Abstract WMP80: Multimodal CT Imaging Of Ischemic Stroke Thrombi Identifies Scale-Invariant Radiomic Features

Background: Paired analysis of ischemic stroke clot histology and pre-treatment CT imaging could identify digital indicators of treatment outcome or stroke etiology. Yet, differences in scale limit our ability to interpret the biology of the clot from pre-treatment images. Hypothesis: Radiomic analysis of resected clots on microCT has the potential to identify important, biologically-interpretable features that are correlated among pre-treatment imaging modalities (CTA, nCCT) and post-treatment histopathology. Methods: We performed multimodal CT imaging of 10 stroke clots retrieved by mechanical thrombectomy (example in top of Figure). Clots were manually segmented from co-registered, pre-treatment CTA and nCCT images. For the same cases, portions of resected clots were stained with iodine, imaged on a ScanCo microCT 100 (4.9 μm resolution), and segmented using adaptive intensity thresholding. Radiomic texture features ( n =93 for each modality, 279 total) were extracted from the images using PyRadiomics. Pearson correlation analysis was used to test associations between CTA (or nCCT) and microCT radiomics. Statistical significance was considered at R ≥0.7 and q Results: 18 features were significantly correlated between CTA and microCT, and 5 features were significantly correlated between nCCT and microCT (bottom of Figure). Cluster Prominence ( R =0.96, q R =0.92, q R =0.90, q R =0.90, q Conclusion: Scale-invariant radiomic features can help bridge the gap between pre-treatment imaging and clot pathobiology.