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It is commonly asserted that MRI-derived lesion masks outperform CT-derived lesion masks in lesion-mapping analysis. However, no quantitative analysis has been conducted to support or refute this claim. This study reports an objective comparison of lesion-mapping analyses based on CT- and MRI-derived lesion masks to clarify how input imaging type may ultimately impact analysis results. Routine CT and MRI data were collected from 85 acute stroke survivors. These data were employed to create binarized lesion masks and conduct lesion-mapping analyses on simulated behavioral data. Following standard lesion-mapping analysis methodology, each voxel or region of interest (ROI) were considered as the underlying "target" within CT and MRI data independently. The resulting thresholded z-maps were compared between matched CT- and MRI-based analyses. Paired MRI- and CT-derived lesion masks were found to exhibit significant variance in location, overlap, and size. In ROI-level simulations, both CT and MRI-derived analyses yielded low Dice similarity coefficients, but CT analyses yielded a significantly higher proportion of results which overlapped with target ROIs. In single-voxel simulations, MRI-based lesion mapping was able to include more voxels than CT-based analyses, but CT-based analysis results were closer to the underlying target voxel. Simulated lesion-symptom mapping results yielded by paired CT and MRI lesion-symptom mapping analyses demonstrated moderate agreement in terms of Dice coefficient when systematic differences in cluster size and lesion overlay are considered. Overall, these results suggest that CT and MR-derived lesion-symptom mapping results do not reliably differ in accuracy. This finding is critically important as it suggests that future studies can employ CT-derived lesion masks if these scans are available within the appropriate time-window.

Original publication

DOI

10.1016/j.neuropsychologia.2023.108564

Type

Journal article

Journal

Neuropsychologia

Publication Date

15/04/2023

Volume

184

Keywords

Clinical neuroimaging, Lesion symptom mapping, Routine imaging, Stroke