Automatically Quantified Follow-Up Imaging Biomarkers Predict Clinical Outcomes After Acute Ischemic Stroke

Background: Follow-up infarct volume (FIV) is a proposed surrogate endpoint for proof-of-concept clinical studies in acute ischemic stroke (AIS). This study aimed to provide clinical validation of an automated FIV algorithm, demonstrating the association of imaging biomarkers with clinical outcomes to support the use of these imaging endpoints in clinical trials.

Methods: Data were gathered for adult AIS patients undergoing mechanical thrombectomy with follow-up imaging 12–96 h from initial assessment. Non-contrast computed tomography was used to quantify infarct volume. Image processing used the AI-powered software Brainomix 360 Stroke and Brainomix core lab research software. The primary clinical endpoint was modified Rankin Scale (mRS) at 90 days; secondary clinical endpoint was NIH Stroke Scale (NIHSS) score at 24 h.

Results: Of 986 patients, 843 (85.5%; median age 72 years) had complete data. FIV was significantly associated with 90-day mRS (concordance = 0.819, p < 0.001) and NIHSS at 24 h (concordance = 0.722, p < 0.001). In multivariate analysis, FIV remained strongly associated with 90-day mRS, and showed a bimodal distribution consistent with success/failure of recanalization during thrombectomy.

Conclusion: Of the algorithm outputs assessed, FIV was most strongly associated with clinical outcomes. This study validates the prognostic significance of automated FIV and its composites as mechanistic endpoints to improve early-stage trials of therapeutics in AIS.