CT-Based Diagnosis of Diffuse Coronary Artery Disease

描述（由申请人提供）：动脉粥样硬化仍然是美国发病率和死亡率的主要原因，弥漫性冠状动脉疾病（DCAD）是一种常见的动脉粥样硬化，尤其难以诊断，因为管腔横截面积（CSA）沿多根血管弥漫性小于正常。通常，即使是轻度节段性狭窄的患者，管腔CSA弥漫性降低30-50%。尽管血管造影一直是冠状动脉局灶性狭窄定义的“金标准”，但其诊断DCAD的可行性仍值得怀疑。因此，临床上迫切需要新的诊断策略。本提案的总体目标是利用冠状动脉的非侵入性成像开发可翻译为患者的DCAD诊断的新指标。诊断矩阵将在动脉粥样硬化猪DCAD模型的研究中得到验证。中心假设是人体冠状动脉树的设计遵循最小能量原则，这导致了一组标度定律；即直径、长度、体积和流量之间的幂律关系。另一个假设是，标度定律可以作为DCAD的敏感度量。标度定律提供了“正常”脉管系统的标志，偏离这些定律可用于量化DCAD的程度。我们独特的动脉粥样硬化大动物模型和正常和疾病患者的计算机断层扫描（CT）图像以及我们的定量方法使我们能够进行拟议的研究。为了实现这一目标，我们设定了以下四个具体目标：1)开发一种有效的分割算法，用于从CT图像中提取形态测量数据（直径和长度）；2)利用Aim 1中CT图像数据，基于形态计量学标度法确定动脉粥样硬化型DCAD猪模型的DCAD诊断指标；3)通过体内IVUS和死后心脏组织病理学验证Aim 2预测的DCAD指标；4)在医学上定义明确的正常和DCAD患者的回顾性队列中使用经验证的DCAD指标。本建议的贡献将是提供常规成像中可见的心外膜冠状动脉树的综合分析，以允许诊断DCAD。公共卫生相关性：动脉粥样硬化仍然是美国发病率和死亡率的主要原因。弥漫性冠状动脉疾病（DCAD）是一种常见的动脉粥样硬化，尤其难以诊断，因为管腔横截面积沿多根血管弥漫性小于正常。本建议的贡献是提供常规影像学可见的心外膜冠状动脉树的综合分析，以允许诊断DCAD。

DESCRIPTION (provided by applicant): 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. PUBLIC HEALTH RELEVANCE: 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.