.11: Results for patient 55
Patient
55
Visual field tests
Esterman
IVF
APP
Fail
Fail
All
quadrants
affected
Pass/
fail
UFOV
Pass
30%
HPT
AVA tests
Hazard
Time
CT, CA, Motion, Colour
Pass
Pass
Fails every test,
superior, inferior
and foveal regions
3.2.3 Patient 17
Patient 17 (Tables 3.12 and 3.13, Figures 3.22 and 3.23) fails the current DVLA
requirements (Esterman) yet passes the UFOV and the HPT (% of hazards seen).
The Esterman and IVF fields are in agreement.
57
Central Scotomata and Driving
Table 3.12: Details for patient 17
Age
56
Diagnosis
Longstanding bilateral optic
nerve lesion
UK licence
Driving
Comment
Revoked
No
–
Figure 3.22: Esterman plot for patient 17 indicating a fail due to a cluster of more
than four points within the central 208 area
The APP field test and the AVA tests indicate that visual function is impaired in the
left hemifield and inferior field, external to the defect identified by the Esterman and
IVF. Contrast detection and discrimination, along with colour perception (red-green)
were outside the age-matched normal range in these three quadrants. Interestingly,
motion perception was normal in all locations tested.
Despite the extensive paracentral visual field loss, the patient achieved a UFOV
score of 27.5% (0,5,22.5) which is close to the upper limit of the age-matched
normal group but nevertheless represents a pass. For the HPT, the percentage of
hazards missed fell within the normal range (14%) but the mean response time was
greatly increased, constituting a fail for this measure of performance.
58
Figure 3.23: HFA threshold plots for patient 17 indicating a significant binocular
visual field loss: (a) and (b) monocular threshold plots for left and right
eyes respectively; (c) measured binocular thresholds; (d) IVF(estimate
of binocular thresholds); and (e) data points with a threshold of less
than 10 dB indicating a fail on the IVF
Table 3.13: Results for patient 55
Patient
17
Visual field tests
Esterman
IVF
APP
Fail
Fail
Left and
inferior
affected
Pass/
fail
UFOV
Pass
27.5%
HPT
AVA tests
Hazard
Time
Pass
Fail
CT, CA, Motion,
Colour
Left hemifield
impaired for CT, CA
and Colour, Motion
normal
3.2.4 Patient 90
Patient 90 (Tables 3.14 and 3.15, Figures 3.24 and 3.25) meets the current DVLA
criteria and shows no significant visual field loss on the IVF. The APP field test
indicates a reduction in sensitivity in the left hemifield and this relates to the
increase in contrast detection thresholds at the fovea and in the left hemifield.
Motion perception was also impaired at the fovea and colour perception was
Table 3.14: Details for patient 90
Age
Diagnosis
UK licence
Driving
Comment
79
Glaucoma 3 years
Yes
Yes
–
59
Central Scotomata and Driving
Figure 3.24: Esterman plot for patient 90 showing five scattered points in the
periphery – this represents a pass
Figure 3.25: HFA threshold plots for patient 90: (a) and (b) monocular threshold
plots for left and right eyes respectively; (c) measured binocular
thresholds; (d) IVF (estimate of binocular thresholds); and (e) no data
points with a threshold of less than 10 dB
60
Table 3.15: Results for patient 90
Patient
90
Visual field tests
Pass/fail
UFOV
Esterman
IVF
APP
Pass
Pass
Impaired
left
hemifield
Fail
45%
HPT
AVA tests
Hazard
Time
CT, CA, Motion,
Colour
Pass
Pass
Patchy loss,
impaired colour
significantly worse than the age-matched normal range for red-green and, in
particular, blue-yellow, as would be expected in a glaucoma patient.
The patient achieved a UFOV score of 45% (0,15,30) which falls just within the
age-matched normal range but nevertheless represents a fail. Performance on the
HPT was within the normal range with no hazards missed.
3.2.5 Patient 103
Patient 103 (Tables 3.16 and 3.17, Figures 3.26 and 3.27) meets the current DVLA
Esterman criteria, missing only one point within the central 208. The IVF plot
indicates that the Esterman underestimates the size of the central defect due to the
absence of testing points within the central 7.58. The APP field test shows a
reduction in sensitivity in the upper-right quadrant, consistent with the IVF result,
which is also backed-up by the AVA tests. All four measures of visual performance
were impaired in the upper-right quadrant and contrast discrimination thresholds
were substantially higher than the age-matched normal range in all paracentral
locations.
Table 3.16: Details for patient 103
Age
Diagnosis
UK licence
Driving
Comment
79
Stroke resulting in cortical lesion
Yes
Yes
–
Table 3.17: Results for patient 103
Patient
103
Visual field tests
Esterman
Pass/fail
Pass
IVF
UFOV
APP
Pass Reduced
top-right
quadrant
Pass
17.5%
HPT
AVA tests
Hazard
Time
Fail
Fail
CT, CA, Motion,
Colour
CT, motion, colour
top right, CA all of
periphery
61
Central Scotomata and Driving
Figure 3.26: Esterman plot for patient 103 showing a single missed point within
the central 208 and three scattered missed points in the periphery –
this represents a pass
Figure 3.27: HFA threshold plots for patient 103: (a) and (b) monocular threshold
plots for left and right eyes respectively showing a partial upper right
quadrantanopia; (c) measured binocular thresholds; (d) IVF (estimate
of binocular thresholds); and (e) five data points with a threshold of
less than 10 dB
62
The patient achieved a UFOV score of 17.5% (0,0,17.5) which constitutes a pass.
The HPT was failed on the basis of a very slow response to the hazards (5.96
seconds) and a large proportion of missed hazards (34.4% missed). Detailed analysis
of eye movements indicated that patient 103 was scanning the screen more than
average.
63
4
DISCUSSION
4.1
Design of studies to assess the effects of visual field
defects on driving safety
The definitive study to assess the implications for driving safety of central scotomata
would include a wide-ranging road test involving non-licensed drivers.
Unfortunately running such a study is difficult in the UK because the participation
of non-legal drivers in a road test is highly problematic. Even the use of a driving
simulator is questionable for those no longer legal to drive because their driving
skills may have atrophied. The next best alternative is a prospective study involving
different groups of drivers which links their performance on visual tests to their
accident rates. However, the use of accident rates has its own inherent limitations,
since the occurrence of road accidents is statistically infrequent and because
reporting biases can affect accident self-reporting. In this study, none of the patients
admitted to having been involved in any accidents within the last three years.
4.2
Design of the current study
In our study several methods of measuring visual fields and other tests of visual
function (the AVA tests, which include motion and contrast discrimination tests)
have been employed to quantify the deficits of a group of 60 patients with a wide
range of visual field defects within the central 208. The visual field defects resulted
from two main causes: diseases affecting primarily the retina (notably glaucoma)
and neurological disorders affecting the visual pathway. Visual field performance
was assessed via the Esterman test and the Integrated Visual Field (IVF). In the
absence of an on-road test, simulator or accurate accident rate data, we used two
surrogate or proxy measures of driving safety. These are the Useful Field of View
(UFOV), a test of divided and selective visual attention shown to be predictive of
driver safety in older drivers, and the Hazard Perception Test (HPT), a test of ability
to identify road hazards correctly and in a timely way during driving. The HPT is
currently used for the UK driving licensing examination, although we modified the
performance criteria to examine both the proportion of hazards identified and the
average hazard response time, along with eye movement parameters.
A group of 72 non-visually impaired age-matched volunteers provided
quantification of the normal range of performance on each of the AVA tests, the
UFOV and the HPTs.
4.3
Driving status questionnaire
Driving status was established by means of self-reporting using a simple
questionnaire, as part of which we sought details of accident history. None of the 60
patients reported having had any accidents in the previous three years. A zero
64
accident rate is improbable in this sample, and may reflect the unreliability of
accident self-reporting, which is subject to various sources of error such as recall
bias and socially-desirable responding. However, it is also well known that drivers
with visual deficits may avoid driving in potentially hazardous situations (Slade et
al., 2002) and this may mitigate any higher road safety risks attributable to their
visual deficit.
4.4
Tests used
4.4.1 The Esterman test
Currently, Class 1 licensing decisions with respect to the visual field are based on
the outcome of the binocular Esterman test normally carried out on the HFA. The
Esterman test presents a bright stimulus at each of the 120 locations within the
visual field, arranged in a pattern that was originally designed to predict an
individual’s mobility (walking), not their driving performance. It is not surprising,
therefore, that the number of locations tested within the functionally-relevant area of
a driver’s visual field is very limited, with only 34 locations tested within the central
208, no locations within the central 7.58, and a predominance of these central
locations falling in the lower half of the visual field (22 versus 12). For further
details please see Section 1.8. In addition, the use of a bright (10 dB) fixed-intensity
stimulus prevents the Esterman from detecting all but the densest of scotomata. The
Esterman testing distance is approximately one-third of a metre, and many patients
and normal participants in our study encountered problems when attempting
binocular fusion of the fields of the right and left eyes.
Of the 56 patients who underwent the Esterman test, 33 passed and 23 failed the
current DVLA visual field criteria for driving. Seven of the 23 Esterman fails had a
UK licence. It is noteworthy, and a cause for some concern, that two of these seven
patients who failed the Esterman criteria and had a current UK licence were still
driving. Both these patients failed as a result of having an inadequate peripheral
visual field.
4.4.2 Integrated Visual Field test
The IVF test could be an alternative approach to the Esterman test for the
assessment of the central visual field. The IVF approach takes the data from each
eye of the ‘gold standard’ full-threshold central visual field tests carried out on the
HFA and combines these to produce a prediction of the central binocular visual
field. The IVF approach has the particular advantage over the Esterman test of
assessing more points within the functionally relevant central 208 of the visual
field (44), including 16 locations within the central 108 visual field, which is an
area largely untested on the Esterman test. For some groups of drivers, for example
those with diagnosed glaucoma or diabetic eye disease, full-threshold HFA fields are
already routinely measured, so no additional field testing would be required to
65
Central Scotomata and Driving
generate the IVF. However, the IVF is based on the central region of the visual field
(up to a maximum of 308) and gives no information on the integrity of the peripheral
visual field.
For each of our patients we analysed the agreement between the pass/fail decisions
on fitness to drive given by the Esterman test compared with the remaining battery
of tests. It should be noted that the Esterman visual field criteria currently used by
the DVLA at the time of writing this report (http://www.dvla.gov.uk/medical/
ataglance.aspx) comprise criteria for both central and peripheral fields. However,
pass/fail decisions for all the other tests in our battery are based on results obtained
solely from the central region of the visual field.
The kappa value for the Esterman/IVF agreement is 0.84, which is classified as
‘very good’. ‘Good’ agreement (kappa ¼ 0.69) has also been found between the
Esterman and IVF tests for primary open angle glaucoma subjects (Crabb et al.,
2004), and this level of agreement might be expected because the IVF approach is
based on merging monocular HFA data.
Fifty-four patients completed both the Esterman and IVF tests. Of particular interest
are three patients (6%) who passed the IVF but failed the Esterman test. All three
had cortical lesions with visual field loss that was peripheral but extended into the
central 208. In an earlier study on glaucoma patients (Crabb et al., 1998), there were
no participants who passed the IVF but failed the Esterman test. Glaucoma patients
tend, initially, to develop central binocular visual field loss, often followed
subsequently by peripheral field loss. This suggests that the IVF may misclassify
patients with predominantly peripheral loss, such as those with certain neurological
anomalies.
One patient passed the Esterman test but failed the IVF test (patient 31 – full details
presented in Section 3.2). The inability of the Esterman test to detect the field defect
probably resulted from the inadequate number of locations tested within the central
208 of field, and from the absence of fixation monitoring on the Esterman. The
IVF, with its superior sampling density, revealed the patient to have a significant
binocular defect in the inferior visual field.
Agreement between the Esterman and IVF tests was ‘very good’ (kappa ¼ 1) when
a small subset of 20 glaucoma patients was analysed separately. The very good
agreement in this small glaucoma sample supports the suggestion by Crabb et al.
(2004) that the IVF test could perform a valuable screening role in the assessment of
glaucoma patients’ fitness to drive. However, the IVF would need to be
supplemented by an Esterman test in non-glaucomatous patients who are more
likely to have significant field defects that primarily affect the peripheral field.
Assessment methods that differed depending on the pathology that presented would
not be practical, particularly given that dual pathology is not uncommon among real
patients.
66
4.4.2.1 Agreement between IVF and a binocular HFA test
In a separate study involving 40 of our patient group, we investigated the agreement
between the IVF and binocular visual fields collected using a monocular test on the
HFA (using the SITA testing strategy) carried out with the patient keeping both eyes
open and the fixation monitoring disabled. Concordance between the binocular test
and the IVF in the location and general shape of binocular visual field defects was
good, and this suggests that the IVF is a good predictor of significant defects in the
central binocular fields.
However, when individual locations in the field were analysed, the binocular testing
tended to overestimate the measured sensitivity values calculated by the IVF
(average of 1 dB), i.e. the binocular test tends to underestimate the severity of the
field defect. Pointwise agreement in sensitivity values in individual participants was
highly variable. It also varied with threshold level, with agreement poorest for
threshold values in the range of greatest interest – around 10 dB. Several reasons
may explain why the agreement was not similar to that reported previously by
Nelson-Quigg et al. (2000):
•
the participants in the current sub-study had mainly non-glaucomatous defects
(36 out of 40);
•
•
•
fixation was not monitored, quantified or controlled in the binocular test;
the type of testing (SITA testing used on non-glaucomatous patients); and
the difficulties of fusing the right and left fields.
4.4.3 The Useful Field of View test
The UFOV test is a computer-administered test of visual attention (essentially the
ability of an individual to take in visual information distributed across the visual
field). The UFOV is included in our battery of tests as it has been proposed as a
proxy measure of driving safety. In a retrospective study, there was a high
correlation with crash frequency over the preceding five years in the older
population (Ball et al., 1993). A prospective study (Owsley et al., 1998b) found that
a poor UFOV performance was associated with a two-fold increase in the relative
risk of crash involvement over the subsequent three years. Furthermore, a recent
cumulative meta analysis of eight studies (all of which used the original version of
the test) found that poorer UFOV test performance is associated with poor driving
performance in older adults (Clay et al., 2005).
In our study, based on the standard UFOV pass/fail criterion of 40%, there was
limited agreement between the UFOV and Esterman tests (65%, kappa ¼ 0.22), and
the UFOV and IVF tests (69%, kappa ¼ 0.23). In particular, a high proportion of
patients failed the visual field tests but passed the UFOV. Mean UFOV scores were
not significantly different between those who passed both the Esterman and IVF
67
Central Scotomata and Driving
tests and those who failed both. The UFOV test only identified 33% of patients who
would be considered unfit to drive based on the current UK visual field
requirements. It appears that for this group of patients, the UFOV is unable to
discriminate between those classified as fit to drive and those classified as unfit on
the basis of visual fields. This is at odds with the previous findings of Crabb et al.
(2004) in a group of glaucoma patients but may relate to our inclusion of patients
with a range of conditions causing paracentral visual field loss. Our use of the
original version of the UFOV test (Visual Attention Analyzer Model 2000, Visual
Resources, Inc., Chicago, USA) rather than the later PC version, which only
examines the central 118 and uses a less sophisticated scoring system, may also be
a factor (Edwards et al., 2005).
As part of this study we have calculated age-matched limits for 100 normal
observers on the UFOV test and established the normal range of UFOV scores for
each decade of life. Agreement between the UFOV and the Esterman and IVF tests
remains poor when the 90th percentile of the age-matched normal range is used as
the cut-off. A reduction in the useful field of view (increased UFOV score) with age
is well documented (Edwards et al., 2006; Sekuler et al., 2000) and confirmed by the
age-matched normal range determined as part of this study. Three normal
participants failed the UFOV with a loss of 40% or more. All were over the age of
70 years. It is possible that the majority of UFOV failures in the patient group are
also due to an age-related loss of attention rather than the presence of paracentral
scotomata. The youngest patient to fail the UFOV was 57 years of age, the next 60
years of age, and the remainder over 70. Some younger patients who passed the
UFOV fell outside the age-matched normal limits. Many of the UFOV failures were
older patients whose UFOV score lay within the age-matched limits. All this raises
the question of the validity of the widely used current cut-off criterion on the UFOV
test for this group of patients, which is currently set at a standard level independent
of the subject’s age. Although the original version of the UFOV test has been shown
to have a high sensitivity (89%) and specificity (81%) in predicting which older
drivers have a driving crash history (Ball et al., 1993), if the UFOV test were ever to
be adopted as the definitive ‘vision’ test for determining fitness to drive, a significant
proportion of older drivers exhibiting visual function within the age-matched normal
range would lose their licence, with profound social consequences.
A statistically significant improvement in UFOV scores was demonstrated over six
UFOV tests in nine normal participants, with the greatest learning effects noted in
the drivers with the poorest UFOV scores. This is consistent with the findings of
Richards et al. (2006), who noted a greater learning effect in older participants who
of course tended to exhibit higher initial UFOV scores. Learning effects have
implications for the methodological approach to the UFOV. There is a strong case
for taking the results from a patient’s first UFOV test, as this corresponds to a
driver’s ‘natural’ or ‘untrained’ visual attention capability.
68
The limited agreement between the UFOV and the visual field tests suggests that
either the current visual field criteria are too strict and relate poorly to driving safety,
or the UFOV test is relatively insensitive to visual field loss. Given that some
patients showed extensive paracentral visual field loss yet passed the UFOV test (see
Section 3.2.2, patient 55), it seems implausible that these particular individuals
would be safe driving a car. Therefore, we conclude that despite the limitations of
the conventional visual field tests, the insensitivity of the UFOV is the more likely
explanation for the poor agreement. There are a number of other factors that may
explain this poor agreement:
•
the original version of the UFOV test examines the central 308 whereas the
Esterman test sparsely samples the whole visual field excluding the central
7.58, and the IVF test considers only the central 208;
•
although the UFOV is designed to limit eye movements by requiring the subject
to identify both a central and peripheral target, compensatory eye movement
strategies in some patients cannot be completely ruled out; abd
•
in order to run the original 308 version of the UFOV test on a compatible
computer, the working distance was restricted to 20 cm.
Participants were corrected for this distance but some may have experienced
fusional problems which could have either helped or hindered their localisation of
the peripheral target.
The UFOV test was designed to reveal loss of divided and selective attention and not
loss of visual field but one might expect paracentral visual field loss to impair
localisation of paracentral UFOV targets. There has been surprisingly little
examination of the relationship between paracentral visual field loss and UFOV
performance. One small study reported UFOV errors in areas of reduced visual field
sensitivity in a small group of low vision patients (Leat and Lovie-Kitchin, 2006),
and another noted a reduction in the UFOV score associated with restricted
peripheral fields (Bowers et al., 2005), presumably due to associated visual function
deficits within the area assessed by the UFOV. A more detailed study by Owsley et
al. (2005) found that visual field sensitivity only accounted for 36% of the variance
in target localisation on the UFOV test and there were a number of participants who
exhibited good UFOV performance in areas of significant visual field loss. Rizzo
and Robin (1996) reported a bilateral reduction in UFOV performance in
participants with unilateral cortical lesions but rather than disproving a link between
field loss and UFOV performance, this probably reflects the impact of more global
cortical damage.
Dividing the patient group into those whose field loss was retinal in origin and those
whose field loss resulted from a neurological lesion, a similar proportion of patients
in each group failed the UFOV (7/21 retinal, 5/20 neurological). This suggests that
UFOV failure in this group of patients was caused by functional deficits associated
69
Central Scotomata and Driving
with the visual field loss rather than a neurological deficit affecting attention. The
UFOV test employs large high-contrast targets, greatly limiting sensitivity to visual
field loss. UFOV spoke errors were found to coincide with the area of lowest visual
field sensitivity in only around one-third of cases, consistent with the findings of
Owsley et al. (2005). The uneven distribution of peripheral test targets between
radial spokes within a single UFOV run reduces the chances of agreement and the
total UFOV score is therefore unlikely to reflect the extent of the visual field loss
until it reaches a critical level in terms of both extent and depth.
Despite the high proportion of patients whose UFOV score fell within the agematched normal range (85%), statistical analysis indicates that the mean total UFOV
score was significantly higher in the patient group than the normal group. However,
the difference between the two groups barely reached clinical significance because
the variability of the UFOV test, expressed by the repeatability standard deviation,
was found to be 5.5% compared with a difference between the mean UFOV scores
of groups of 6.6%. If this group difference is a real effect, it might reflect the high
UFOV scores of a minority of patients with dense paracentral visual field loss
extensive enough to impact UFOV performance. A more likely explanation is that
the slightly higher UFOV score in the patient group relates to the profound visual
loss across wide areas of the paracentral field for other stimulus attributes,
specifically contrast acuity (see Section 3.1.9). Agreement was poor between the
AVA tests (Contrast Threshold, Contrast Acuity, Motion and Colour) and the UFOV
since the majority of patients passed the UFOV but fell outside the 90th percentile of
the normal range for each of the AVA tests (fail). The limited agreement between
the UFOV score and motion perception is consistent with the findings of Raghuram
and Lakshminarayanan (2006). Reduction in the perceived contrast of the UFOV
targets, regardless of whether this occurs at a retinal or higher processing level,
would be expected to increase the paracentral crowding effect that is intrinsic in the
UFOV test. Crowding has been found to reduce the variance in target localisation
accounted for by conventional visual field loss from 36% (subtest 2) to 13%
(subtest 3) (Owsley et al., 2005). If we were able to modify the UFOV test to
examine a range of different contrast targets in controls, we hypothesise that they
would behave like patients. It is not possible, however, for the UFOV to discriminate
between a poor performance caused either by the effects of crowding or by an
attentional deficit.
The UFOV test is expensive, with current models ideally requiring a special touch
screen. Furthermore, the new version employs only one eccentricity at
approximately 118 and has not yet been shown to relate to crash risk, unlike the
original version with three eccentricities. Outcomes may be affected by the method
in which the test is administered and the UFOV model used. The UFOV has been
described as ‘impractical for widespread use’ (Wood, 2002).
70
4.4.4 The Hazard Perception Test
The HPT examines the ability to detect hazards in a series of videos of moving road
scenes. Twenty-six film clips were made available to the research team from a series
known to predict driver safety (Grayson and Sexton, 2002), therefore the test was
included in this study as a proxy measure of driving safety.
The videos covered a range of environments (dual carriageway, rural lane, busy
urban road, etc.) and each contained between one and three hazardous driving
events. The camera-car took the appropriate evasive action when reaching the
hazard. HPT hazards cannot be mapped onto the location of a subject’s visual field
defect.
Unlike the HPT score calculated by the Driving Standards Agency (DSA), we
judged HPT performance in terms of the percentage of hazards missed (% missed)
and also the mean hazard response time (RT). This allowed us to study the
variability and value of each parameter. The DSA pass/fail criteria for learner
drivers was in flux during the period of data collection and so an established cut-off
value was not available. Neither HPT performance measure demonstrated a
significant relationship with age, therefore we selected the 90th percentile of the
normal range as the pass/fail boundary for each. The proportion of the patient group
who fell within this range was 81.3% and 75.0% for % missed and RT respectively.
In our study, agreement between the visual field tests and % missed (HPT) was
limited, and this parameter only identified 29% of patients who would be considered
unfit to drive based on the current UK visual field requirements. There was no
statistically significant difference between the % missed by the patient group and the
normal group. Whether or not an individual responded to a hazard was found to be
affected by the participants’ personality make-up. A key factor in a subject’s
performance on the HPT is how each subject is instructed as to what constitutes a
hazard and how each subject interprets these instructions. It is not reassuring to note
that in our study, although each subject received identical instructions prior to the
test, the average normal subject ‘missed’ 16% of the hazards. We attribute this
figure to participants deciding that some hazards did not represent hazards, rather
than the hazards being not seen by the participants. The hazards are large, loom for
extended periods, and do not represent the more visually-difficult scenarios that are
most likely to lead to accidents in the real driving environment. Scoring the HPT on
the basis of the percentage of hazards missed is unlikely, therefore, to be an accurate
indicator of participants’ driving performance under the conditions in which they are
most likely to have an accident.
Agreement between the visual field tests and RT (HPT) was classed as fair but RT
was still only able to identify 39% of patients who would be considered unfit to
drive based on the current UK visual field requirements. Despite the fact that 75%
of patients showed a mean hazard response time within the normal range, the patient
71
Central Scotomata and Driving
group demonstrated a significantly longer hazard response time than the normal
group. The length of saccadic eye movements (in degrees) and the horizontal
variance of these movements were also greater for the patient group, although
fixation duration did not differ. This analysis of eye movements suggests that some
patients compensate for their paracentral visual field loss by increasing their
scanning of the visual scene to improve their chance of detecting hazards. Modified
scanning strategies may also explain the small but significant increase in hazard
response time for the patient group, since some scans will move fixation further
away from an impending hazard, therefore increasing time to detection. Whether
such scanning strategies improve or degrade driving safety depends very much on
the characteristics of the hazard and the particular circumstances.
These findings suggest that paracentral visual field loss may affect the ability to
detect hazards on the road in an effective and timely fashion. The poor agreement is
likely to relate to the unchallenging nature of the HPT test in its current form and
perhaps our choice of pass/fail cut-off point (90th percentile of the normal range).
Extensive visual loss for other stimulus attributes (contrast acuity, motion, etc.)
rather than conventional visual field loss (high-contrast detection task) might impair
HPT performance. The degree of impairment revealed by the AVA tests is rarely
reflected by the extent of paracentral visual field loss. Differentiating between those
patients who have developed an efficient and effective scanning strategy who may
therefore be safe to drive, and those who have not, is likely to require a more
demanding test.
4.4.5 The AVA tests
The psychophysical AVA tests provide further evidence of the limitations of the
Esterman test which can only provide a limited measure of vision loss. Selective
vision loss (contrast detection, contrast acuity, motion, colour) was identified in the
majority of patients in areas of the visual field deemed normal or near normal,
according to conventional perimetric tests. It emerged from the AVA tests that
contrast detection and motion perception were the least affected stimulus attributes
in our patient group. Contrast acuity and the ability to detect colour tended to be the
most affected stimulus attributes. These results highlight the fact that selective
vision loss can occur in the absence of a visual field defect but the reverse is rarely
the case. Therefore, none of the AVA tests compared well with the Esterman or IVF
tests when pass/fail agreement was examined from 2 3 2 frequency tables.
Noteworthy are the very high sensitivities and very low specificities for the Contrast
Threshold, Contrast Acuity and Colour tests, with many participants failing these
tests despite passing the Esterman test. Agreement was also poor between three of
the AVA tests (Contrast Threshold, Contrast Acuity and Colour) and both the UFOV
and HPT tests, with very low sensitivities but good specificities. These outcomes are
consistent with pass/fail cut-offs that are too severe. Interestingly, the Motion test
showed agreement with the UFOV that was comparable with the Esterman and IVF,
and with higher sensitivity. Also, the Motion test showed better agreement with the
HPT (for both %missed and hazard response time) than the other AVA tests, with
72
sensitivities greater, though specificities lower, than achieved with the Esterman and
IVF tests.
There is evidence to show that selective loss of any of these four specific visual
functions impacts on driving performance. Contrast sensitivity is known to be a
moderate predictor of driving performance (Bowers et al., 2005; Evans and
Ginsburg, 1985; Coeckelbergh et al., 2004; Ginsburg et al., 1985; Owsley and
McGwin, 1999; Wood et al., 1993; Wood and Troutbeck, 1994; Wood and
Troutbeck, 1995; Worringham et al., 2006) and has a greater association with crash
risk than either visual acuity (Owsley et al., 2001; Wood and Owens, 2005) or
central visual field sensitivity (Owsley et al., 1998a). An association between
reduced contrast sensitivity and modified driving behaviour has been demonstrated
in the form of slower driving speeds (Szlyk et al., 2002) and night-driving cessation
(Brabyn et al., 2005). Not surprisingly given the dynamic nature of the driving task,
impaired motion perception limits driving performance (Shinar, 1977). The
importance of good colour discrimination for safe driving is less well established but
colour information is certainly not redundant (Vingrys and Cole, 1988). Protanopes
have more rear-end collisions than colour normals (Cole and Maddocks, 1997;
Verriest et al., 1980), and the misidentification of rear signal lights at night has been
reported in colour defective drivers (Tagarelli et al., 2004).
The level at which a deficit in one or more of these specific visual functions has
some bearing on fitness to drive is poorly understood. As a result, the pass/fail
criteria we used for the AVA tests were established on the basis of the 90th percentile
normal limits of performance derived from our small age-matched normal groups.
These criteria are likely to be overly stringent and need revision based on larger
numbers of visually-normal volunteers within each age group, and through the
determination, for each test, of the level of visual performance required for safe
driving. The normal database has already been extended, independently of the
current study, to begin to address this issue. These results show that when visual
losses involve the central 208 of the visual field, the corresponding loss in visual
performance can be profound. Assuming that a key function of this paracentral
region of the visual field is to detect novel events that can be used to trigger eye/
head movements, these losses in visual performance leave a level of residual vision
that could have a significant impact on driving safety.
4.5
Which test should be the gold standard?
The preceding discussion has assumed that the Esterman test is the gold standard
test for visual fields for driving. This is not unreasonable as a starting point, given
that the Esterman test is the current basis for UK Group 1 licensing decisions. But it
is possible that this reliance on the Esterman test is ill-founded, and that either the
UFOV or the HPT would be an improved gold standard. Therefore, all our pass/fail
driving data for each test (including all the AVA tests) have been reanalysed, with
first the UFOV test and then HPT taken as gold standard.
73
Central Scotomata and Driving
4.5.1 Esterman as the gold standard
When the Esterman is the gold standard, a key feature of the pass/fail outcomes for
both the UFOV and HPT tests is the number of patients who pass the proxy measure
tests but fail the Esterman test. The sensitivities of the proxy measures (the number
of patients who passed the proxy measures but failed the Esterman test) are 33% for
UFOV, 22% for HPT %missed, and 39% for HPT RT. The specificities of the proxy
measures are high (87% for UFOV, and 86% and 82% for %missed HPT and RT
HPT, respectively), indicating that the proxy measures pass the majority of patients
who pass the Esterman test. This combination of low sensitivity and high specificity
is consistent with the proxy measures passing too many patients who should not be
driving. However, it is also consistent with the conclusion that the Esterman test is
an inadequate gold standard which fails too many patients who are fit to drive.
Analysis of the detailed results from these participants does not support this second
argument, with most of these participants having Esterman and other visual field test
results which should preclude driving (e.g. patients 55 and 17, with full details
presented in Section 3.2), although there is the possibility that some of these
individuals have developed compensatory eye movement strategies and may, in fact,
be safe to drive. Irrespective of the concerns about the pass/fail cut-off for the
Esterman test, the limited number of stimulus locations within the driver’s
functional visual field is worrying.
4.5.2 UFOV as the gold standard
When the data are re-analysed with the UFOV as the gold standard, the Esterman
gives a sensitivity of 65% and a specificity of 66%. The specificity value is not
surprising given the relative ease with which the participants pass the UFOV
compared with the Esterman, but it is interesting that the sensitivity is so low. Of the
11 patients who fail the UFOV, four pass the Esterman. Analysis of the detailed
results of these participants supports the view that they have Esterman and other
visual fields test results which should permit driving (e.g. Patient 90 –full details
presented in Section 3.2). It appears that for the group of patients in this study, the
UFOV is unable to discriminate between those classified as fit to drive and those
classified unfit on the basis of visual fields.
The greatest predictor of UFOV failure in our patient (and normal) group appears to
be age. Many of the UFOV failures were older patients whose UFOV score actually
lay within the age-matched limits. If the UFOV test were ever to be adopted as the
definitive ‘vision’ test for determining fitness to drive, a significant proportion of
older drivers exhibiting visual function within the age-matched normal range would
lose their licence, with profound social consequences. The UFOV also suffers from
significant learning effects, limiting its use as a potential gold standard. The fact that
the patient group on average showed a small but significant increase in mean UFOV
score compared with the normal group suggests that aspects of the UFOV, for
example the paracentral crowding/divided attention used in subtest 3, may be a
useful element to incorporate in to a future, composite test.
74
4.5.3 HPT as the gold standard
When the data are re-analysed with the HPT as the gold standard, the Esterman
gives sensitivities of 50% and 58% and specificities of 63% and 67% when
compared with HPT % missed and HPT RT respectively. The specificities reflect the
relative ease with which the participants passed the HPT compared with the
Esterman, but as for the UFOV/Esterman, the sensitivities are low. Of the eight
patients who fail the HPT for %missed, four pass the Esterman, and of the 12
participants who fail the HPT for hazard response time, five pass the Esterman.
Analysis of the detailed results of these participants supports the view that they have
Esterman and other visual fields test results which would be expected to permit
driving (e.g. patient 103 – full details presented in Section 3.2).
Although the mean hazard response time was significantly longer for the patient
group than the normal group, there is little evidence from our study to support the
HPT test in its current form as a replacement gold standard. The hazards are large,
loom for extended periods, and do not represent the more visually difficult scenarios
that are most likely to lead to accidents in the real driving environment. There is
also a wide variation in the interpretation of what constitutes a hazard. Scoring the
HPT on the basis of the percentage of hazards missed is unlikely, therefore, to be an
accurate indicator of participants’ driving performance under the conditions in
which they are most likely to have an accident. Hazard response time with the 90th
percentile pass/fail cut-off is also an unreliable indicator of visual field outcome and
its relationship with driving safety has yet to be established. The HPT does have the
advantage of being a test that participants can easily relate to the driving task but
incorporating the assessment of eye movements in to the HPT test would be
impractical for wide-spread use.
4.6
Index of Good Vision
The experience gained from this work suggests that it is possible to generate an
Index of Good Vision (IOGV) which would be a useful measure to quantify an
individual’s quality of vision for driving. Based on the results of the current study,
the aspects of visual performance that should contribute to the index would be:
•
•
•
•
•
central and peripheral visual fields;
contrast detection;
contrast acuity;
motion detection; and
colour vision.
The IOGV would take into account the patient’s age, and could be a valuable tool in
the licensing decision-making process, particularly for those drivers who have failed
the base-line visual field test for driving (currently the Esterman test). A detailed
75
Central Scotomata and Driving
visual task analysis would be needed to determine the contribution of each element
to the IOGV.
4.7
Compensatory head and eye movements
It is known that some patients with visual field defects adapt to their deficits when
driving through the adoption of compensatory head and eye movements. Evidence
has been provided by individuals with visual field loss of congenital origin who have
been driving for years unaware of their defect. Modified scanning behaviour may
improve their driving safety and accident records.
In this study, fixation was monitored during the IVF (monocular merged fields) and
APP visual field tests but the binocular Esterman test does not provide for fixation
monitoring. It is not possible to control for compensatory eye movements on the
UFOV, although saccades to view peripheral targets can lead to incorrect
identification of the central car/lorry and exclusion of that trial from the overall
result. Participants are allowed free eye movements on the HPT, although head
movements were restricted to permit accurate eye movement recording. In this
study, agreement between the HPT and visual field tests was limited but there was
evidence to suggest that, on average, the patient group showed modified scanning
behaviour compared with the normal group. The patient group exhibited greater
scanning of the visual scene, as indicated by a larger horizontal variance and longer
saccadic eye movements (measured in degrees). Fixation duration did not differ
from that of the normal group. Modified scanning strategies may explain the small
but significant increase in hazard response time for the patient group compared with
the normal group. Increased scanning of the visual scene may improve an
individual’s chance of detecting a hazard but is also likely to lead to an increase in
mean time to detection. Whether such scanning strategies improve or degrade
driving safety depends very much on the characteristics of the hazard and the
particular visual context.
Given the relatively small difference between the patient and normal groups for
hazard response time and eye movements, it is unlikely that many of the patients in
this study have adopted these strategies, particularly since so many showed complex
central field loss that would be difficult to overcome by modifying eye movements.
Examination of the eye movements of individual patients during the HPT suggests
rather erratic scan patterns in some, with little in common between patients with
similar visual field loss. We do not believe that the large number of HPT passes
among patients failing the Esterman test can be attributed to compensatory eye
movements. Nevertheless, adaptation to visual field defects is a most important
aspect to consider when ruling on driving fitness, and should be investigated further.
76
5
RECOMMENDATIONS
Our results indicate that interpretation of visual field plots alone is an inadequate
method of assessing drivers’ vision. However, in the short-term, visual fields are
likely to remain the arbiter for screening purposes. Therefore, we recommend that in
future a more complete visual assessment should be employed for borderline cases
(see Section 5.2 below).
5.1
Current practice
Although it is desirable that the perimetric test used for licensing requirements
should be carried out binocularly, there is a major problem for many patients
regarding binocular fusion of the fields of the right and left eyes at the usual testing
distances of around 33 cm:
5.2
•
For the standard screening of drivers we would currently recommend a modified
Esterman test be developed with many more central locations tested. However,
the remaining limitations of this test must be accepted, including fusion
difficulties and the inability to monitor fixation. These factors reduce reliability
and repeatability.
•
For patients with known visual field defects, the IVF, which is based on
monocular data, could be used but it must still be supported by the Esterman
performance for the peripheral field.
•
As an alternative to the IVF, a central field test, such as the Advanced Perimetry
Program (APP – see Table 2.2), could be used, again supported by the Esterman
test. The 70 cm working distance of the APP is sufficiently large to overcome
the fusion problem, and fixation monitoring can be incorporated. However, any
visual field test with a working distance greater than 33 cm would not be
compatible with the HFA hardware – one of the most widely available visual
field machines in the UK.
Developments for the future
A new composite test that incorporates suitable material to indicate the levels of
visual performance, distributed attention and motor responses within an interactive
driving environment could be developed. Such a test is likely to produce scores that
correlate more closely with driving performance. Of particular value in any new test
or tests would be the assessment of visual performance under conditions of free eye
movements.
Absolutely fundamental to the development of any new tests is a wide-ranging
Visual Task Analysis (VTA) focused on the visual challenges faced by the normal
driver, such as has been previously undertaken for commercial aviation (Chisholm
77
Central Scotomata and Driving
et al., 2003). This analysis should consider a wide range of driving conditions and
would allow the identification of difficult visual environments, driving conditions
and hazards that would be incorporated into any subsequent test. Crucial to this
VTA would be the input from particular groups of drivers, for instance police
drivers, driving instructors, etc.
An important group of patients to study are those who already have longstanding
defects, including congenital defects. Information would be obtained on the degree
to which different patients develop strategies to cope with their visual field defect.
To inform this investigation it would also be useful to monitor patients soon after
they acquire a visual field defect and then at intervals subsequently to identify the
strategies employed to compensate for their defects, to assess the time course for
learning to compensate, and to chart the range of improvement in performance
across the patient group.
It is of crucial importance that any new test or test battery is acceptable to patients
and has face-value as a test that is clearly related directly to the driving task.
78
6
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