Atherosclerosis remains the major cause of morbidity and mortality in the U.S. Diffuse Coronary Artery Disease (DCAD), a common form of atherosclerosis, is especially difficult to diagnose because the lumen cross- sectional area (CSA) is diffusely smaller than the normal along multiple vessels. Typically, for patients with even mild segmental stenosis, lumen CSA is diffusely reduced by 30-50%. Whereas angiography has been the "gold standard" in the definition of focal stenosis of coronary artery, its viability to diagnose DCAD remains questionable. Hence, there is a significant clinical need for novel strategy to diagnose DCAD. The general objective of this proposal is to develop novel indices for diagnosis of DCAD using non-invasive imaging of the coronary arteries that are translatable to the patient. The matrices of diagnosis will be validated in studies of an atherosclerotic porcine model with DCAD. The central hypothesis is that the design of the human coronary arterial tree obeys a principle of minimum energy which results in a set of scaling laws;i.e., power-law relations between diameters, lengths, volumes and flows. An additional hypothesis is that the scaling laws can be used as sensitive measures of DCAD. The scaling laws provide the signature of "normal" vasculature and deviations from these laws can be used to quantify the extent of DCAD. Our unique atherogenic large animal model and computerized tomography (CT) images of normal and disease patients along with our quantitative approach uniquely position us to undertake the proposed research. To achieve this objective, we set the following four Specific Aims: 1) To develop a validated segmentation algorithm for extraction of morphometric data (diameters and lengths) from CT images;2) To determine diagnostic indices of DCAD in an atherosclerotic DCAD porcine model using data obtained from CT images in Aim 1 based on morphometric scaling laws;3) To validate the indices of DCAD predicted in Aim 2 using IVUS in vivo and histopathology in postmortem hearts;and 4) To use the validated indices of DCAD in a retrospective cohort of medically well-defined normal and DCAD patients. The contribution of this proposal will be to provide an integrated analysis of the epicardial coronary artery tree visible in routine imaging to allow diagnosis of DCAD.
Atherosclerosis remains the major cause of morbidity and mortality in the U.S. Diffuse Coronary Artery Disease (DCAD), a common form of atherosclerosis, is especially difficult to diagnose because the lumen cross-sectional area is diffusely smaller than the normal along multiple vessels. The contribution of this proposal is to provide an integrated analysis of the epicardial coronary artery tree visible in routine imaging to allow diagnosis of DCAD.
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