Relevance of Brain Regions' Eloquence Assessment in Patients With a Large Ischemic Core Treated With Mechanical Thrombectomy.

医学 改良兰金量表 冲程(发动机) 芯(光纤) 磁共振弥散成像 内科学 心脏病学 灌注扫描 磁共振成像
作者
Basile Kerleroux,Joseph Benzakoun,Kevin Janot,Cyril Dargazanli,Dimitri Daly Eraya,Wagih Ben Hassen,François Zhu,Benjamin Gory,Jean-François Hak,Charline Perot,Lili Detraz,Romain Bourcier,Rouchaud Aymeric,Géraud Forestier,Gaultier Marnat,Florent Gariel,Pasquale Mordasini,Pierre Seners,Guillaume Turc,Johannes Kaesmacher,Catherine Oppenheim,Olivier Naggara,Gregoire Boulouis
出处
期刊:Neurology [Ovid Technologies (Wolters Kluwer)]
卷期号:97 (20) 被引量:1
标识
DOI:10.1212/wnl.0000000000012863
摘要

Objective Individualized patient selection for mechanical thrombectomy (MT) in patients with acute ischemic stroke (AIS) and large ischemic core (LIC) at baseline is an unmet need. We tested the hypothesis, that assessing the functional relevance of both the infarcted and hypo-perfused brain tissue, would improve the selection framework of patients with LIC for MT. Methods Multicenter, retrospective, study of adult with LIC (ischemic core volume > 70ml on MR-DWI), with MRI perfusion, treated with MT or best medical management (BMM). Primary outcome was 3-month modified-Rankin-Scale (mRS), favourable if 0-3. Global and regional-eloquence-based core-perfusion mismatch ratios were derived. The predictive accuracy for clinical outcome of eloquent regions involvement was compared in multivariable and bootstrap-random-forest models. Results A total of 138 patients with baseline LIC were included (MT n=96 or BMM n=42; mean age±SD, 72.4±14.4years; 34.1% females; mRS=0-3: 45.1%). Mean core and critically-hypo-perfused volume were 100.4ml±36.3ml and 157.6±56.2ml respectively and did not differ between groups. Models considering the functional relevance of the infarct location showed a better accuracy for the prediction of mRS=0-3 with a c-Statistic of 0.76 and 0.83 for logistic regression model and bootstrap-random-forest testing sets respectively. In these models, the interaction between treatment effect of MT and the mismatch was significant (p=0.04). In comparison in the logistic regression model disregarding functional eloquence the c-Statistic was 0.67 and the interaction between MT and the mismatch was insignificant. Conclusion Considering functional eloquence of hypo-perfused tissue in patients with a large infarct core at baseline allows for a more precise estimation of treatment expected benefit.
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