Location-weighted versus Volume-weighted Mismatch at MRI for Response to Mechanical Thrombectomy in Acute Stroke. Radiology Fukutomi, H., Yamamoto, T., Sibon, I., Christensen, S., Raposo, N., Marnat, G., Albucher, J., Olindo, S., Calviere, L., Sagnier, S., Viguier, A., Renou, P., Guenego, A., Poli, M., Darcourt, J., Debruxelles, S., Drif, A., Thalamas, C., Sommet, A., Rousseau, V., Mazighi, M., Bonneville, F., Albers, G. W., Cognard, C., Dousset, V., Olivot, J. M., Tourdias, T., BBS and FRAME investigators, Fontaine, L., Chollet, F., Barbieux, M., Michelozzi, C., Tall, P., Januel, A., Caparros, F., Pouzet, B., Calvas, F., Galitzki, M., Rouanet, F., Ledure, S., Menegon, P., Berge, J., Barreau, X., Gariel, F., Asselineau, J., Perez, P., Mlynash, M. 2022: 220080

Abstract

Background A target mismatch profile can identify good clinical response to recanalization after acute ischemic stroke, but does not consider region specificities. Purpose To test whether location-weighted infarction core and mismatch, determined from diffusion and perfusion MRI performed in patients with acute stroke, could improve prediction of good clinical response to mechanical thrombectomy compared with a target mismatch profile. Materials and Methods In this secondary analysis, two prospectively collected independent stroke data sets (2012-2015 and 2017-2019) were analyzed. From the brain before stroke (BBS) study data (data set 1), an eloquent map was computed through voxel-wise associations between the infarction core (based on diffusion MRI on days 1-3 following stroke) and National Institutes of Health Stroke Scale (NIHSS) score. The French acute multimodal imaging to select patients for mechanical thrombectomy (FRAME) data (data set 2) consisted of large vessel occlusion-related acute ischemic stroke successfully recanalized. From acute MRI studies (performed on arrival, prior to thrombectomy) in data set 2, target mismatch and eloquent (vs noneloquent) infarction core and mismatch were computed from the intersection of diffusion- and perfusion-detected lesions with the coregistered eloquent map. Associations of these imaging metrics with early neurologic improvement were tested in multivariable regression models, and areas under the receiver operating characteristic curve (AUCs) were compared. Results Data sets 1 and 2 included 321 (median age, 69 years [IQR, 58-80 years]; 207 men) and 173 (median age, 74 years [IQR, 65-82 years]; 90 women) patients, respectively. Eloquent mismatch was positively and independently associated with good clinical response (odds ratio [OR], 1.14; 95% CI: 1.02, 1.27; P = .02) and eloquent infarction core was negatively associated with good response (OR, 0.85; 95% CI: 0.77, 0.95; P = .004), while noneloquent mismatch was not associated with good response (OR, 1.03; 95% CI: 0.98, 1.07; P = .20). Moreover, adding eloquent metrics improved the prediction accuracy (AUC, 0.73; 95% CI: 0.65, 0.81) compared with clinical variables alone (AUC, 0.65; 95% CI: 0.56, 0.73; P = .01) or a target mismatch profile (AUC, 0.67; 95% CI: 0.59, 0.76; P = .03). Conclusion Location-weighted infarction core and mismatch on diffusion and perfusion MRI scans improved the identification of patients with acute stroke who would benefit from mechanical thrombectomy compared with the volume-based target mismatch profile. Clinical trial registration no. NCT03045146 © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Nael in this issue.

View details for DOI 10.1148/radiol.220080

View details for PubMedID 36194114