Automatic assessment of cardiac function from short-axis MRI: procedure and clinical evaluation |
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| Institution: | 1. Center for Medical Physics, School of Physics and Astronomy, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel;2. The Heart Institute, Sheba Medical Center, Tel Hashome, Israel;3. The Heart Institute, Rabin Medical Center, Petach Tikva, Israel;4. Elscint Ltd., Haifa, Israel;1. Department of Physics, University of the Free State, Bloemfontein ZA9300, South Africa;2. Department of Physics and Electronics, Rhodes University, Grahamstown ZA6140, South Africa;3. School of Physics, Shri Mata Vaishno Devi University, Katra 182320, Jammu Kashmir, India;1. Physical Sciences Platform, Sunnybrook Research Institute, 2075 Bayview Avenue, Room M7-510, M4N 3M5, Toronto, ON, Canada;2. Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada;3. Schulich Heart Research Program, Sunnybrook Health Sciences Centre, Toronto, ON, Canada;4. The Toronto Centre for Phenogenomics, Mount Sinai Hospital, Toronto, ON, Canada;1. Catalonian Institute for Advanced Chemistry (IQAC-CSIC), Barcelona 08034, Spain;2. Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Zaragoza 50018, Spain;3. Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland;4. Institute for Biomechanics, Eidgenössische Technische Hochschule Zürich (ETZH), Zürich 8093, Switzerland;5. Institute for Bioengineering of Catalonia (IBEC), Barcelona 08028, Spain;1. University Paris-Sud CNRS, Université Paris-Saclay, Villejuif, France;2. Gustave Roussy, Villejuif, France;1. Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University, Baltimore, MD, USA;2. Department of Molecular and Comparative Pathobiology, The Johns Hopkins University, Baltimore, MD, USA;3. Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, 600 N. Wolfe Street, 314 Park Building, 21287, Baltimore, MD, USA |
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| Abstract: | Cardiac magnetic resonance imaging (MRI) provides a wealth of morphological and physiological information. Automatic extraction of this information is possible by implementing various image processing techniques. However, existing procedures mostly rely on extensive human interaction and are seldom evaluated on a clinical scale. In this study, a nearly automatic process that extracts physiological parameters from cardiac MR images has been both developed and clinically evaluated. Raw images were obtained in the short-axis view and acquired by a gradient-cho (GE) protocol. In images selected to be analyzed, the only manual step required is the indication of a point in the center of the left ventricle (LV). From a set of such images, the process extracts endocardial and epicardial contours and calculates left ventricular volumes, mass and ejection fraction (EF). The process implements novel approaches to image processing techniques such as thresholding and shape extraction and can be adapted to other acquisition protocols. The process has demonstrated a clear potential for accurate extraction of the endocardial contour but a lower one with respect to the epicardial contour as a result of the low contrast between myocardium and some surrounding tissues, generated by the gradient-echo protocol. The ability of the process to asses physiological parameters has been subjected to a systematic clinical evaluation, which compared parameters, derived manually and automatically, in 10 healthy subjects and 10 patients. The evaluation has indicated that although individual volumes and mass were not accurately assessed, the automatic process has shown high potential for assessing the ejection fraction with relatively high accuracy and reliability. |
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