Kerleroux Basile, Benzakoun Joseph, Janot Kévin, Dargazanli Cyril, Eraya Dimitri Daly, Ben Hassen Wagih, Zhu François, Gory Benjamin, Hak Jean-Francois, Perot Charline, Detraz Lili, Bourcier Romain, Aymeric Rouchaud, Forestier Géraud, Marnat Gaultier, Gariel Florent, Mordasini Pasquale, Seners Pierre, Turc Guillaume, Kaesmacher Johannes, Oppenheim Catherine, Naggara Olivier, Boulouis Gregoire
From INSERM U1266 (B.K., J.B., W.B.H., C.O., O.N.), Institut of Psychiatry and Neuroscience (IPNP), UMR_S1266, INSERM, Université de Paris, GHU Paris Psychiatrie et Neurosciences, Site Sainte-Anne; Diagnostic and Therapeutic Neuroradiology (K.J., G.B.), CHRU de Tours; Department of Interventional Neuroradiology (C.D., D.D.E.), University Hospital Center of Montpellier, Gui de Chauliac Hospital; Department of Diagnostic and Therapeutic Neuroradiology, CHRU-Nancy (F.Z., B.G.), IADI, INSERM U1254 (F.Z., B.G.), and ADI U1254 (F.Z., G.B.) Université de Lorraine, Nancy; Department of Diagnostic and Interventional Neuroradiology (J.-F.H.) and Neurology Department (C.P.), APHM, Cedex, Timone Hospital, Aix Marseille University; Department of Diagnostic and Interventional Neuroradiology (L.D., R.B.), Guillaume et René Laennec University Hospital, Nantes; Department of Interventional Neuroradiology (R.A., G.F.), Dupuytren University Hospital, Limoges; Department of Diagnostic and Interventional Neuroradiology (G.M., F.G.), Pellegrin Hospital-University Hospital of Bordeaux, France; Institute of Diagnostic, Interventional and Pediatric Radiology and Institute of Diagnostic and Interventional Neuroradiology (P.M., J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland; Neurology Department (P.S.), Fondation Rothschild Hospital, Paris; Neurology Department (G.T.), GHU Paris Psychiatrie et Neurosciences, Université de Paris, INSERM U1266, FHU NeuroVasc; and Neuroradiology Department (G.B.), Université de Paris, des Neurosciences Psychiatrie de Paris, France.
Neurology. 2021 Nov 16;97(20):e1975-e1985. doi: 10.1212/WNL.0000000000012863. Epub 2021 Oct 14.
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 infarcted and hypoperfused brain tissue would improve the selection framework of patients with LIC for MT.
We performed a multicenter, retrospective study of adults with LIC (ischemic core volume >70 mL on MRI diffusion-weighted imaging) with MRI perfusion treated with MT or best medical management (BMM). Primary outcome was 3-month modified Rankin Scale (mRS), favorable 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.
A total of 138 patients with baseline LIC were included (MT n = 96 or BMM n = 42; mean age ± SD, 72.4 ± 14.4 years; 34.1% female; mRS 0-3: 45.1%). Mean core and critically hypoperfused volume were 100.4 mL ± 36.3 mL and 157.6 ± 56.2 mL, 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 ( = 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.
Considering functional eloquence of hypoperfused tissue in patients with a large infarct core at baseline allows for a more precise estimation of treatment expected benefit.
This study provides Class II evidence that, in patients with AIS and LIC, considering the functional eloquence of the infarct location improves prediction of disability status at 3 months.
对于急性缺血性卒中（AIS）且基线存在大面积缺血半暗带（LIC）的患者，进行机械取栓（MT）的个体化患者选择是一项尚未满足的需求。我们检验了这样一个假设，即评估梗死脑组织和灌注不足脑组织的功能相关性将改善LIC患者MT的选择框架。
我们对接受MT或最佳药物治疗（BMM）的LIC成人患者（MRI扩散加权成像显示缺血核心体积>70 mL）进行了一项多中心回顾性研究，并进行了MRI灌注检查。主要结局是3个月改良Rankin量表（mRS）评分，0至3分为预后良好。得出基于全脑和局部语言区的核心灌注不匹配率。在多变量和自助随机森林模型中比较了语言区受累对临床结局的预测准确性。
共纳入138例基线存在LIC的患者（MT组n = 96或BMM组n = 42；平均年龄±标准差，72.4±14.4岁；女性占34.1%；mRS 0至3分：45.1%）。平均核心体积和严重灌注不足体积分别为100.4 mL±36.3 mL和157.6±56.2 mL，两组之间无差异。考虑梗死部位功能相关性的模型对mRS 0至3分的预测准确性更高，逻辑回归模型和自助随机森林测试集的c统计量分别为0.76和0.83。在这些模型中，MT治疗效果与不匹配之间的相互作用具有显著性（P = 0.04）。相比之下，在不考虑功能语言区的逻辑回归模型中，c统计量为0.67，MT与不匹配之间的相互作用无显著性。
考虑基线存在大面积梗死核心患者灌注不足组织的功能语言区，能够更精确地估计预期治疗获益。
本研究提供了II级证据，即在AIS和LIC患者中，考虑梗死部位的功能语言区可改善对3个月时残疾状态的预测。
