Europace (2015) 17, ii97–ii104
doi:10.1093/europace/euv244
SUPPLEMENT: CLINICAL RESEARCH
Effect of the electrograms density in detecting and
ablating the tip of the rotor during chronic atrial
fibrillation: an in silico study
Juan P. Ugarte 1*, Catalina Tobón 1,2, Andrés Orozco-Duque 1,2, Miguel A. Becerra3,
and John Bustamante 1
1
Centro de Bioingenierı́a, Universidad Pontificia Bolivariana, Medellı́n, Colombia; 2GI2B, Instituto Tecnológico Metropolitano, Medellı́n, Colombia; and 3GEA, Institución Universitaria
Salazar y Herrera, Medellı́n, Colombia
Received 28 February 2015; accepted after revision 17 June 2015
Aims
Identification in situ of arrhythmogenic mechanisms could improve the rate of ablation success in atrial fibrillation (AF).
Our research group reported that rotors could be located through dynamic approximate entropy (DApEn) maps.
However, it is unknown how much the spatial resolution of catheter electrodes could affect substrates localization.
The present work looked for assessing the electrograms (EGMs) spatial resolution needed to locate the rotor tip using
DApEn maps.
.....................................................................................................................................................................................
Methods
A stable rotor in a two-dimensional computational model of human atrial tissue was simulated using the Courtemanche
and results
electrophysiological model and implementing chronic AF features. The spatial resolution is 0.4 mm (150 × 150 EGM).
Six different lower resolution arrays were obtained from the initial mesh. For each array, DApEn maps were constructed using the inverse distance weighting (IDW) algorithm. Three simple ablation patterns were applied. The full
DApEn map detected the rotor tip and was able to follow the small meander of the tip through the shape of the area
containing the tip. Inverse distance weighting was able to reconstruct DApEn maps after applying different spatial resolutions. These results show that spatial resolutions from 0.4 to 4 mm accurately detect the rotor tip position. An
ablation line terminates the rotor only if it crosses the tip and ends at a tissue boundary.
.....................................................................................................................................................................................
Conclusion
A previous work has shown that DApEn maps successfully detected simulated rotor tips using a high spatial resolution.
In this work, it was evinced that DApEn maps could be applied using a spatial resolution similar to that available in commercial catheters, by adding an interpolation stage. This is the first step to translate this tool into medical practice with a
view to the detection of ablation targets.
----------------------------------------------------------------------------------------------------------------------------------------------------------Keywords
Atrial fibrillation † Computer model † Dynamic approximate entropy map † Ablation † Rotor tip
Introduction
Ablation has emerged as an important therapeutic strategy to treat
atrial fibrillation (AF).1 Pulmonary veins isolation, as a single or repeated procedure, reaches success rates for paroxysmal AF treatment up to 76%.2 However, for the chronic case, this strategy
does not achieve satisfactoryoutcomes,3 consequently complexes
ablation lines are added to theprocedure.1 To improve the effectiveness of these additional lines, the logical approach is to relate them
with substrates that sustain the arrhythmia.
The rotor theory establishes that, an AF episode is perpetuated
by a stable re-entrant circuit, rotating around an unexcited core.4
Several studies have observed rotors in cellular and animal models,5 and its presence in humans was recently reported.6 Furthermore, the ablation of the core has resulted in the restoration of
sinus rhythm. 7 However, the observation of a rotor, through
monitoring the action potential propagation, requires several cycles of recording, rotor spatial stability, and a large quantity of electrodes. Other signal processing tools for detecting rotors are
being developed, e.g. phase singularity tracking; but the technical
* Corresponding author. E-mail address: [email protected]
Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2015. For permissions please email: [email protected].
ii98
What’s new?
† Dynamic approximate entropy maps can effectively locate
the tip of rotor, using a feasible spatial resolution.
† The design of ablation lines based on information provided
by dynamic approximate entropy maps could successfully
terminate the rotors.
† The area marked as rotor tip position by the dynamic
approximate entropy map, describes the meandering of the
rotor tip through the shape of its perimeter.
requirements they demand, such as high spatial resolution,8 are not
currently available. Although the technological developments,
looking for increasing the spatial resolution, are on move; tools
for arrhythmogenic substrate detection—such as rotors—should
be pursued and have the capability of adapting to current
technology.
This work aims to establish a feasible spatial resolution of electrodes array for rotor tip detection by means of dynamic approximate
entropy (DApEn) maps. Dynamic approximate entropy allowed designing simple and effective ablation patterns. Moreover, a relationship between the DApEn map and the motion of the tip was
inferred. Phase diagrams were used as gold standard method to detect and track the tip of the rotor.
Methods
Six different spatial resolutions were applied to the model and DApEn
maps rotor detection capability using these arrays was assessed. The
methodology is summarized as follows: a two-dimensional (2D) AF
computational model was implemented, high-density electrograms
(EGMs) signals were calculated, and DApEn and phase maps were generated. New spatial resolutions were obtained by reducing the number
of EGM from the full array. Motion of the EGM array was considered.
Dynamic approximate entropy maps were reconstructed for each spatial resolution. Using DApEn map information, ablation lines were applied. The following sections detail the materials and methods used in
this work.
Electrophysiological and two-dimensional
models
The Courtemanche – Ramirez – Nattel – Kneller 9,10 membrane formalism was implemented to simulate the electrical activity of human
atrial cell. Based on the experimental data,11 the cellular model was
modified in order to reproduce electrophysiological conditions of
chronic AF (cAF): the maximum conductance of potassium time independent current (IK1) was increased by 100%, the maximum conductance of transient potassium current (I to ) and delayed rectifier
potassium current (IKur) were decreased by 50%, and the maximum
conductance of L-type calcium current (ICaL) was decreased by 70%
(see Table 1). Thus, the action potential duration was reduced by
70% (Figure 1A).
A 2D human atrial tissue model was generated. The tissue surface was
discretized into a 150 × 150 hexahedral mesh (22 500 elements and
45 602 nodes). Spatial resolution is 0.4 mm. The electrophysiological
model was integrated into the 2D virtual model.
J.P. Ugarte et al.
Propagation and stimulation protocol
The electrical propagation of action potential in the tissue was modelled
using the monodomain reaction – diffusion equation:
1
∂Vm
∇ · (D∇Vm ) = Cm
+ Iion − Istim ,
Sv
∂t
(1)
where Sv corresponds to the surface-to-volume ratio, D is the conductivity tensor, Cm is the specific membrane capacitance (50 pF), Iion is the
total ionic current that crosses the membrane cells, Vm is the membrane
potential, and Istim is the stimulus current. The tissue was considered isotropic. A conductivity of 0.3 S/cm was assigned in order to obtain a conduction velocity of 60 cm/s. Equation (1) was solved using the finite
elementmethod.12
Chronic AF episode was generated by applying S1 – S2 cross-field
stimulation protocol. Stimuli pulses were rectangular with 2 ms of duration and 6 mA of amplitude. The S1 stimulus was plane and was applied
at the left boundary of the model (Figure 1B). The S2 stimulus was rectangular (2 × 3 cm) and was applied 40 ms after S1 in a corner of the
model (Figure 1C).
Electrograms and approximate entropy
Unipolar EGMs were calculated at a distance of 0.2 mm above the atrial
surface, with temporal resolution of 1 ms, by computing the extracellular potential ( fe) in an approximate large volume conductor13 as:
fe (r) = −
1 si
4p se
∇′ Vm (r ′ ) · ∇′
r′
1
dv,
−r
(2)
where ∇ ′ Vm is the spatial gradient of transmembrane potential Vm, si is
the intracellular conductivity, se is the extracellular conductivity, r is the
distance from the source point (x, y, z) to the measuring point (x ′ , y ′ , z ′ ),
and dv is the volume differential. A total of 22 500 virtual electrodes
(VEs) (150 × 150), spaced by 0.4 mm, were used to calculate the
EGM signals (one for each element of the model).
Fractionation was assessed through the EGM irregularity. Approximate entropy was calculated from EGM, in order to quantify the degree
of complexity of the signals. Approximate entropy is a non-linear statistic proposed by Pincus14 and is defined as:
ApEn(m, r, N) = øm (r) + øm+1 (r),
øm (r) =
N−m+1
1
log (Cim (r)).
N − m + 1 i=1
(3)
(4)
Calculation of ApEn(m, r, N) depends on three parameters: number
of data points N, embedding dimension m, and threshold r. ApEn(m, r, N)
allows measuring regularity by calculating the probability, Cim, that patterns of length m remain close on next incremental comparisons within
a signal of length N, with m , N. Approximate entropy is theoretically
Table 1 Conductance (g) changes of currents for cAF
Conductance
cAF [relative to (Courtemanche)]
gK1
Increased by 100%
gKur
gto
Decreased by 50%
Decreased by 50%
gCaL
Decreased by 70%
................................................................................
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Effect of the electrograms density
A
B
10
Physiological
cAF
C
mV
5
45 ms
90 ms
–10
mV
–16
–30
–38
–50
–70
–90
S1
–59
0
50
100 150 200 250 300
t (ms)
S2
–80
Figure 1 (A) Action potential under physiological and cAF conditions. (B, C) S1– S2 cross-field protocol. The plane S1 and rectangular S2 stimulus are shown.
defined as the value dependent on m and r, considering N 1. Pincus
stated that for N ¼ 1000, small values of m are needed in order to converge to the real value of ApEn.15
used to estimate unknown data point values, based on the assumption
that this will be the weighted average of his neighbour values. Inverse
distance weighting assumes that the closest neighbour values have the
largest weight.18 Thus, the weights calculation is defined by the equation:
Phase diagram and rotor tip tracking
Phase diagram was generated as reported in Ref. 16. Briefly, unipolar
EGMs were filtered by a 40 – 250 Hz bandpass, rectified and filtered
by a 20 Hz lowpass. The mean of the resulting signal was set to zero
by subtracting its average. Hilbert transform was applied and the phase
was calculated using the four-quadrant inverse tangent (atan2) function
of MatLabw between the imaginary part of the Hilbert transform and
the post-processed signal. The rotor tip was located where all phases
between −p and p converged.
a
d−
ij
Wij = nj ,
k dkj
where the index i represents the points which values are known and j
represents the points with unknown values, nj is the number of points
a
with unknown values related to the point j, and d−
is the distance beij
j value at the point j was calcutween points i and j.19 The interpolated R
lated using the following equation:
Dynamic approximate entropy maps
Values of 3 and 0.38 for m and r ApEn parameters, respectively, were
used. These values were obtained by an optimization method previouslydescribed.17 Approximate entropy was calculated from EGM, with 4 s
in length, using a moving window of 1000 ms, without overlapping. Maps
were built applying the range of ApEn values to a colour scale, where
the red colour corresponds to the maximum ApEn value and blue corresponds to the minimum value. These maps were named as DApEn
maps. The tip was detected by the highest ApEn value. The error of
tip localization (eTL) was calculated as the Euclidian distance between
the tip defined by DApEn map and phase singularity position obtained
from phase maps.
Reduction and interpolation stages
The reduction stage depends on initially defining a new spatial resolution
d (in mm). A VE is fixed; and the N 2 1 consecutive VEs in horizontal
direction are removed, where N ¼ d/0.4. This action is contiguously recurrent until the matrix boundary is reached. For each defined VE in the
previous process, the action is repeated in the vertical direction. Electrograms are calculated at every fixed VEs. Each displacement of the first
VE defines a new variation. Shifting the first VE, initially located at a
corner, generates N 2 different variations for a given value of d. In this
manner, the position variability of an electrodes array is included.
For the six reduced designs and all their variations, the reconstruction
of DApEn maps was performed using the inverse distance weighting
(IDW) algorithm. Inverse distance weighting is an interpolation method
(5)
j =
R
nj
wij Rij ,
(6)
i=1
where Rij is the value of the known point i.
Numerical and computational methods
The hexahedral mesh was built using Femap from Siemens PLM software. Equations were numerically solved using EMOS software.12
EMOS is a parallel code (mpi based) that implements the finite element
method and operator splitting for solving the monodomain model. The
time step was fixed to 0.001 ms.
Ablation patterns
Three different linear ablation patterns were designed. They are composed by two elements of thickness; to which null conductivity was assigned in order to convert these elements into conduction block lines.
To evaluate the patterns effectiveness to terminate rotors, each pattern
was applied into the 2D model after 4 s of the rotor activity.
Results
Atrial fibrillation simulation, phase map,
and dynamic approximate entropy map
A 4-s stable clockwise rotor was generated in the 2D model after
applying the S1–S2 protocol (Figure 2A and Supplementary material
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J.P. Ugarte et al.
Figure 2 (A) Stable rotor. (B) Phase diagram, singularity marked by black circle. (C) Motion of the singularity in the phase diagram within the first
second of simulation. (D) Dynamic approximate entropy map. (E) Dynamic approximate entropy map + phase diagram. The high ApEn area encloses singularity. Thus, DApEn detects the rotor tip. High ApEn perimeter matches with locus depicted in (C). Dynamic approximate entropy map
is able to provide information about the meandering of the tip. (F) Top: fractionated EGM sample from the core of the rotor. Bottom: regular EGM
calculated in * from (A).
Table 2 Reduction process characteristics
d (mm) (spatial resolution)
N 2 1 (VE within one removed segment)
N 2 (number of variations)
Number of EGM
%Reduction
...............................................................................................................................................................................
0.4
0
1
22500
0.00
0.8
1
4
5625
75.00
2.4
4.0
5
9
36
100
625
225
97.20
99.00
5.2
12
169
144
99.36
6.0
7.2
14
17
225
324
100
81
99.56
99.64
online, Video S1). Electrograms were calculated over the whole surface of the 2D model. Phase diagram is shown in Figure 2B (see Supplementary material online, Video S2). Black circle marks the
singularity. The locus of the phase singularity motion is shown in
Figure 2C (see Supplementary material online, Video S3).
Figure 2D shows the DApEn map from full EGM array (see Supplementary material online, Video S4). High ApEn values, in red, are
found in the location of the rotor tip. This can be verified in
Figure 2E: red zone from DApEn map coincides with the singularity
in the phase diagram. A 98.9% of EGM present simple morphology;
with ApEn values ,0.1 (0.093 + 0.011) (Figure 2F, bottom). The remaining 1.1% of EGM, located at the rotor tip, exhibit potentials
composed by two or more deflections and ApEn values .0.12
(0.1312 + 0.080) (Figure 2F, top).
In the vicinity of the rotor core: the ApEn increases to maximal values (.0.12) as it approaches to the tip, and it decreases when
ii101
Effect of the electrograms density
reaching the tip (0.1220 + 0.0042). This behaviour depicts a shape,
which matches with the locus of the singularity tracking (Figure 2C, D).
Reduction and reconstruction of dynamic
approximate entropy maps
Six d values were used: 0.8 mm (75% reduction), 2.4 mm (97.22%
reduction), 4 mm (99% reduction), 5.2 mm (99.36% reduction),
6 mm (99.56% reduction), and 7.2 mm (99.64% reduction). Each
spatial resolution generates multiple variations as described in the
‘Methods’ section. Table 2 summarizes the characteristics of each
design.
Table 3 summarizes the median (M ), interquartile range (IQR),
and range (R) for the eTL calculated for each spatial resolution.
Data are presented for each 1000 ms interval. For d values
≥5.2 mm, M and 75th percentile values tend to increase. Also,
R-values exceed the respective spatial resolution at least by a factor
of 4. Figure 3 shows representative reconstructed DApEn maps for
spatial resolutions of 0.8, 2.4, 4.0, and 5.2 mm.
Ablation
The patterns applied are described as follows: Pattern 1, a line that
does not pass through the rotor tip and ends at the tissue boundary
(1 in Figure 4A). Pattern 2, a line passing through the rotor tip and
ending before touching the tissue boundary (2 in Figure 4A). Pattern
3, a line passing through the rotor tip and ending at the tissue boundary (3 in Figure 4A).
The ablation pattern #1 was not effective in terminating the AF
activity; the rotor continued turning around the ablation line, which
behaves as an anatomical barrier to the rotor (Figure 4B). The ablation pattern #2 was not effective in terminating the AF; the rotor
became a figure-of-eight-re-entry, because the ablation line fragmented the spiral wave, generating a new rotor turning in the
opposite direction (Figure 4C). Ablation pattern #3, composed by
a line through the rotor tip and ending at the tissue boundary,
was effective in terminating the AF activity and the rotor stopped
at 200 ms (Figure 4D). The ablation line eliminates the singular point
through which the rotor is maintained, and the boundary prevents
re-entry of the propagation wave.
Discussion
The principal findings are summarized as follows:
† Dynamic approximate entropy map, obtained from high spatial
resolution EGM array, encloses the rotor tip within an area
whose contour describes the meandering of the tip.
† Rotor tip detection is possible through DApEn maps, using a feasible spatial resolution of electrodes array in a 2D atrial tissue
model under AF conditions.
† A line of ablation starting at the rotor tip and ending at a tissue
boundary terminates the rotor.
Chronic AF ablation procedures require a large number of ablation
lines in order to effectively terminate the AF episode. Electrogramguided ablation has led to the development of new tools for
detecting arrhythmogenic substrates. Complex fractionated atrial
electrograms (CFAEs) were shown to be located in rotor tip
areas,20 but the CFAE mapping is still a debatable technique.21 Complex fractionated atrial electrogram characterization algorithms are
being questioned due to the fact that they are focused on cycle
length and not on the signalmorphology.1,22 Our previous work assessed fractionation by grading it on irregularity levels, through
ApEn, and it looks for relating these levels with arrhythmogenic substrates. High ApEn values are related with high fractionated EGM
signals contained in the vicinity of the rotor tip, but at the same
Table 3 Median, IQR, and range of error of tip localization corresponding to six spatial resolutions. All values are in mm
Time interval (ms)
Spatial resolution, d (mm)
.........................................................................................................................................
0.8
2.4
4.0
5.2
6.0
7.2
1.91
1.65
2.00
2.53
2.82
3.44
1.62– 3.26
1.23– 2.10
1.23– 2.86
1.60– 3.77
1.70–4.20
2.10–4.87
3.03
4.55
5.82
23.48
27.63
37.11
M
1.82
1.74
2.21
2.68
2.88
3.58
IQR
R
1.46– 315
3.04
1.26– 1.26
5.37
1.44– 3.44
5.51
1.65– 3.79
5.26
1.79–4.02
32.56
2.15–4.68
32.89
M
IQR
1.62
1.43– 1.90
1.65
1.26– 2.02
1.79
1.20– 2.56
2.43
1.65– 3.44
2.68
1.70–3.71
3.22
2.04–4.50
R
0.89
5.06
5.82
28.63
32.70
34.45
3.12
...............................................................................................................................................................................
0 –1000
M
IQR
R
1001–2000
2001–3000
3001–4000
M
1.62
1.67
1.70
2.26
2.56
IQR
1.35– 1.97
1.01– 2.15
1.2–2.37
1.60– 3.21
1.79–4.00
2.15–4.42
R
0.89
5.76
5.56
23.69
27.65
44.71
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J.P. Ugarte et al.
A
B
C
D
0.07
ApEn
0.14
Figure 3 Dynamic approximate entropy map reconstructed using spatial resolutions of (A) 0.8 mm, (B) 2.4 mm, and (C) 4.0 mm.
A
B
C
D
mV
5
–16
–38
3
2
1
–58
–80
Figure 4 (A) Simple ablation patterns (red lines 1, 2, and 3). (B – D) Only one of the three ablation patterns (pattern 3) was effective in ending
the AF activity.
time, this high ApEn value zone encloses lower ApEn values, which
implies some degree of regularity; refer to Figure 2B. This agrees
with other works reporting the highest dominant frequency (DF)
and regularity at the rotor tip23; and irregularity surrounding the
tip.20,24 Supplementary material refers to DF analysis: Supplementary material online, Figure S1 shows DF and regularity index (RI)
maps. Regularity index and DApEn maps exhibit similar characteristics: RI map depicts the EGM from the core of the rotor as the most
regular (RI ¼ 0.9058), while DApEn map assigns some degree of regularity (ApEn ¼ 0.1177) to the core but not the most regular
(ApEn ¼ 0.06). Moreover, DApEn maps allow better temporal
resolution than DF analysis, being that DF requires at least 2 s
EGM for reliable measurements,25 while ApEn could be calculated
using at least 500 ms.17
Phase diagrams are used to locate the tip of the rotor and to track
itsmotion.26 Our results showed the DApEn map generating a starform shape that surrounds the rotor tip. There are works reporting
the motion of the tip describing a star, using phase diagrams16,27
built from time series of membrane potentials or from EGM. The
phase diagram also gives information about the rotation direction.
ii103
Effect of the electrograms density
However, calculation of phase diagrams using EGM requires a prefiltering stage in order to reduce the EGM to a sinusoidal signal.
Additionally, to generate a phase diagram, high spatial resolution is
required. In this study, it was showed that a DApEn map is able to
depict the meandering of the tip, which fits with the result of phase
diagram. Furthermore, the star depicted in DApEn map reveals the
rotor clockwise rotation (see Supplementary material online, Video
S3). Thus, DApEn maps are strong candidates for analysing rotor
characteristics.
There are studies reporting computational tools that are aimed to
characterize rotors from EGM records.6,24,28 The isochrones method to track rotors is being applied in the clinical environment. This
tool heavily depends on the time of observation and the spatial resolution, i.e. the number of recording electrodes available and the extraction of temporal characteristics from the EGM signal. In a
previous work, we showed that using a high density of unipolar
EGM, DApEn maps are able to identify the rotor tip position, by
means of quantification of fractionated EGM using the ApEn statistic, either the rotor is stable or it meanders.17 In the present work,
we aimed to study the DApEn maps behaviour using spatial resolutions similar to those available in commercial catheters. Spatial
resolutions of 0.8, 2.4, and 4.0 mm provide similar eTL median values ,2.21 mm. Furthermore, IQR values evidenced higher accuracy than spatial resolutions ≥5.2 mm. Minor dependence on the
electrodes array position, for d ≤ 4.0 mm, is also evidenced by
R values. These results led to suggest a minimum spatial resolution
of 4.0 mm to accurately detect the rotor tip. Under our design, this
value corresponds to an array with 225 EGM within 36 cm2. It is
important to highlight that the irregularity area surrounding the
tip is broader than the regularity area at the rotor tip. Dynamic approximate entropy map with 0.4 mm resolution (Figure 2D) differs
from those with lower resolution (Figure 3) in that regularity area is
not distinguishable in the latter. This could have practical consequences: commercial electrode arrays, with inter-electrode distance .2 mm, make it difficult to locate the rotor tip using high
frequency and high regularity criteria described by Kalifa et al. 23
Moreover, this behaviour at the rotor tip was observed using
optical mapping with a spatial resolution of 0.39 mm, similar to
our high spatial resolution array (d ¼ 0.4 mm). Despite this, high
fractionation surrounding the rotor tip could be detected by
using ApEn criteria with lower spatial resolution. Nowadays,
64-electrodes basket catheter is used in the clinical practice to locate rotors.7 Further studies are needed to assess the clinical use
of DApEn maps using this kind of electrodes. Although a resolution
of 0.4 mm or higher is needed to find the regularity characteristic
in the rotor tip, the irregularity could be observed using a lower
resolution, up to 4 mm.
In this work, three simple ablation patterns guided by DApEn
maps were designed, attempting to successfully terminate the rotor
activity. Only the ablation pattern composed by a line passing
through the rotor tip and ending at the tissue boundary was effective
in terminating the rotor. Experimental studies29,30 have developed
modifications to the Maze procedure, in order to simplify the surgical technique, reducing time, adverse effects, and postsurgical complications. Intuitively, the ideal ablation pattern should be able to
prevent arrhythmias with a limited number of lines, with minimum
length and to allow the mechanical activity recovery of the atria
during sinusrhythm.31 Recent studies have demonstrated that rotor
ablation is highly effective in terminating AF.6
Although the ablation of the rotor, using the information resulted
from the DApEn maps, was successful; conclusions cannot be extended beyond the conditions of our simulation. Cardiac fibrillation
occurs in a complex 3D structure and our study was performed in a
simplified 2D monolayer model. Nevertheless, we focused on ionic
mechanisms of fibrillatory activity. Our methods thus provide a wellcontrolled system to simulate rotor activity under cAF conditions.
Future studies should include 3D atria models, which could give outline to clinicians in order to apply the DApEn maps in real procedures. In the previous work, involving a 3D human atria, the tips
of two rotors were located. However, the tip motion cannot be described due to the fact that recorded signals density per area was
lower than the one we used for this study. Further developments
of the DApEn maps should address this drawback, from the viewpoint of performance in real procedures. One possible solution is
to look for an ApEn-parameters configuration that suits the tip motion tracking purpose.
Conclusion
Dynamic approximate entropy maps were previously reported, successfully detecting simulated rotor tips using a high density of EGM.
In this work, different spatial resolutions for rotor detection using
DApEn maps in a 2D AF model were assessed. We provided evidence to suggest a spatial resolution ≤4 mm to accurately detect
the rotor tip. This value is close to existing commercial electrode
arrays used in electrophysiological procedures. Additionally, it was
shown that DApEn maps are able to track the tip motion and to provide information about the rotation direction, using the full array;
evidencing DApEn maps as a rotor characterization tool. This is
the first step to translate this tool into medical practice with a
view to the detection of ablation targets.
Supplementary material
Supplementary material is available at Europace online.
Funding
This work was supported by the “Departamento Administrativo de
Ciencia, Tecnologı́a e Innovación—COLCIENCIAS” of Colombia, by
research project #121056933647; and by the project with ITM code
P14112 and IUSH code 250.
Conflict of interest: none declared.
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