Automated Measurement of Net Water Uptake From Baseline and Follow-Up CTs in Patients With Large Vessel Occlusion Stroke

作者：Atul Kumar, Yasheng Chen, Aaron M. Corbin, Ali Hamzehloo, Amin Abedini, Zeynep Vardar, Grace Carey, Kunal Bhatia, Laura Heitsch, Jamal J. Derakhshan, Jin‐Moo Lee, Rajat Dhar · 发表于：Frontiers in Neurology · 年份：2022 · DOI：10.3389/fneur.2022.898728 · 被引用次数：20 · 研究领域：Acute Ischemic Stroke Management、Cerebrovascular and Carotid Artery Diseases、Photoacoustic and Ultrasonic Imaging

Quantifying the extent and evolution of cerebral edema developing after stroke is an important but challenging goal. Lesional net water uptake (NWU) is a promising CT-based biomarker of edema, but its measurement requires manually delineating infarcted tissue and mirrored regions in the contralateral hemisphere. We implement an imaging pipeline capable of automatically segmenting the infarct region and calculating NWU from both baseline and follow-up CTs of large-vessel occlusion (LVO) patients. Infarct core is extracted from CT perfusion images using a deconvolution algorithm while infarcts on follow-up CTs were segmented from non-contrast CT (NCCT) using a deep-learning algorithm. These infarct masks were flipped along the brain midline to generate mirrored regions in the contralateral hemisphere of NCCT; NWU was calculated as one minus the ratio of densities between regions, removing voxels segmented as CSF and with HU outside thresholds of 20–80 (normal hemisphere and baseline CT) and 0–40 (infarct region on follow-up). Automated results were compared with those obtained using manually-drawn infarcts and an ASPECTS region-of-interest based method that samples densities within the infarct and normal hemisphere, using intraclass correlation coefficient (ρ). This was tested on serial CTs from 55 patients with anterior circulation LVO (including 66 follow-up CTs). Baseline NWU using automated core was 4.3% (IQR 2.6–7.3) and correlated with manual measurement (ρ = 0.80, p < 0....