Abstract

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Title:: Computer-aided diagnosis system for aortic coarctation based on MRI and hemodynamic simulation

Author(s):: SHI Yubing1; 2; Israel Valverde3; Patricia V. Lawford2; D. Rodney Hose2; 1. Institute of Integrative Medicine, Shaanxi University of Chinese Medicine, Xianyang 712046, China 2. Medical Physics Group, Department of Cardiovascular Science, Faculty of Medicine, Dentistry and Health, University of Sheffield, Sheffield, UK 3. Division of Imaging Sciences and Biomedical Engineering, Kings College London, The Rayne Institute, St. Thomas Hospital, London, UK

Keywords:: Keywords: cardiocerebral vascular disease computer-aided diagnosis system magnetic resonance imaging hemodynamic calculation computer simulation

Abstract:: Abstract: Currently there is few computer-aided diagnosis system for the cardiocerebral vascular diseases. Based on the research works conducted in the EU FP7 euHeart project and taking the diagnosis of aortic coarctation as an example, a computer-aided diagnosis system for the cardiocerebral vascular diseases based on MRI and hemodynamic calculation is presented, and the structure, function and the workflow of the system are explained in details. The system uses the MRI images of the diseased vessel and the pressure waveforms measured at carotid and femoral arteries as the input, analyzes these data using the image processing module, the physiological data processing module, the computational grid generation module and the hemodynamic calculation module, and outputs the pressure gradient across the coarctation to aid the assessment of necessity for interventional surgery, besides revealing the hemodynamic characteristics including the velocity and shear stress distributions to assist the prediction of potential for mechanical damages to the endothelium and blood cells accompanying the abnormal blood flow in the diseased vessel. The developed system is preliminarily validated using a typical case as the example, and the results show that the system give accurate and reliable predictions of the disease condition. The developed system can serve as a reference in building other computer-aided diagnosis systems for the cardiocerebral vascular diseases.