Background The effects of thrombus imaging characteristics on procedural and clinical outcomes after ischemic stroke are increasingly being studied. These thrombus characteristics - for eg, size,... Show moreBackground The effects of thrombus imaging characteristics on procedural and clinical outcomes after ischemic stroke are increasingly being studied. These thrombus characteristics - for eg, size, location, and density - are commonly analyzed as separate entities. However, it is known that some of these thrombus characteristics are strongly related. Multicollinearity can lead to unreliable prediction models. We aimed to determine the distribution, correlation and clustering of thrombus imaging characteristics based on a large dataset of anterior-circulation acute ischemic stroke patients. Methods We measured thrombus imaging characteristics in the MR CLEAN Registry dataset, which included occlusion location, distance from the intracranial carotid artery to the thrombus (DT), thrombus length, density, perviousness, and clot burden score (CBS). We assessed intercorrelations with Spearman's coefficient (rho) and grouped thrombi based on 1) occlusion location and 2) thrombus length, density and perviousness using unsupervised clustering. Results We included 934 patients, of which 22% had an internal carotid artery (ICA) occlusion, 61% M1, 16% M2, and 1% another occlusion location. All thrombus characteristics were significantly correlated. Higher CBS was strongly correlated with longer DT (rho=0.67, p<0.01), and moderately correlated with shorter thrombus length (rho=-0.41, p<0.01). In more proximal occlusion locations, thrombi were significantly longer, denser, and less pervious. Unsupervised clustering analysis resulted in four thrombus groups; however, the cohesion within and distinction between the groups were weak. Conclusions Thrombus imaging characteristics are significantly intercorrelated - strong correlations should be considered in future predictive modeling studies. Clustering analysis showed there are no distinct thrombus archetypes - novel treatments should consider this thrombus variability. Show less
Venema, S.M.U.; Dankbaar, J.W.; Wolff, L.; Es, A.C.G.M. van; Sprengers, M.; Lugt, A. van der; ... ; MR CLEAN Registry Investigators 2022
Background Successful recanalization and good collateral status are associated with good clinical outcomes after endovascular treatment (EVT) for acute ischemic stroke, but the relationships among... Show moreBackground Successful recanalization and good collateral status are associated with good clinical outcomes after endovascular treatment (EVT) for acute ischemic stroke, but the relationships among them are unclear. Objective To assess if collateral status is associated with recanalization after EVT and if collateral status modifies the association between successful recanalization and functional outcome. Methods We retrospectively analyzed data from the MR CLEAN Registry, a multicenter prospective cohort study of patients with a proximal anterior occlusion who underwent EVT in the Netherlands. We determined collateral status with a previously validated four-point visual grading scale and defined successful recanalization as an extended Thrombolysis in Cerebral Infarction score >= 2B. Functional outcome was determined using the modified Rankin Scale score at 90 days. We assessed, with multivariable logistic regression models, the associations between (1) collateral status and successful recanalization, (2) successful recanalization and functional outcome, (3) collateral status and functional outcome. An interaction of collateral status and successful recanalization was assessed. Subgroup analyses were performed for patients treated with intravenous thrombolysis. Results We included 2717 patients, of whom 1898 (70%) had successful recanalization. There was no relationship between collateral status and successful recanalization (adjusted common OR (95% CI) of grades 1, 2, and 3 vs 0: 1.19 (0.82 to 1.72), 1.20 (0.83 to 1.75), and 1.10 (0.74 to 1.63), respectively). Successful recanalization (acOR (95% CI): 2.15 (1.84 to 2.52)) and better collateral grades (acOR (95% CI) of grades 1, 2, and 3 vs 0: 2.12 (1.47 to 3.05), 3.46 (2.43 to 4.92), and 4.16 (2.89 to 5.99), respectively) were both associated with a shift towards better functional outcome, without an interaction between collateral status and successful recanalization. Results were similar for the subgroup of thrombolysed patients. Conclusions Collateral status is not associated with the probability of successful recanalization after EVT and does not modify the association between successful recanalization and functional outcome. Show less
Background Machine learning algorithms hold the potential to contribute to fast and accurate detection of large vessel occlusion (LVO) in patients with suspected acute ischemic stroke. We assessed... Show moreBackground Machine learning algorithms hold the potential to contribute to fast and accurate detection of large vessel occlusion (LVO) in patients with suspected acute ischemic stroke. We assessed the diagnostic performance of an automated LVO detection algorithm on CT angiography (CTA). Methods Data from the MR CLEAN Registry and PRESTO were used including patients with and without LVO. CTA data were analyzed by the algorithm for detection and localization of LVO (intracranial internal carotid artery (ICA)/ICA terminus (ICA-T), M1, or M2). Assessments done by expert neuroradiologists were used as reference. Diagnostic performance was assessed for detection of LVO and per occlusion location by means of sensitivity, specificity, and area under the curve (AUC). Results We analyzed CTAs of 1110 patients from the MR CLEAN Registry (median age (IQR) 71 years (60-80); 584 men; 1110 with LVO) and of 646 patients from PRESTO (median age (IQR) 73 years (62-82); 358 men; 141 with and 505 without LVO). For detection of LVO, the algorithm yielded a sensitivity of 89% in the MR CLEAN Registry and a sensitivity of 72%, specificity of 78%, and AUC of 0.75 in PRESTO. Sensitivity per occlusion location was 88% for ICA/ICA-T, 94% for M1, and 72% for M2 occlusion in the MR CLEAN Registry, and 80% for ICA/ICA-T, 95% for M1, and 49% for M2 occlusion in PRESTO. Conclusion The algorithm provided a high detection rate for proximal LVO, but performance varied significantly by occlusion location. Detection of M2 occlusion needs further improvement. Show less
