Development of Image Analysis Algorithms for Computational Assessment of Cardiac Structure and Function

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Advancements in cardiac magnetic resonance (MR) imaging technologies in the past decade have enabled great potential for developing novel measurements to detect abnormalities in the structure and function of the heart. Two such advancements include acquisition of high-resolution (Hi-res) three-dimensional (3D) images with increased spatial resolution, and quantitative imaging techniques to differentiate injured (infarcted) tissue from healthy tissue in the cardiac muscle. Tissue in infarcted regions plays a central role in the mechanisms that lead to heart dysfunction and therefore, accurate and reproducible estimation of the infarct regions is paramount to the analysis of cardiac structure and function. Parallel to these developments, computational modeling of cardiac function has emerged as a promising tool to predict abnormal electrical activity of the heart. These computational models are built based on the information extracted from cardiac MR images and must incorporate accurate geometries of the ventricles and infarcted regions of the heart for accurate prediction. This presents us with an opportunity to evaluate whether incorporating Hi-res, quantitative imaging methods in building computational models, as compared to the models generated from conventional low-resolution images, will improve the sensitivity and specificity in predicting abnormal electrical activities of the heart. However, in order to extract geometric information from these 3D MR images, the development of robust, automated image analysis methods is required. The overall goal of the research program will be to address this need by developing advanced image analysis tools for the non-invasive assessment of the cardiac structure and its function. In particular, image analysis methods will be developed to align cardiac MR images to a common reference to correct for cardiac motion and extract the 3D ventricular and infarct geometry of the heart. Computational simulations of the electrical activity of the heart will then be used to evaluate efficacy of the 3D MR technique. This research program will integrate emerging advances in cardiac MR imaging and computational cardiology through novel developments in medical image analysis. The anticipated significance of this work to biomedical engineering and imaging science is twofold: engineering innovations resulting from the development of new image analysis methods for 3D MR images; and enabling our understanding of accurate methods to image the infarct structure. By accurately incorporating the infarct structure, these virtual electrophysiological models may provide a tool to non-invasively interrogate the heart without the need for invasive catheter-based methods. Although the proposed algorithms will initially be developed for cardiac MR images, they will be directly applicable to analyzing images of other imaging techniques and organs.