Ryszard S Gomolka1,2, Robert M Chrzan3, Andrzej Urbanik3, Wieslaw L Nowinski4,5. 1. Faculty of Electronics and Information Technology, Warsaw University of Technology, Warsaw, Poland. rgomolka@mion.elka.pw.edu.pl. 2. Biomedical Imaging Lab, Agency for Science Technology and Research, Singapore. rgomolka@mion.elka.pw.edu.pl. 3. Department of Radiology, Jagiellonian University, The Cracow University Hospital, Kraków, Poland. 4. Department of Radiology, University of Washington, University District Building, Seattle, WA. 5. John Paul II Center for Virtual Anatomy and Surgical Simulation, Cardinal Stefan Wyszyński University, Warsaw, Poland.
Abstract
PURPOSE: Because clinical evaluation of noncontrast computed tomography (CT) has a poor sensitivity in the evaluation of acute ischemic stroke, computer-aided diagnosis may be able to facilitate the performance. Recently, we introduced a computational method for the detection and localization of visible infarcts. Herein, we aimed to evaluate and extend a previous method, the Stroke Imaging Marker (SIM), to localize nonvisible hyperacute ischemia. MATERIALS AND METHODS: On the basis of the SIM and its components-the ratio of percentile differences in subranges of Hounsfield Unit (HU) distribution (P-ratio), ratio of voxels count in ranges of brain CT intensity, median HU attenuation value-the infarct localization was performed in 140 early and follow-up scans of 70 patients. In none of the early scans was the infarct visible to a radiologist or an experienced stroke neuroradiologist. The infarcted hemisphere detection rate (HDR) and sensitivity of infarct localization were measured by overlapping the region of detected tissue in the initial scan, with the gold standard set for the fully visible stroke in the follow-up scan. RESULTS: The best performance of the algorithm was found for the P-ratio including seven percentile subranges within the range of 35th-75th percentile. The modified SIM provided a 76% ischemic HDR and 54% sensitivity in spatial localization of hyperacute ischemia (68% among properly detected infarct sides). CONCLUSION: The improved SIM is a dedicated and potentially useful tool for hyperacute nonvisible brain infarct detection from CT scans and may contribute to reduction of image-to-needle time in patients eligible for revascularization therapy.
PURPOSE: Because clinical evaluation of noncontrast computed tomography (CT) has a poor sensitivity in the evaluation of acute ischemic stroke, computer-aided diagnosis may be able to facilitate the performance. Recently, we introduced a computational method for the detection and localization of visible infarcts. Herein, we aimed to evaluate and extend a previous method, the Stroke Imaging Marker (SIM), to localize nonvisible hyperacute ischemia. MATERIALS AND METHODS: On the basis of the SIM and its components-the ratio of percentile differences in subranges of Hounsfield Unit (HU) distribution (P-ratio), ratio of voxels count in ranges of brain CT intensity, median HU attenuation value-the infarct localization was performed in 140 early and follow-up scans of 70 patients. In none of the early scans was the infarct visible to a radiologist or an experienced stroke neuroradiologist. The infarcted hemisphere detection rate (HDR) and sensitivity of infarct localization were measured by overlapping the region of detected tissue in the initial scan, with the gold standard set for the fully visible stroke in the follow-up scan. RESULTS: The best performance of the algorithm was found for the P-ratio including seven percentile subranges within the range of 35th-75th percentile. The modified SIM provided a 76% ischemic HDR and 54% sensitivity in spatial localization of hyperacute ischemia (68% among properly detected infarct sides). CONCLUSION: The improved SIM is a dedicated and potentially useful tool for hyperacute nonvisible brain infarct detection from CT scans and may contribute to reduction of image-to-needle time in patients eligible for revascularization therapy.