• Kaixi Xu, Baodong Gu, Taosheng Zuo, Xingru Xu, Yu-Chen Chen, Xindao Yin, and Guangkui Feng.
• Department of Radiology.
• Medicine (Baltimore). 2020 Dec 11; 99 (50): e23490.

AbstractThis study aimed to quantitatively assess the consistency and correlation between perfusion weighted imaging (PWI)/ diffusion weighted imaging (DWI) Alberta Stroke Program Early CT Score (ASPECTS) mismatch and PWI/DWI mismatch.Sixty-eight acute ischemic stroke with middle cerebral artery occlusion who underwent magnetic resonance imaging before thrombectomy were eligible. DWI volume, PWI volume and PWI-DWI mismatch were measured. DWI-, PWI-, PWI-DWI ASPECTS were evaluated. Statistical analysis was performed to compare the correlation between volume and ASPECTS of DWI-, PWI- and PWI-DWI mismatch. Receiver operating characteristic curve analysis was used to assess the predictive value of the PWI-DWI ASPECTS mismatch for the occurrence of PWI-DWI mismatch in acute ischemic stroke patients with middle cerebral artery occlusion.Of 68 patients, the DWI volume, PWI volume and PWI-DWI mismatch volume were (27.76 ± 17.53) mL, (167.09 ± 59.64) mL and (139.33 ± 58.18) mL respectively. DWI-ASPECTS was 6.75 ± 1.90 with the interobserver agreement was κ=0.98 (95% CI, 0.95-0.99); PWI-ASPECTS was 3.09 ± 2.11 with the interobserver agreement was κ=0.95 (95% CI, 0.91-0.99); PWI-DWI ASPECTS mismatch was 6.75 ± 1.90. Spearman's rank correlation analysis revealed that PWI-DWI mismatch volume was negatively correlated with PWI-DWI ASPECTS mismatch (r = -0.802; P = .000). Receiver operating characteristic analysis showed that when the PWI-DWI ASPECTS mismatch cut point was ≥ 2, the under curve of PWI-DWI ASPECTS mismatch for predicting PWI-DWI mismatch was 0.954 (95%CI, 0.911-0.998), with the sensitivity and specificity were 84.00% and 100% respectively.PWI-DWI ASPECTS mismatch may represent a convenient surrogate for penumbra in clinical trials.

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