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弥漫性冠状动脉疾病（DCAD）的主要原因（DCAD）是动脉粥样硬化的一种常见形式，很难诊断，因为腔横截面区域（CSA）比正常容器散布小于正常容器。通常，对于即使是轻度节狭窄的患者，Lumen CSA散布降低了30-50％。尽管血管造影是冠状动脉局灶性狭窄的定义的“黄金标准”，但其诊断DCAD的生存能力仍然值得怀疑。因此，对诊断DCAD的新型策略有很大的临床需求。该提案的一般目标是使用可转换为患者的冠状动脉动脉的非侵入性成像来开发用于诊断DCAD的新指数。诊断的矩阵将在使用DCAD的动脉粥样硬化猪模型的研究中进行验证。中心假设是人类冠状动脉树的设计服从最低能量的原理，从而导致一系列缩放定律。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”脉管系统的签名，与这些定律的偏差可用于量化DCAD的程度。我们独特的动脉粥样硬化大型动物模型和计算机断层扫描（CT）的正常和疾病患者的图像以及我们的定量方法独特地定位了我们进行拟议的研究。为了实现这一目标，我们设定了以下四个特定目的：1）开发一种经过验证的分割算法，用于从CT图像中提取形态计量数据（直径和长度）； 2）使用基于形态计量规律的AIM 1中从CT图像获得的数据确定DCAD在动脉粥样硬化DCAD猪模型中的DCAD诊断指数； 3）用IVUS在验尸心脏中使用IVUS和组织病理学验证AIM 2中预测的DCAD指数； 4）在回顾性的医学定义明确的正常患者和DCAD患者的回顾组中使用已验证的DCAD指数。该提案的贡献是提供对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：在美国弥漫性冠状动脉疾病（DCAD）（一种常见的动脉粥样硬化形式）中，动脉粥样硬化仍然是发病率和死亡率的主要原因。该提案的贡献是提供对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。