Julian Schröder1, Bastian Cheng2, Martin Ebinger2, Martin Köhrmann2, Ona Wu2, Dong-Wha Kang2, David S Liebeskind2, Thomas Tourdias2, Oliver C Singer2, Soren Christensen2, Bruce Campbell2, Marie Luby2, Steven Warach2, Jens Fiehler2, Jochen B Fiebach2, Christian Gerloff2, Götz Thomalla2. 1. From the Klinik und Poliklinik für Neurologie, Kopf- und Neurozentrum, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany (J.S., B. Cheng, C.G., G.T.); Centrum für Schlaganfallforschung Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany (M.E., J.B.F.); Klinik für Neurologie, Universität Erlangen-Nürnberg, Erlangen, Germany (M.K.); Department of Radiology, Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston (O.W.); Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (D.-W.K.); Department of Neurology, University of California, Los Angeles (D.S.L.); Université de Bordeaux, CHU de Bordeaux, Service de NeuroImagerie Diagnostique de Thérapeutique, Bordeaux, France (T.T.); Klinik für Neurologie, Universitätsklinikum Frankfurt, Frankfurt, Germany (O.C.S.); Department of Medicine and Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, Australia (S.C., B. Campbell); National Institute of Neurological Disorders and Stroke, Bethesda, MD (M.L.); Department of Neurology and Neurotherapeutics, Seton/UT Southwestern Clinical Research Institute of Austin, UT Southwestern Medical Center, Austin, TX (S.W.); and Klinik und Poliklinik für Neuroradiologische Diagnostik und Intervention, Unversitätsklinikum Hamburg-Eppendorf, Hamburg, Germany (J.F.). jul.schroeder@uke.de. 2. From the Klinik und Poliklinik für Neurologie, Kopf- und Neurozentrum, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany (J.S., B. Cheng, C.G., G.T.); Centrum für Schlaganfallforschung Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany (M.E., J.B.F.); Klinik für Neurologie, Universität Erlangen-Nürnberg, Erlangen, Germany (M.K.); Department of Radiology, Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston (O.W.); Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (D.-W.K.); Department of Neurology, University of California, Los Angeles (D.S.L.); Université de Bordeaux, CHU de Bordeaux, Service de NeuroImagerie Diagnostique de Thérapeutique, Bordeaux, France (T.T.); Klinik für Neurologie, Universitätsklinikum Frankfurt, Frankfurt, Germany (O.C.S.); Department of Medicine and Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, Australia (S.C., B. Campbell); National Institute of Neurological Disorders and Stroke, Bethesda, MD (M.L.); Department of Neurology and Neurotherapeutics, Seton/UT Southwestern Clinical Research Institute of Austin, UT Southwestern Medical Center, Austin, TX (S.W.); and Klinik und Poliklinik für Neuroradiologische Diagnostik und Intervention, Unversitätsklinikum Hamburg-Eppendorf, Hamburg, Germany (J.F.).
Abstract
BACKGROUND AND PURPOSE: Alberta Stroke Program Early Computed Tomographic Score (ASPECTS) has been used to estimate diffusion-weighted imaging (DWI) lesion volume in acute stroke. We aimed to assess correlations of DWI-ASPECTS with lesion volume in different middle cerebral artery (MCA) subregions and reproduce existing ASPECTS thresholds of a malignant profile defined by lesion volume ≥100 mL. METHODS: We analyzed data of patients with MCA stroke from a prospective observational study of DWI and fluid-attenuated inversion recovery in acute stroke. DWI-ASPECTS and lesion volume were calculated. The population was divided into subgroups based on lesion localization (superficial MCA territory, deep MCA territory, or both). Correlation of ASPECTS and infarct volume was calculated, and receiver-operating characteristics curve analysis was performed to identify the optimal ASPECTS threshold for ≥100-mL lesion volume. RESULTS: A total of 496 patients were included. There was a significant negative correlation between ASPECTS and DWI lesion volume (r=-0.78; P<0.0001). With regards to lesion localization, correlation was weaker in deep MCA region (r=-0.19; P=0.038) when compared with superficial (r=-0.72; P<0.001) or combined superficial and deep MCA lesions (r=-0.72; P<0.001). Receiver-operating characteristics analysis revealed ASPECTS≤6 as best cutoff to identify ≥100-mL DWI lesion volume; however, positive predictive value was low (0.35). CONCLUSIONS: ASPECTS has limitations when lesion location is not considered. Identification of patients with malignant profile by DWI-ASPECTS may be unreliable. ASPECTS may be a useful tool for the evaluation of noncontrast computed tomography. However, if MRI is used, ASPECTS seems dispensable because lesion volume can easily be quantified on DWI maps.
BACKGROUND AND PURPOSE:Alberta Stroke Program Early Computed Tomographic Score (ASPECTS) has been used to estimate diffusion-weighted imaging (DWI) lesion volume in acute stroke. We aimed to assess correlations of DWI-ASPECTS with lesion volume in different middle cerebral artery (MCA) subregions and reproduce existing ASPECTS thresholds of a malignant profile defined by lesion volume ≥100 mL. METHODS: We analyzed data of patients with MCA stroke from a prospective observational study of DWI and fluid-attenuated inversion recovery in acute stroke. DWI-ASPECTS and lesion volume were calculated. The population was divided into subgroups based on lesion localization (superficial MCA territory, deep MCA territory, or both). Correlation of ASPECTS and infarct volume was calculated, and receiver-operating characteristics curve analysis was performed to identify the optimal ASPECTS threshold for ≥100-mL lesion volume. RESULTS: A total of 496 patients were included. There was a significant negative correlation between ASPECTS and DWI lesion volume (r=-0.78; P<0.0001). With regards to lesion localization, correlation was weaker in deep MCA region (r=-0.19; P=0.038) when compared with superficial (r=-0.72; P<0.001) or combined superficial and deep MCA lesions (r=-0.72; P<0.001). Receiver-operating characteristics analysis revealed ASPECTS≤6 as best cutoff to identify ≥100-mL DWI lesion volume; however, positive predictive value was low (0.35). CONCLUSIONS: ASPECTS has limitations when lesion location is not considered. Identification of patients with malignant profile by DWI-ASPECTS may be unreliable. ASPECTS may be a useful tool for the evaluation of noncontrast computed tomography. However, if MRI is used, ASPECTS seems dispensable because lesion volume can easily be quantified on DWI maps.
Authors: P A Barber; M D Hill; M Eliasziw; A M Demchuk; J H W Pexman; M E Hudon; A Tomanek; R Frayne; A M Buchan Journal: J Neurol Neurosurg Psychiatry Date: 2005-11 Impact factor: 10.154
Authors: T Nezu; M Koga; K Kimura; Y Shiokawa; J Nakagawara; E Furui; H Yamagami; Y Okada; Y Hasegawa; K Kario; S Okuda; K Nishiyama; M Naganuma; K Minematsu; K Toyoda Journal: Neurology Date: 2010-08-10 Impact factor: 9.910
Authors: W Taylor Kimberly; Bruce C V Campbell; Felix C Ng; Nawaf Yassi; Gagan Sharma; Scott B Brown; Mayank Goyal; Charles B L M Majoie; Tudor G Jovin; Michael D Hill; Keith W Muir; Jeffrey L Saver; Francis Guillemin; Andrew M Demchuk; Bijoy K Menon; Luis San Roman; David S Liebeskind; Philip White; Diederik W J Dippel; Antoni Davalos; Serge Bracard; Peter J Mitchell; Michael J Wald; Stephen M Davis; Kevin N Sheth Journal: Stroke Date: 2021-08-13 Impact factor: 7.914