医学
放射科
血管造影
冲程(发动机)
计算机断层血管造影
核医学
H&E染色
相关性
病理
染色
机械工程
几何学
数学
工程类
作者
Briana A. Santo,Seyyed Mostafa Mousavi Janbeh Sarayi,Andrew D. McCall,André Monteiro,Brianna M. Donnelly,Adnan H. Siddiqui,Vincent M. Tutino
标识
DOI:10.1136/jnis-2022-019967
摘要
Background Biological interpretability of ischemic stroke clot imaging remains challenging. Objective To carry out paired CT/micro-CT imaging of ischemic stroke clots retrieved by thrombectomy with the aim of identifying interpretable image features that are correlated among pretreatment image modalities and post-treatment histopathology. Methods We performed multimodal CT imaging and histology for 10 stroke clots retrieved by mechanical thrombectomy. Clots were manually segmented from co-registered, pretreatment CT angiography (CTA) and non-contrast CT (NCCT). For the same cases, retrieved clots were iodine-stained, and imaged with a ScanCo micro-CT 100 (4.9 µm resolution). Afterwards, clots were subjected to histological processing (hematoxylin and eosin staining) and whole slide scanned (40X). Clot radiomic features (RFs) (n=93 per modality, 279 total) were extracted using PyRadiomics and histological composition was computed using Orbit Image Analysis. Correlation analysis was used to test associations between micro-CT and CTA (or NCCT) RFs as well as between RFs and histological composition. Statistical significance was considered at R≥0.65 and q<0.05. Results From paired RF correlation analysis, we identified 23 scale-invariant RFs with significant correlation between micro-CT and CTA (18), and micro-CT and NCCT (5). Correlation of unpaired RFs identified 377 positively and 36 negatively correlated RFs between micro-CT and CTA, and 168 positively and 41 negatively correlated RFs between micro-CT and NCCT. Scale-invariant RFs computed from CTA and NCCT demonstrated significant correlation with red blood cell and fibrin-platelet components, while micro-CT RFs were found to be correlated with white blood cell percent composition. Conclusion Multimodal CT, radiomic, and histological analysis of stroke clots can help to bridge the gap between pretreatment imaging and clot pathobiology.
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