The association between neurological deficit in acute ischemic stroke and mean transit time

Background and Purpose-There is ample evidence that in anterior circulation stroke, the diffusion-weighted imaging (DWI) lesion may escape infarction and thus is not a reliable infarct predictor. In this study, we assessed the predictive value of the mean transit time (MTT) for final infarction within the DWI lesion, first in patients scanned back-to-back with 15 O-positron emission tomography and MR (DWI and perfusion-weighted imaging; "Cambridge sample") within 7 to 21 hours of clinical onset, then in a large sample of patients with anterior circulation stroke receiving DWI and perfusion-weighted imaging within 12 hours (85% within 6 hours; "I-KNOW sample"). Methods-Both samples underwent structural MRI at approximately 1 month to map final infarcts. For both imaging modalities, MTT was calculated as cerebral blood volume/cerebral blood flow. After image coregistration and matrix resampling, the MTT values between voxels of interest that later infarcted or not were compared separately within and outside DWI lesions (DWIϩ and DWIϪ, respectively) both within and across patients. In the I-KNOW sample, receiver operating characteristic curves were calculated for these voxel of interest populations and areas under the curve and optimal thresholds calculated. Results-In the Cambridge data set (nϭ4), there was good concordance between predictive values of MTT positron emission tomography and MTT perfusion-weighted imaging for both DWI؉ and DWIϪ voxels of interest indicating adequate reliability of MTT perfusion-weighted imaging for this purpose. In the I-KNOW data set (Nϭ42), the MTT significantly added to the DWI lesion to predict infarction in both DWIϪ and DWI؉ voxels of interest with areas under the curve approximately 0.78 and 0.64 (both PϽ0.001) and optimal thresholds approximately 8 seconds and 11 seconds, respectively. Conclusions-Despite the relatively small samples, this study suggests that adding MTT perfusion-weighted imaging may improve infarct prediction not only as already known outside, but also within, DWI lesions. (Stroke. 2011;42:1602-1607.)

Section: Discussionsupporting

confidence: 68%

Predicting Infarction Within the Diffusion-Weighted Imaging Lesion

Carrera

Jones

Alawneh

et al. 2011

“…[12][13][14][15][16] Different ways of estimating a single PWI parameter like MTT may yield differently sized PWI lesions. 17 Comparisons of how well different relative and/or quantitative PWI lesions predict infarct growth yield differing results, [17][18][19] possibly due to differences in patient case mix or the timing of scanning, as well as to variations in the combinations of PWI processing methods used.…”

Section: Does This Variation Matter?mentioning

confidence: 99%

Comparison of 10 Different Magnetic Resonance Perfusion Imaging Processing Methods in Acute Ischemic Stroke

Kane

Carpenter

Chappell

et al. 2007

142

Background and Purpose-Several methods are available to assess the magnetic resonance perfusion lesion in acute ischemic stroke. We tested 10 of these to compare perfusion lesion sizes and to assess the relation to clinical scores and final infarct extent. Methods-We recruited patients with acute ischemic stroke, performed diffusion-and perfusion-weighted imaging, and recorded stroke severity at baseline, final infarct size on T2-weighted imaging at Ն1 month, and Rankin Scale score at 3 months. We calculated 10 perfusion parameters (6 of mean transit time, MTT; 3 of cerebral blood flow; 1 of cerebral blood volume; 7 relative and 3 quantitative), measured the perfusion-weighted imaging lesion and diffusion/perfusion mismatch volumes, and compared each with clinical and radiologic outcomes. Results-Among 32 patients, the median perfusion lesion volume varied from 0 to 14 882 voxels (PϽ0.0001); the proportion of patients with mismatch varied from 9% to 72% (PϽ0.05), depending on the perfusion parameter. Five measures of relative MTT were associated with baseline National Institutes of Health Stroke Scale score; 1 (arrival time fitted) was also associated with clinical outcome. Final infarct size was most strongly associated with MTT measures, including arrival time fitted. There was no advantage of quantitative perfusion measures and no relation between mismatch presence/absence and infarct expansion with any of the 10 perfusion measures. Conclusions-Perfusion lesion size differs markedly depending on the parameter calculated. Relative perfusion parameters performed as well as quantitative ones. Some parameters (mainly representing MTT measures) were correlated with clinical scores; others were correlated with final infarct size; and arrival time fitted was correlated with both. These findings should be validated in other datasets. A consensus is required on which perfusion measurement and processing methods should be used.

“…Based on these findings, several MR studies have aimed at identifying parameters and thresholds that correspond best with this penumbral threshold. [5][6][7] In practice, the hypoperfused at-risk region is most commonly defined as a region above a certain threshold value of mean transit time or time to peak of the residue function (Tmax). 8 It is clear that lower threshold values may include significant amounts of benign oligemia, 9 and that no single threshold is capable of accurately predicting tissue fate, even in homogenous groups of patients without reperfusion.…”

mentioning

confidence: 99%

Moving Beyond a Single Perfusion Threshold to Define Penumbra

Nagakane

Christensen

Ogata

et al. 2012

Background and Purpose— The mismatch lesion volumes defined by perfusion-weighted imaging exceeding diffusion-weighted imaging have been used as a marker of ischemic penumbral tissue. Defining the perfusion lesion by thresholding has shown promise as a practical tool; several positron emission tomography studies have indicated a more probabilistic relationship between perfusion and infarction. Here, we used a randomized controlled trial dataset of tissue-type plasminogen activator 3 to 6 hours after stroke to: (1) quantify the relationship between severity of hypoperfusion (measured by Tmax) and risk of infarction; (2) exploit this relationship to present a novel definition of mismatch based on infarct probabilities rather than dichotomies; and (3) examine the treatment response in the subgroup of patients with mismatch by the new definition. Methods— Patients from the Echoplanar Imaging Thrombolytic Evaluation Trial (EPITHET) were included. Baseline perfusion-weighted imaging and 90-day T2-weighted imaging were coregistered. Perfusion-weighted imaging lesion volumes were divided into 10 Tmax delay strata, and infarct risk was defined as the fraction of the tissue at a given Tmax strata that progressed to infarction by day 90. Results— Sixty-two patients were studied. Infarct risk was an increasing function of Tmax for all subgroups, including the whole cohort. The probabilistic approach outperformed all Tmax thresholds, with exception of the Tmax ≥10 threshold, for which it was only favored by a trend. Conclusions— Infarct risk and treatment effect increased with severity of perfusion abnormalities. This suggests that a severity-weighted mismatch definition may define penumbral tissue more accurately.