PDF(Pubmed)
Abstract：
(1) Background: For acute ischemic strokes caused by large vessel occlusion, manually assessed thrombus volume and perviousness have been associated with treatment outcomes. However, the manual assessment of these characteristics is time-consuming and subject to inter-observer bias. Alternatively, a recently introduced fully automated deep learning-based algorithm can be used to consistently estimate full thrombus characteristics. Here, we exploratively assess the value of these novel biomarkers in terms of their association with stroke outcomes. (2) Methods: We studied two applications of automated full thrombus characterization as follows: one in a randomized trial, MR CLEAN-NO IV (n = 314), and another in a Dutch nationwide registry, MR CLEAN Registry (n = 1839). We used an automatic pipeline to determine the thrombus volume, perviousness, density, and heterogeneity. We assessed their relationship with the functional outcome defined as the modified Rankin Scale (mRS) at 90 days and two technical success measures as follows: successful final reperfusion, which is defined as an eTICI score of 2b-3, and successful first-pass reperfusion (FPS). (3) Results: Higher perviousness was significantly related to a better mRS in both MR CLEAN-NO IV and the MR CLEAN Registry. A lower thrombus volume and lower heterogeneity were only significantly related to better mRS scores in the MR CLEAN Registry. Only lower thrombus heterogeneity was significantly related to technical success; it was significantly related to a higher chance of FPS in the MR CLEAN-NO IV trial (OR = 0.55, 95% CI: 0.31-0.98) and successful reperfusion in the MR CLEAN Registry (OR = 0.88, 95% CI: 0.78-0.99). (4) Conclusions: Thrombus characteristics derived from automatic entire thrombus segmentations are significantly related to stroke outcomes.
摘要：
（1）背景：对于大血管闭塞引起的急性缺血性中风，人工评估血栓体积和渗透性与治疗结果相关.然而,对这些特征的人工评估是耗时的，并且受到观察者之间的偏见。或者，最近推出的基于深度学习的全自动算法可用于一致地估计全部血栓特征.这里,我们探索性地评估了这些新型生物标志物与卒中结局的相关性.（2）方法：我们研究了以下两种自动化全血栓表征的应用：一项随机试验，MRCLEAN-NOIV(n=314)，另一个在荷兰全国登记处，清洁登记先生（n=1839）。我们用自动管道来确定血栓体积,渗透性，密度,和异质性。我们评估了它们与功能结局的关系，该功能结局定义为90天的改良Rankin量表（mRS）和以下两个技术成功指标：成功的最终再灌注，其定义为eTICI评分为2b-3，并且成功的首过再灌注（FPS）。（3）结果：在MRCLEAN-NOIV和MRCLEAN注册表中，较高的渗透性与较好的mRS显着相关。较低的血栓体积和较低的异质性仅与MRCLEAN注册中更好的mRS评分显着相关。只有较低的血栓异质性与技术成功显着相关；它与MRCLEAN-NOIV试验中FPS的较高机会（OR=0.55，95％CI：0.31-0.98）和MRCLEAN注册中的成功再灌注（OR=0.88，95％CI：0.78-0.99）显着相关。（4）结论：自动完整血栓分割得出的血栓特征与卒中结局显着相关。
