Reperfusion Half-Life
A Novel Pharmacodynamic Measure of Thrombolytic Activity
José G. Merino, MD, MPhil; Lawrence L. Latour, PhD; Li An, PhD; Amie W. Hsia, MD;
Dong-Wha Kang, MD; Steven Warach, MD, PhD
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Background and Purpose—We hypothesized that the probability of reperfusion can be modeled by an exponential decay
(ie, half-life) function and that this reperfusion half-life is decreased by thrombolytic treatment.
Methods—Serial perfusion MRI scans were evaluated for evidence of reperfusion in intravenous tissue plasminogen
activator-treated (n⫽45) and untreated (n⫽103) patients. The cumulative probability of reperfusion for each group was
fit with exponential decay functions. The resulting reperfusion half-life (ie, the time it takes half the sample to reperfuse)
was calculated.
Results—In untreated patients, a monoexponential decay function fit the data well (R2⫽0.95) with a half-life of 29.1 hours.
In tissue plasminogen activator-treated patients, the data were best fit with a biexponential decay function (R2⫽0.99) that
had a fast and a slow component. The fast component is attributable to tissue plasminogen activator therapy and has a
half-life of 0.71 hours, whereas the slow component was similar to that of the untreated group. Approximately 3.5 hours
after the start of treatment, the effect of tissue plasminogen activator on the probability of reperfusion was negligible.
Conclusion—The probability of reperfusion can be well described by the reperfusion half-life. Determination of the fast
component reperfusion half-life may be an approach to compare the relative potency of different thrombolytic agents.
(Stroke. 2008;39:2148-2150.)
Key Words: MRI 䡲 reperfusion 䡲 stroke 䡲 thrombolytic therapy
T
issue reperfusion is the goal of acute stroke therapies,
and prompt reperfusion is associated with smaller final
infarct volume and improved outcome.1,2 Reperfusion is a
naturally occurring dynamic process that can be augmented
and accelerated in some patients using a thrombolytic
agent.1,3–5 Among untreated patients, the probability of finding a penumbral pattern decreases gradually over time,6 and
the probability of a favorable response to intravenous tissue
plasminogen activator (tPA) also declines logarithmically as
time from stroke onset to initiation of treatment increases.
Many biological processes, including drug kinetics, follow an
exponential decay model, and we hypothesized that reperfusion of ischemic stroke does as well.7
The purpose of this study was to parameterize the time–
reperfusion relationship in tPA-treated patients. We hypothesized that (1) the rate of spontaneous reperfusion can be
modeled using an exponential decay function from which the
reperfusion half-life, the time it takes for half the patients to
have reperfusion, can be calculated; and that (2) treatment
with intravenous tPA will shift the curve to the left, leading to
a shorter reperfusion half-life.
Methods
Patients
This is an analysis of data collected prospectively as part of a natural
history study approved by the Institutional Review Board at the
National Institute of Neurological Diseases and Stroke and Suburban
Hospital. All patients or their authorized representative signed
informed consent. We considered all consecutive patients with
ischemic stroke who had a baseline MRI with diffusion- and
perfusion (PWI)-weighted images within 24 hours of onset and at
least one follow-up PWI within 1 week. We included patients who
were treated in a standard fashion as per the clinical pathway of the
National Institutes of Health Stroke Program at Suburban Hospital,
including those who received intravenous tPA consistent with
current guidelines.8 We excluded patients treated with intraarterial
thrombolytics or who were enrolled in clinical trials, patients who
despite a clinical diagnosis of stroke had negative diffusion-weighted
and PWI images at baseline, and patients with brainstem or
lacunar stroke.
Imaging
Imaging was performed in a 1䡠5-Tesla MRI scanner. Typical MRI
parameters and the methodology used to generate mean transit time
maps from the PWI using the first over zeroeth moment have been
previously described.2 Three readers reviewed the images in 2
stages. In the first stage, we identified patients who had imaging
Received November 23, 2007; accepted November 28, 2007.
From the Section on Stroke Diagnostics and Therapeutics (J.G.M., L.L.L., L.A., S.W.), National Institute of Neurological Disorders and Stroke,
National Institutes of Health, Bethesda, Md; the Washington Hospital Center Stroke Center (A.W.H.), Washington, DC; and the Department of Neurology
(D.W.K.), Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Correspondence to José G. Merino, MD, MPhil, Suburban Hospital Stroke Program, 8600 Old Georgetown Rd, Bethesda, MD 20814. E-mail
[email protected]
© 2008 American Heart Association, Inc.
Stroke is available at http://stroke.ahajournals.org
DOI: 10.1161/STROKEAHA.107.510818
2148
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Merino et al
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Figure 1. Cumulative probability of reperfusion
over time. A, Untreated group, monoexponential
model. B, Treated group, monoexponential
model. C, Untreated group, biexponential model.
D, Treated group, biexponential model.
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Time after Stroke Onset (hours)
exclusion criteria using baseline diffusion-weighted images, PWI,
gradient recalled echo, and fluid-attenuated inversion recovery images of potentially eligible patients. In the second stage, we reviewed
the baseline diffusion-weighted images and baseline and follow-up
mean transit time maps of patients not excluded in the first stage to
determine whether reperfusion had occurred with respect to baseline
(a dichotomous outcome). For this analysis, we were interested in
any degree of visually apparent reperfusion, which we believe
represents a decrease of the mean transit time delay volume of at
least 20% to 30%, a change in volume associated with good clinical
outcome.2–5
Statistical Analysis and Modeling
We analyzed patients in 2 groups: treated versus not treated with
intravenous tPA. We compared groups using Student t, the Mann–
Whitney, or Fisher exact test, as appropriate, and calculated the
cumulative probability of reperfusion (the complement of the probability of survival) using standard Kaplan–Meier methodology. For
the survival analysis, we considered the time to reperfusion as the
midpoint between the last scan without reperfusion and the first scan
in which reperfusion was noted. Patients who at baseline had a
diffusion-weighted lesion but a normal PWI were included in the
analysis, and the midpoint between the onset of symptoms and the
baseline scan was taken as the time of reperfusion. We fit mono- and
biexponential decay models using a nonlinear least squares algorithm
using an IDL program with a Levenberg-Marquardt nonlinear
least-square fitting subroutine (see Supplemental Table I, available
online at http://stroke.ahajournals.org for details) and calculated a
decay constant (␶) and the reperfusion half-life, as described in
Supplemental Table I.9 Initially, we fit a monoexponential function,
and if this did not fit the data well, we used a biexponential one.
Results
In a period of 40 months, we evaluated 497 consecutive
patients with ischemic stroke who had a baseline MRI and at
least another PWI scan within 1 week of onset of symptoms.
For this analysis, we excluded, before the first stage, 303
patients because they did not meet baseline inclusion/exclusion criteria and, after the first stage, 46 patients who had
imaging exclusion criteria. Thus, 148 patients were included
in the final sample and evaluated in the second stage: 45 who
were treated with intravenous tPA and 103 who were not
(Supplemental Table II). The median time to reperfusion in
the untreated group was longer than in the tPA-treated group
(24.7 hours; 95% CI, 20.1 to 29.3 hours versus 7.7 hours;
95% CI, 0 to 18.1 hours, respectively; P⫽0.004).
In the untreated group, the cumulative probability of
reperfusion was well fit by a monoexponential function
(R2⫽0.95, ␶⫽41.97). The reperfusion half-life was 29.1 hours
(Figure 1; Table). In contrast, the cumulative probability data
from the tPA-treated group was less well fit by a monoexponential function (R2⫽0.83). However, a biexponential function with fast and slow components of markedly different
time constants fit the tPA data much better (R2⫽0.99; Figure
2). The inflection point of the curve occurred 3.5 hours after
onset of treatment; at this time, 97% of patients who would
reperfuse at the fast rate had done so. Reperfusion occurred
early in 41% of tPA-treated patients with a time constant, ␶1,
of 1.02 hours and a half-life of 0.7 hours after treatment. This
is suggestive of the effect of tPA. Reperfusion occurred late
in 54% of the tPA-treated patients with a time constant, ␶2, of
42.18 hours and a half-life of 29.2 hours, which is similar to
that of the untreated group. This suggests that in this fraction
of patients, reperfusion occurred spontaneously through intrinsic mechanisms and was not due to the effect of tPA.
From the model we estimate that the remaining 5% of
patients had some reperfusion before the start of tPA at the
spontaneous reperfusion rate.
Discussion
Time to reperfusion after acute stroke is well described by the
reperfusion half-life, a novel pharmacodynamic variable.
Table. Time Constant and Reperfusion Half-Lives for the
Spontaneous Reperfusion and the Intravenous tPA Groups
Time
Constant (␶)
Spontaneous reperfusion
Intravenous tPA (fast component)
Intravenous tPA (slow
component)
41.97
Reperfusion
Half-Life (t1⁄2)
29.1 hour
1.02
0.7 hours*
42.18
29.2 hours*
*Time from start of intravenous tPA infusion.
Cumulative Probability of Reperfusion
2150
Stroke
July 2008
scans. Both factors may affect the slope of the reperfusion
curve, but the fact that the spontaneous reperfusion rate is
similar to the slow component among the tPA-treated patients
gives us confidence that the differences in the timing and
number of scans do not affect the validity of the model.
In conclusion, modeling the rate of reperfusion, and calculating the reperfusion half-life, provides a measure of the
speed and duration of thrombolytic activity and may lead to
improvements in the design of MRI-based clinical trials that
use reperfusion as a marker of outcome.
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Figure 2. Fast (light green) and slow (dark green) components
of the biexponential function that describes the cumulative
probability of reperfusion data from intravenous tPA-treated
patients. The curve for the slow component is shifted upward to
show how the biexponential curve results from the summation
of both components.
Modeling the probability of reperfusion to calculate the
reperfusion half-life can help differentiate spontaneous from
therapy-induced reperfusion and may potentially be used to
compare the effects of 2 drugs. We recognize that our
findings must be replicated using different patient samples
and measures of recanalization and reperfusion, and although
we expect that the exact value of the time constants to vary,
we believe that the principles underlying the model will hold.
The model described in this study can help determine the
optimal imaging time to discriminate between responders and
nonresponders. From the model we found that the optimal
time to detect tPA-related reperfusion among patients treated
was 3.5 hours, approximately 5 reperfusion half-lives. We
speculate that the optimal imaging time is different for each
thrombolytic agent, and future clinical trials that have an
imaging outcome may be improved if the agent-specific
optimal time to ascertain treatment-induced reperfusion is
identified. Our findings, if replicated, can also be used in
clinical practice; if a treated patient has not reperfused 3.5
hours after tPA, then another intervention may be warranted.
Our study has several limitations. Because reperfusion is a
dynamic process, and imaging studies were only performed at
discrete time points, the exact time of reperfusion is unknown. However, we used standard survival analysis methodology to determine the time to the event and, because our
sample is large, this method yields a good estimate of the
actual reperfusion time. Patients in the intravenous tPAtreated group were scanned earlier than patients in the
spontaneous reperfusion group; this is unavoidable, because
patients seen soon after symptom onset are scanned sooner
and are more likely to receive thrombolytics. Because the
baseline scan in the spontaneous reperfusion group was later,
these patients were more likely to have unidentified partial
reperfusion at baseline. In addition, these patients had fewer
We thank the members of the National Institutes of Health Stroke
Team at Suburban Hospital who assisted with data collection and
patient care.
Source of Funding
This research was supported by the Division of Intramural Research
of the National Institute of Neurological Disorders and Stroke,
National Institutes of Health.
Disclosures
None.
References
1. Barber PA, Davis SM, Infeld B, Baird AE, Donnan GA, Jolley D, Lichtenstein M. Spontaneous reperfusion after ischemic stroke is associated
with improved outcome. Stroke. 1998;29:2522–2528.
2. Chalela JA, Kang DW, Luby M, Ezzeddine M, Latour LL, Todd JW, Dunn
B, Warach S. Early magnetic resonance imaging findings in patients
receiving tissue plasminogen activator predict outcome: insights into the
pathophysiology of acute stroke in the thrombolysis era. Ann Neurol.
2004;55:105–112.
3. Hacke W, Albers G, Al-Rawi Y, Bogousslavsky J, Davalos A, Eliasziw M,
Fischer M, Furlan A, Kaste M, Lees KR, Soehngen M, Warach S. The
desmoteplase in acute ischemic stroke trial (DIAS): a Phase II MRI-based
9-hour window acute stroke thrombolysis trial with intravenous desmoteplase. Stroke. 2005;36:66 –73.
4. Furlan AJ, Eyding D, Albers GW, Al-Rawi Y, Lees KR, Rowley HA,
Sachara C, Soehngen M, Warach S, Hacke W. Dose Escalation of Desmoteplase for Acute ischemic Stroke (DEDAS): evidence of safety and
efficacy 3 to 9 hours after stroke onset. Stroke. 2006;37:1227–1231.
5. Albers GW, Thijs VN, Wechsler L, Kemp S, Schlaug G, Skalabrin E,
Bammer R, Kakuda W, Lansberg MG, Shuaib A, Coplin W, Hamilton S,
Moseley M, Marks MP. Magnetic resonance imaging profiles predict
clinical response to early reperfusion: the diffusion and perfusion imaging
evaluation for understanding stroke evolution (DEFUSE) study. Ann
Neurol. 2006;60:508 –517.
6. Darby DG, Barber PA, Gerraty RP, Desmond PM, Yang Q, Parsons M, Li
T, Tress BM, Davis SM. Pathophysiological topography of acute ischemia
by combined diffusion-weighted and perfusion MRI. Stroke. 1999;30:
2043–2052.
7. Hacke W, Donnan G, Fieschi C, Kaste M, von Kummer R, Broderick JP,
Brott T, Frankel M, Grotta JC, Haley EC Jr, Kwiatkowski T, Levine SR,
Lewandowski C, Lu M, Lyden P, Marler JR, Patel S, Tilley BC, Albers G,
Bluhmki E, Wilhelm M, Hamilton S. Association of outcome with early
stroke treatment: pooled analysis of ATLANTIS, ECASS, and NINDS
rt-PA stroke trials. Lancet. 2004;363:768 –774.
8. Lattimore SU, Chalela J, Davis L, DeGraba T, Ezzeddine M, Haymore J,
Nyquist P, Baird AE, Hallenbeck J, Warach S. Impact of establishing a
primary stroke center at a community hospital on the use of thrombolytic
therapy: the NINDS Suburban Hospital Stroke Center experience. Stroke.
2003;34:e55–57.
9. Marquardt D. An algorithm for least-squares estimation of nonlinear parameters. J Soc Indust Appl Math. 1963;11:431– 441.
Reperfusion Half-Life: A Novel Pharmacodynamic Measure of Thrombolytic Activity
José G. Merino, Lawrence L. Latour, Li An, Amie W. Hsia, Dong-Wha Kang and Steven
Warach
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Stroke. 2008;39:2148-2150; originally published online May 1, 2008;
doi: 10.1161/STROKEAHA.107.510818
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