Nika Guberina1, U Dietrich2, A Radbruch2, J Goebel2, C Deuschl2, A Ringelstein2,3, M Köhrmann4, C Kleinschnitz4, M Forsting2, C Mönninghoff2. 1. Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Hufelandstraße 55, 45147, Essen, Germany. nika.guberina@uk-essen.de. 2. Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Hufelandstraße 55, 45147, Essen, Germany. 3. Department of Radiology and Neuroradiology, Mariahilf Mönchengladbach, Mönchengladbach, Germany. 4. Clinic for Neurology, University Hospital Essen, Essen, Germany.
Abstract
PURPOSE: New software solutions emerged to support radiologists in image interpretation in acute ischemic stroke. This study aimed to validate the performance of computer-aided assessment of the Alberta Stroke Program Early CT score (ASPECTS) for detecting signs of early infarction. METHODS: ASPECT scores were assessed in 119 CT scans of patients with acute middle cerebral artery ischemia. Patient collective was differentiated according to (I) normal brain, (II) leukoencephalopathic changes, (III) infarcts, and (IV) atypical parenchymal defects (multiple sclerosis, etc.). ASPECTS assessments were automatically provided by the software package e-ASPECTS (Brainomix®, UK) (A). Subsequently, three neuroradiologists (B), (C), and (D) examined independently 2380 brain regions. Interrater comparison was performed with the definite infarct core as reference standard after best medical care (thrombolysis and/or thrombectomy). RESULTS: Interrater comparison revealed higher correlation coefficient of (B) 0.71, (C) 0.76, and of (D) 0.80 with definite infarct core compared to (A) 0.59 for ASPECTS assessment in the acute ischemic stroke setting. While (B), (C), and (D) showed a significant correlation for individual patient groups (I), (II), (III), and (IV), except for (D) (II), (A) was not significant in patient groups with pre-existing changes (II), (III), and (IV). The following sensitivities, specificities, PPV, NPV, and accuracies given in percent were achieved: (A) 83, 57, 55, 82, and 67; (B) 74, 76, 69, 83, and 77; (C) 80.8, 85.2, 76, 84, and 80; (D) 63, 90.7, 82, 79, and 80, respectively. CONCLUSION: For ASPECTS assessment, the examined software may provide valid data in case of normal brain. It may enhance the work of neuroradiologists in clinical decision making. A final human check for plausibility is needed, particularly in patient groups with pre-existing cerebral changes.
PURPOSE: New software solutions emerged to support radiologists in image interpretation in acute ischemic stroke. This study aimed to validate the performance of computer-aided assessment of the Alberta Stroke Program Early CT score (ASPECTS) for detecting signs of early infarction. METHODS: ASPECT scores were assessed in 119 CT scans of patients with acute middle cerebral artery ischemia. Patient collective was differentiated according to (I) normal brain, (II) leukoencephalopathic changes, (III) infarcts, and (IV) atypical parenchymal defects (multiple sclerosis, etc.). ASPECTS assessments were automatically provided by the software package e-ASPECTS (Brainomix®, UK) (A). Subsequently, three neuroradiologists (B), (C), and (D) examined independently 2380 brain regions. Interrater comparison was performed with the definite infarct core as reference standard after best medical care (thrombolysis and/or thrombectomy). RESULTS: Interrater comparison revealed higher correlation coefficient of (B) 0.71, (C) 0.76, and of (D) 0.80 with definite infarct core compared to (A) 0.59 for ASPECTS assessment in the acute ischemic stroke setting. While (B), (C), and (D) showed a significant correlation for individual patient groups (I), (II), (III), and (IV), except for (D) (II), (A) was not significant in patient groups with pre-existing changes (II), (III), and (IV). The following sensitivities, specificities, PPV, NPV, and accuracies given in percent were achieved: (A) 83, 57, 55, 82, and 67; (B) 74, 76, 69, 83, and 77; (C) 80.8, 85.2, 76, 84, and 80; (D) 63, 90.7, 82, 79, and 80, respectively. CONCLUSION: For ASPECTS assessment, the examined software may provide valid data in case of normal brain. It may enhance the work of neuroradiologists in clinical decision making. A final human check for plausibility is needed, particularly in patient groups with pre-existing cerebral changes.
Entities:
Keywords:
Alberta Stroke Program Early CT score; Computed Tomography; Ischemic stroke; Machine learning techniques
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