ANGIOGRAPHIC IMAGING OF CORONARY LESION MORPHOLOGY

冠状动脉病变形态的血管造影成像

基本信息

批准号：
2220804
负责人：
JAMES S WHITING
金额：
$ 26万
依托单位：
CEDARS-SINAI MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
1991
资助国家：
美国
起止时间：
1991-04-01 至 1995-09-29
项目状态：
已结题

项目摘要

Although more than one million coronary arteriograms are performed in the U.S. annually, the potential of the angiogram to predict risk or outcome has probably not been full realized. In the past several years, there has been evolving evidence that atherosclerotic plaque surface morphology, rather than the degree of luminal obstruction, predicts unstable ischemic syndromes. Pathologic and angioscopic studies have shown that plaque disruption (fissuring, ulceration, or hemorrhage, with or without thrombosis) is present in an overwhelming percentage of patients presenting with sudden death, myocardial infarction or unstable angina. Under ideal angiographic imaging conditions, different lesion morphologies have different and sometimes characteristic appearances that can be recognized subjectively. Morphologic classification is highly dependent upon the quality of the angiographic image where noise, contrast, resolution, and projection--as well as the size of the vessel and lesion may limit the degree of observer confidence. These are the rational for this proposal where the major objective is to optimize angiographic detection and classification of coronary artery lesion morphology. Digital image processing will be used to address four long term goals: (1) to develop a basic understanding of visual perception of dynamically displayed cineangiograms; (2) to define the accuracy of morphological classification of coronary stenoses and how accuracy depends upon image enhancement and display; (3) to develop imaging and display techniques for maximizing this accuracy; and (4) to perform clinical validation of morphological classification. Detailed preliminary data are presented and a program of research is described which uses computer simulations, post-mortem histologic validation, and human angioscopic studies to quantify observer performance for angiographic detection of morphologic features. If successful, this grant will extend image signal detection theory to include cine, or dynamic, image display and develop specific and reliable methods to optimize the coronary angiograms for the detection and extractior of anatomic parameters of atherosclerotic plaque surface morphology. Thus, the potential health related impact of this research may be a more accurate means of identifying high risk coronary lesions and thus improve clinical decision making in patients with coronary artery disease.

尽管在医学界进行了超过一百万次冠状动脉造影美国每年血管造影预测风险或结果的潜力可能尚未完全实现。在过去的几年里，有不断发展的证据表明动脉粥样硬化斑块表面形态，而不是管腔阻塞的程度，预测不稳定的缺血综合症。病理学和血管镜研究表明，斑块破坏（开裂、溃疡或出血，有或没有绝大多数患者存在血栓形成猝死、心肌梗塞或不稳定型心绞痛。理想状态下血管造影成像条件不同，病变形态也不同可以识别的不同的、有时是特征性的外观主观上。形态学分类高度依赖于血管造影图像的质量，其中噪声、对比度、分辨率和投影——以及血管和病变的大小可能会限制观察者的置信度。这些是这个提议的理由主要目标是优化血管造影检测和冠状动脉病变形态的分类。数字图像处理将用于实现四个长期目标：(1) 制定对动态显示的视觉感知有基本的了解电影血管造影； (2)定义形态分类的准确率冠状动脉狭窄以及准确性如何取决于图像增强和展示; (3) 开发成像和显示技术以最大化这一点准确性; (4) 进行形态学的临床验证分类。提供了详细的初步数据和计划描述了使用计算机模拟、事后分析的研究组织学验证和人体血管镜研究以量化观察者血管造影检测形态特征的性能。如果成功后，这笔资助将扩展图像信号检测理论，包括电影或动态图像显示并开发特定且可靠的方法优化冠状动脉造影以检测和提取动脉粥样硬化斑块表面形态的解剖参数。因此，这项研究的潜在健康相关影响可能更准确识别高风险冠状动脉病变的方法，从而改善临床冠状动脉疾病患者的决策。