Abstract DP136: Macrovascular angiographic and tissue-level perfusion collateral scoring to predict inter-hospital infarct growth rate

Introduction: In acute ischemic stroke patients, collateral circulation is an important target for neuroprotectant treatments as it influences tissue survival and clinical outcomes. Collateral status is determined with the expert-rated Tan score on CT Angiography (CTA) or tissue-level perfusion metrics on CT Perfusion (CTP). We developed a deep learning–based vessel segmentation method for CTA to quantify all vessels- and artery-only collateral scores (vesQCS, aQCS). We aim to (1) compare the performance of macrovascular and tissue-level collateral status for predicting inter-hospital infarct growth rate (IGR) and (2) evaluate if a mismatch in macrovascular and tissue-level collateral status influences IGR. Methods: We included patients recruited in a prospective, multicenter study who were transferred from a primary to a comprehensive stroke center for EVT (n=387). vesQCS and aQCS were defined as the ratio of deep learning–segmented vessel or artery volume in the infarcted versus contralateral hemisphere (Figure-1). Tan score was expert-rated, while tissue level collaterals such as the Hypoperfusion Intensity Ratio (HIR: Tmax>10s/Tmax>6s) and the mismatch volume (Tmax>6s-rCBF