TY - JOUR
T1 - Thrombus imaging characteristics within acute ischemic stroke
T2 - similarities and interdependence
AU - Arrarte Terreros, Nerea
AU - Bruggeman, Agnetha Ae
AU - Kappelhof, Manon
AU - Tolhuisen, Manon L
AU - Brouwer, Josje
AU - Hoving, Jan W
AU - Konduri, Praneeta R
AU - van Kranendonk, Katinka R
AU - Dutra, Bruna G
AU - Alves, Heitor Cbr
AU - Dippel, Diederik Wj
AU - van Zwam, Wim H
AU - Beenen, Ludo Fm
AU - Yo, Lonneke Sf
AU - van Bavel, Ed
AU - Majoie, Charles Blm
AU - Marquering, Henk A
AU - MR CLEAN Registry Investigators
N1 - 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:
© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - ATTENUATION
KW - CT
KW - CT Angiography
KW - OCCLUSION
KW - RECANALIZATION
KW - SEGMENTATION
KW - Stroke
KW - Thrombectomy
KW - Thrombolysis
KW - Ct
U2 - 10.1136/jnis-2022-019134
DO - 10.1136/jnis-2022-019134
M3 - Article
C2 - 35835463
SN - 1759-8478
VL - 15
SP - e60-e68
JO - Journal of Neurointerventional Surgery
JF - Journal of Neurointerventional Surgery
IS - e1
ER -