Background Radiomic and transcriptomic analyses have independently identified features linked to mechanical thrombectomy (MT) outcomes in acute ischemic stroke (AIS). Here, we integrate paired radiomic and transcriptomic profiling of AIS clots to identify Neutrophil Extracellular Trap (NET) enrichment as a predictor of first‐pass MT success. We further assess the potential to non‐invasively detect NET enrichment using pre‐thrombectomy CT imaging. Methods We performed radiomic and transcriptomic analysis of 32 stroke clots retrieved by MT (n=16 each of modified first pass mFP success and failure). Clots were segmented from pre‐MT CTA and nCCT scans and radiomic features (RFs) were extracted using pyRadiomics. Normality, equal variance, and two‐sample testing were completed to identify which RFs were significantly different between mFP outcomes. Differentially expressed genes (DEGs) were identified between transcriptomes of mFP success and failure using the criteria: logFC≥1.5 and q<0.05. A NET enrichment score was computed from expression data and correlated with RFs to identify a RF signature predictive of NET enrichment. Immunofluorescence (IF) staining was completed on retrieved clot tissue to provide ground truth labeling of NETs. Results 44 DEGs were identified between mFP outcomes. From ontology analysis, NET Formation, Neutrophil Degranulation, and the NET Signaling Pathway were among the most enriched terms in the mFP failure group, with related genes downregulated in the mFP success group. 40 RFs were significantly different between mFP outcomes. Of these, 6 were found to be correlated with and predictive of clot NET enrichment. IF quantification validated that transcriptomic NET signatures accurately reflected NET presence within clot tissues. Conclusion Our findings indicate that NET enrichment within thrombi is associated with reduced mFP success, and that radiomic features extracted from pre‐thrombectomy CT imaging can serve as non‐invasive biomarkers of clot NET content. This radiomic signature may aid in pre‐procedural decision‐making, including thrombolytic therapy planning and thrombectomy device selection. image image
Santo et al. (Sat,) studied this question.