Abstract
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, 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 (ρ) 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 (ρ=0.67, p<0.01), and moderately correlated with shorter thrombus length (ρ=-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.
| Original language | English |
|---|---|
| Pages (from-to) | E60-E68 |
| Journal | Journal of NeuroInterventional Surgery |
| Volume | 15 |
| Issue number | e1 |
| Early online date | 14 Jul 2022 |
| DOIs | |
| Publication status | Published - 1 Sept 2023 |
Bibliographical note
Funding Information:This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 777072 (INSIST project), and the AMC medical Research BV, Amsterdam UMC, location AMC, under project No 21937. The MR CLEAN registry is partially funded by unrestricted grants from the Applied Scientific Institute for Neuromodulation (Toegepast Wetenschappelijk Instituut voor Neuromodulatie), Erasmus Medical Center, Amsterdam University Medical Center and Maastricht University Medical Center. HAM reports being a co-founder and shareholder of Nicolab, a company that focuses on the use of artificial intelligence for medical image analysis. CBLMM reports grants from European Commission during the conduct of the study; grants from CVON/Dutch Heart Foundation, TWIN Foundation, Health Evaluation Netherlands, and Stryker, outside the submitted work; and shareholder of Nicolab. DWJD reports unrestricted grants from Stryker, Penumbra, Medtronic, Cerenovus, Thrombolytic Science, LLC, Dutch Heart Foundation, Brain Foundation Netherlands, The Netherlands Organization for Health Research and Development, Health Holland Top Sector Life Sciences and Health, and Thrombolytic Science, LLC for research, paid to institution. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Funding Information:
This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 777072 (INSIST project), and the AMC medical Research BV, Amsterdam UMC, location AMC, under project No 21937. The MR CLEAN Registry was partly funded by TWIN Foundation, Erasmus MC University Medical Center, Maastricht University Medical Center, and Amsterdam UMC.
Publisher Copyright:
© 2023 Journal of NeuroInterventional Surgery. All rights reserved.