The combination of baseline magnetic resonance perfusion-weighted imaging-derived tissue volume with severely prolonged arterial-tissue delay and diffusion-weighted imaging lesion volume is predictive of MCA-M1 recanalization in patients treated with endovascular thrombectomy

摘要

Introduction: Indices of collateral flow deficit derived from MR perfusion imaging that are predictive of MCA-M1 recanalization after intravenous thrombolysis have been recently reported. Our objective was to test the performance of such MRI-derived collateral flow indices for prediction of recanalization after endovascular thrombectomy. Methods: Fifty-seven patients with MCA-M1 occlusion evaluated with multimodal MRI prior to thrombectomy were included. Bayesian processing allowed quantification of collateral perfusion indices like the volume of tissue with severely prolonged arterial-tissue delay (>6 s) (VolATD6). Baseline DWI lesion volume was also measured. Correlations with angiographic collateral flow grading and post-thrombectomy recanalization were assessed. Results: VolATD6 < 27 ml or DWI lesion volume <15 ml provide the most accurate diagnosis of excellent collateral supply (p < 0.0001). The combination of VolATD6 > 27 ml and DWI lesion volume >15 ml significantly discriminates recanalizers versus nonrecanalizers (whole cohort, p = 0.032; MERCI cohort (n = 50), p = 0.024). When both criteria are positive, 76.2 % of the patients treated with the MERCI retriever do not fully recanalize (p = 0.024). In multivariate analysis, the aforementioned combined criterion and the angiographic collateral grade are the only independent predictors of recanalization with the MERCI retriever (p = 0.015 and 0.029, respectively). Conclusion: Bayesian arterial-tissue delay maps and DWI maps provide a non-invasive assessment of the degree of collateral flow and a combined index that is predictive of MCA-M1 recanalization after endovascular thrombectomy. Further studies are needed to evaluate the accuracy of this index in patients treated with novel stent retriever devices.