BACKGROUND AND PURPOSE: Clot perviousness in acute ischemic stroke is a potential CT imaging biomarker for mechanical thrombectomy efficacy. We investigated the association among perviousness, clot cellular composition, and first-pass effect. MATERIALS AND METHODS: In 40 mechanical thrombectomy–treated cases of acute ischemic stroke, we calculated perviousness as the difference in clot density on CT angiography and noncontrast CT. We assessed the proportion of fibrin/platelet aggregates, red blood cells, and white blood cells on clot histopathology. We tested for linear correlation between histologic components and perviousness, differences in components between “high” and “low” pervious clots defined by median perviousness, and differences in perviousness/composition between cases that did and did not achieve a first-pass effect. RESULTS: Perviousness significantly positively and negatively correlated with the percentage of fibrin/platelet aggregates (P = .001) and the percentage of red blood cells (P = .001), respectively. Higher pervious clots had significantly greater fibrin/platelet aggregate content (P = .042). Cases that achieved a first-pass effect (n = 14) had lower perviousness, though not significantly (P = .055). The percentage of red blood cells was significantly higher (P = .028) and the percentage of fibrin/platelet aggregates was significantly lower (P = .016) in cases with a first-pass effect. There was no association between clot density on NCCT and clot composition or first-pass effect. Receiver operating characteristic analysis indicated that clot composition was the best predictor of first-pass effect (area under receiver operating characteristic curve: percentage of fibrin/platelet aggregates = 0.731, percentage of red blood cells = 0.706, perviousness = 0.668). CONCLUSIONS: Clot perviousness on CT is associated with a higher percentage of fibrin/platelet aggregate content. Histologic data and, to a lesser degree, perviousness may have value in predicting first-pass outcome. Imaging metrics that more strongly reflect clot biology than perviousness may be needed to predict a first-pass effect with high accuracy.

Mechanical thrombectomy (MT) for large vessel acute ischemic stroke (AIS) has enabled biologic analyses of resected clots. While clot histology has been well-studied, little is known about gene expression within the tissue, which could shed light on stroke pathophysiology. In this methodological study, we develop a pipeline for obtaining useful RNA from AIS clots. A total of 73 clot samples retrieved by MT were collected and stored in RNALater and in 10% phosphate-buffered formalin. RNA was extracted from all samples using a modified Chemagen magnetic bead extraction protocol on the PerkinElmer Chemagic 360. RNA was interrogated by UV–Vis absorption and electrophoretic quality control analysis. All samples with sufficient volume underwent traditional qPCR analysis and samples with sufficient RNA quality were subjected to next-generation RNA sequencing on the Illumina NovaSeq platform. Whole blood RNA samples from three patients were used as controls, and H&E-stained histological sections of the clots were used to assess clot cellular makeup. Isolated mRNA was eluted into a volume of 140 µL and had a concentration ranging from 0.01 ng/µL to 46 ng/µL. Most mRNA samples were partially degraded, with RNA integrity numbers ranging from 0 to 9.5. The majority of samples (71/73) underwent qPCR analysis, which showed linear relationships between the expression of three housekeeping genes (GAPDH, GPI, and HPRT1) across all samples. Of these, 48 samples were used for RNA sequencing, which had moderate quality based on MultiQC evaluation (on average, ~35 M reads were sequenced). Analysis of clot histology showed that more acellular samples yielded RNA of lower quantity and quality. We obtained useful mRNA from AIS clot samples stored in RNALater. qPCR analysis could be performed in almost all cases, while sequencing data could only be performed in approximately two-thirds of the samples. Acellular clots tended to have lower RNA quantity and quality.