Louis Lassalle1, Guillaume Turc1, Marie Tisserand1, Sylvain Charron1, Pauline Roca1, Stephanie Lion1, Laurence Legrand1, Myriam Edjlali1, Olivier Naggara1, Jean-François Meder1, Jean-Louis Mas1, Jean-Claude Baron1, Catherine Oppenheim2. 1. From the Departments of Radiology (L. Lassalle, M.T., S.C., P.R., S.L., L. Legrand, M.E., O.N., J.-F.M., C.O.), and Neurology (G.T., J.-L.M., J.-C.B.), Université Paris Descartes Sorbonne Paris Cité, Centre de Psychiatrie et Neurosciences, INSERM S894, DHU Neurovasc, Centre Hospitalier Sainte-Anne, Paris, France. 2. From the Departments of Radiology (L. Lassalle, M.T., S.C., P.R., S.L., L. Legrand, M.E., O.N., J.-F.M., C.O.), and Neurology (G.T., J.-L.M., J.-C.B.), Université Paris Descartes Sorbonne Paris Cité, Centre de Psychiatrie et Neurosciences, INSERM S894, DHU Neurovasc, Centre Hospitalier Sainte-Anne, Paris, France. c.oppenheim@ch-sainte-anne.fr.
Abstract
BACKGROUND AND PURPOSE: Rapid and reliable assessment of the perfusion-weighted imaging (PWI)/diffusion-weighted imaging (DWI) mismatch is required to promote its wider application in both acute stroke clinical routine and trials. We tested whether an evaluation based on the Alberta Stroke Program Early CT Score (ASPECTS) reliably identifies the PWI/DWI mismatch. METHODS: A total of 232 consecutive patients with acute middle cerebral artery stroke who underwent pretreatment magnetic resonance imaging (PWI and DWI) were retrospectively evaluated. PWI-ASPECTS and DWI-ASPECTS were determined blind from manually segmented PWI and DWI volumes. Mismatch-ASPECTS was defined as the difference between PWI-ASPECTS and DWI-ASPECTS (a high score indicates a large mismatch). We determined the mismatch-ASPECTS cutoff that best identified the volumetric mismatch, defined as VolumeTmax>6s/VolumeDWI≥1.8, a volume difference≥15 mL, and a VolumeDWI<70 mL. RESULTS: Inter-reader agreement was almost perfect for PWI-ASPECTS (κ=0.95 [95% confidence interval, 0.90-1]), and DWI-ASPECTS (κ=0.96 [95% confidence interval, 0.91-1]). There were strong negative correlations between volumetric and ASPECTS-based assessments of DWI lesions (ρ=-0.84, P<0.01) and PWI lesions (ρ=-0.90, P<0.01). Receiver operating characteristic curve analysis showed that a mismatch-ASPECTS ≥2 best identified a volumetric mismatch, with a sensitivity of 0.93 (95% confidence interval, 0.89-0.98) and a specificity of 0.82 (95% confidence interval, 0.74-0.89). CONCLUSIONS: The mismatch-ASPECTS method can detect a true mismatch in patients with acute middle cerebral artery stroke. It could be used for rapid screening of patients with eligible mismatch, in centers not equipped with ultrafast postprocessing software.
BACKGROUND AND PURPOSE: Rapid and reliable assessment of the perfusion-weighted imaging (PWI)/diffusion-weighted imaging (DWI) mismatch is required to promote its wider application in both acute stroke clinical routine and trials. We tested whether an evaluation based on the Alberta Stroke Program Early CT Score (ASPECTS) reliably identifies the PWI/DWI mismatch. METHODS: A total of 232 consecutive patients with acute middle cerebral artery stroke who underwent pretreatment magnetic resonance imaging (PWI and DWI) were retrospectively evaluated. PWI-ASPECTS and DWI-ASPECTS were determined blind from manually segmented PWI and DWI volumes. Mismatch-ASPECTS was defined as the difference between PWI-ASPECTS and DWI-ASPECTS (a high score indicates a large mismatch). We determined the mismatch-ASPECTS cutoff that best identified the volumetric mismatch, defined as VolumeTmax>6s/VolumeDWI≥1.8, a volume difference≥15 mL, and a VolumeDWI<70 mL. RESULTS: Inter-reader agreement was almost perfect for PWI-ASPECTS (κ=0.95 [95% confidence interval, 0.90-1]), and DWI-ASPECTS (κ=0.96 [95% confidence interval, 0.91-1]). There were strong negative correlations between volumetric and ASPECTS-based assessments of DWI lesions (ρ=-0.84, P<0.01) and PWI lesions (ρ=-0.90, P<0.01). Receiver operating characteristic curve analysis showed that a mismatch-ASPECTS ≥2 best identified a volumetric mismatch, with a sensitivity of 0.93 (95% confidence interval, 0.89-0.98) and a specificity of 0.82 (95% confidence interval, 0.74-0.89). CONCLUSIONS: The mismatch-ASPECTS method can detect a true mismatch in patients with acute middle cerebral artery stroke. It could be used for rapid screening of patients with eligible mismatch, in centers not equipped with ultrafast postprocessing software.