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 15O-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 (DWI+ and DWI-, 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 (n=4), there was good concordance between predictive values of MTT (positron emission tomography) and MTT (perfusion-weighted imaging) for both DWI+ and DWI- voxels of interest indicating adequate reliability of MTT (perfusion-weighted imaging) for this purpose. In the I-KNOW data set (N=42), the MTT significantly added to the DWI lesion to predict infarction in both DWI- and DWI+ voxels of interest with areas under the curve approximately 0.78 and 0.64 (both P<0.001) 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.
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 15O-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 (DWI+ and DWI-, 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 (n=4), there was good concordance between predictive values of MTT (positron emission tomography) and MTT (perfusion-weighted imaging) for both DWI+ and DWI- voxels of interest indicating adequate reliability of MTT (perfusion-weighted imaging) for this purpose. In the I-KNOW data set (N=42), the MTT significantly added to the DWI lesion to predict infarction in both DWI- and DWI+ voxels of interest with areas under the curve approximately 0.78 and 0.64 (both P<0.001) 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.
Authors: Jean Marc Olivot; Michael Mlynash; Manabu Inoue; Michael P Marks; Hayley M Wheeler; Stephanie Kemp; Matus Straka; Gregory Zaharchuk; Roland Bammer; Maarten G Lansberg; Gregory W Albers Journal: Stroke Date: 2014-03-04 Impact factor: 7.914
Authors: Anna Christina Alegiani; Simon MacLean; Hanna Braass; Susanne Gellißen; Tae-Hee Cho; Laurent Derex; Marc Hermier; Yves Berthezene; Norbert Nighoghossian; Christian Gerloff; Jens Fiehler; Götz Thomalla Journal: Front Neurol Date: 2019-02-26 Impact factor: 4.003
Authors: Anna Christina Alegiani; Simon MacLean; Hanna Braass; Susanne Siemonsen; Christian Gerloff; Jens Fiehler; Tae-Hee Cho; Laurent Derex; Marc Hermier; Yves Berthezene; Norbert Nighoghossian; Götz Thomalla Journal: PLoS One Date: 2017-11-30 Impact factor: 3.240