CT-Based Diagnosis of Diffuse Coronary Artery Disease

基于 CT 的弥漫性冠状动脉疾病诊断

基本信息

批准号：
8274323
负责人：
GHASSAN S KASSAB
金额：
$ 40.91万
依托单位：
INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-08-01 至 2014-05-31
项目状态：
已结题

项目摘要

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.

描述（由申请人提供）：动脉粥样硬化仍然是美国发病和死亡的主要原因。弥漫性冠状动脉疾病 (DCAD) 是动脉粥样硬化的一种常见形式，由于管腔横截面积 (CSA) 广泛分布，因此诊断特别困难。沿多条血管小于正常值。通常，即使是轻度节段狭窄的患者，管腔 CSA 也会普遍减少 30-50%。尽管血管造影一直是定义冠状动脉局灶性狭窄的“金标准”，但其诊断 DCAD 的可行性仍然值得怀疑。因此，临床迫切需要诊断 DCAD 的新策略。该提案的总体目标是使用可转化为患者的冠状动脉非侵入性成像来开发诊断 DCAD 的新指标。诊断矩阵将在 DCAD 猪动脉粥样硬化模型的研究中得到验证。中心假设是，人类冠状动脉树的设计遵循最小能量原则，从而产生一组缩放定律；即直径、长度、体积和流量之间的幂律关系。另一个假设是缩放定律可以用作 DCAD 的敏感度量。缩放定律提供了“正常”脉管系统的特征，并且与这些定律的偏差可用于量化 DCAD 的范围。我们独特的致动脉粥样硬化大型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）开发一种经过验证的分割算法，用于从 CT 图像中提取形态测量数据（直径和长度）； 2) 使用目标 1 中的 CT 图像获得的数据，基于形态测量缩放法则，确定动脉粥样硬化 DCAD 猪模型中的 DCAD 诊断指标； 3) 使用体内 IVUS 和死后心脏的组织病理学来验证目标 2 中预测的 DCAD 指标； 4) 在医学上明确定义的正常人和 DCAD 患者的回顾性队列中使用经过验证的 DCAD 指数。该提案的贡献将是对常规成像中可见的心外膜冠状动脉树进行综合分析，以诊断 DCAD。公共健康相关性：动脉粥样硬化仍然是美国发病和死亡的主要原因。弥漫性冠状动脉疾病 (DCAD) 是动脉粥样硬化的一种常见形式，诊断起来特别困难，因为管腔横截面积沿多个方向普遍小于正常横截面积。船只。该提案的贡献是对常规成像中可见的心外膜冠状动脉树进行综合分析，以诊断 DCAD。