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

Kerleroux, Basile; Benzakoun, Joseph; Janot, Kévin; Dargazanli, Cyril; Eraya, Dimitri Daly; Ben Hassen, Wagih; Zhu, François; Gory, Benjamin; Jean-Francois, Hak; Perot, Charline; Detraz, Lili; Bourcier, Romain; Aymeric, Rouchaud; Forestier, Géraud; Marnat, Gaultier; Gariel, Florent; Mordasini, Pasquale; Seners, Pierre; Turc, Guillaume; Kaesmacher, Johannes; ... (2021). Relevance of Brain Regions' Eloquence Assessment in Patients With a Large Ischemic Core Treated With Mechanical Thrombectomy. Neurology, 97(20), e1975-e1985. American Academy of Neurology 10.1212/WNL.0000000000012863

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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.

Interest & Impact

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5 Citations in Web of Science ®
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