Abstract Number: Esoc2026a898 Time to Imaging and Reperfusion Status Modify Ct Perfusion Prediction of Malignant Cerebral Infarction
Year: 2026
Type: conference-abstract
Abstract: Background and aims Malignant cerebral infarction (MCI) is a life-threatening complication of large vessel occlusion (LVO). Baseline CT-perfusion (CTP) thresholds and ASPECTS predict MCI, but their performance may depend on time-to-imaging and reperfusion success. We evaluated whether these factors influence the predictive accuracy of baseline markers (ASPECTS, relative cerebral blood volume [rCBV], relative cerebral blood flow [rCBF]) for MCI. Methods We retrospectively analyzed 249 patients with severe anterior circulation LVO and multimodal CT at admission. Patients were stratified into four groups by time-to-CTP (Early <3h vs. Late ≥3h) and reperfusion status (Successful, mTICI 2b–3 vs. Unsuccessful). MCI was defined by both clinical and radiological criteria. Predictive performance of ASPECTS, rCBV, and rCBF core volumes across thresholds (0–100% of contralateral values) was assessed using ROC area, sensitivity, specificity, positive predictive value (PPV), and F1-score. Results MCI occurred in 62/249 patients (25%). Time and reperfusion showed a strong interaction (p<0.001): rates were 12% (Early+Successful), 32% (Early+Unsuccessful), 14% (Late+Successful), and 46% (Late+Unsuccessful). In the Early+Unsuccessful group, rCBV<40% had higher predictive capacity than ASPECTS or rCBF. In the Late+Unsuccessful group, all three parameters reached high predictive values. In both reperfused subgroups, PPV for all baseline parameters dropped to 20–35% despite sensitivity >90%. Conclusions Baseline imaging prediction of MCI is strongly time- and reperfusion-dependent. rCBV is the most robust early marker of malignant evolution when reperfusion fails, whereas successful reperfusion essentially invalidates predictions derived from baseline cores. Conflict of interest Name of author: nothing to disclose
Source: European Stroke Journal
Authors: Antonio Doncel-Moriano, Alejandro Rodríguez Vázquez, Andrea Cabero-Arnold, Irene Rosa Batlle, Arturo Renú, Inés Bartolomé, Salvatore Rudilosso, Martha Vargas, Xabier Urra, Angel Chamorro
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,400
OpenAlex ID: W7160411714
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