Low relative diffusion weighted image signal intensity can predict good prognosis after endovascular thrombectomy in patients with acute ischemic stroke.

Kishi, Fumihisa; Nakagawa, Ichiro; Park, HunSoo; Kotsugi, Masashi; Myouchin, Kaoru; Motoyama, Yasushi; Nakase, Hiroyuki

BACKGROUND It is vital to identify a surrogate last-known-well time to perform proper endovascular thrombectomy in acute ischemic stroke; however, no established imaging biomarker can easily and quickly identify eligibility for endovascular thrombectomy and predict good clinical prognosis. OBJECTIVE To investigate whether low relative diffusion-weighted imaging (DWI) signal intensity can be used as a predictor of good clinical outcome after endovascular thrombectomy in patients with acute ischemic stroke. METHODS We retrospectively identified consecutive patients with acute ischemic stroke who were treated with endovascular thrombectomy within 24 hours of the last-known-well time and achieved successful recanalization (modified Thrombolysis in Cerebral Infarction score ≥2b). Relative DWI signal intensity was calculated as DWI signal intensity in the infarcted area divided by DWI signal intensity in the contralateral hemisphere. Good prognosis was defined as a modified Rankin Scale score of 0-2 at 90 days after stroke onset (good prognosis group). RESULTS 49 patients were included in the analysis. Relative DWI signal intensity was significantly lower in the group with good prognosis than in the those with poor prognosis (median (IQR) 1.32 (1.27-1.44) vs 1.56 (1.43-1.66); p<0.01), and the critical cut-off value for predicting good prognosis was 1.449 (area under the curve 0.78). Multiple logistic regression analysis revealed association of good prognosis after endovascular thrombectomy with low relative DWI signal intensity (OR=6.84; 95% CI 1.13 to 41.3; p=0.04). CONCLUSIONS Low relative DWI signal intensity was associated with good prognosis after endovascular thrombectomy. Its ability to predict good clinical outcome shows potential for determining patient suitability for endovascular thrombectomy.