Department of Biomedical Engineering and Physics, Amsterdam UMC, location University of Amsterdam, Amsterdam, The Netherlands
Department of Radiology and Nuclear Medicine, Amsterdam UMC, location University of Amsterdam, Amsterdam, The Netherlands.
J Neurointerv Surg. 2023 Sep;15(e1):e60-e68. doi: 10.1136/jnis-2022-019134. Epub 2022 Jul 14.
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.
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.
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.
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.
血栓成像特征对缺血性脑卒中后治疗和临床结局的影响越来越受到关注。这些血栓特征,如大小、位置和密度,通常被分析为独立的实体。然而,已知其中一些血栓特征密切相关。多重共线性会导致预测模型不可靠。我们旨在基于大量前循环急性缺血性脑卒中患者的数据集,确定血栓成像特征的分布、相关性和聚类。
我们在 MR CLEAN 注册研究数据集内测量了血栓成像特征,包括闭塞位置、血栓距颅内颈内动脉的距离(DT)、血栓长度、密度、可透性和血栓负荷评分(CBS)。我们使用 Spearman 系数(ρ)评估了相互间的相关性,并根据 1)闭塞位置和 2)血栓长度、密度和可透性,使用无监督聚类对血栓进行分组。
我们纳入了 934 名患者,其中 22%有颈内动脉(ICA)闭塞,61%是 M1 段,16%是 M2 段,1%是其他闭塞位置。所有血栓特征均显著相关。更高的 CBS 与更长的 DT(ρ=0.67,p<0.01)强烈相关,与更短的血栓长度中度相关(ρ=-0.41,p<0.01)。在更靠近近端的闭塞位置,血栓更长、更致密、更不易通透。无监督聚类分析产生了 4 个血栓组,但组内和组间的凝聚力和区分力较弱。
血栓成像特征显著相关,在未来的预测模型研究中应考虑到强相关性。聚类分析表明,没有明显的血栓原型,新型治疗方法应考虑到这种血栓的多样性。