Automated Plaque Detection and Classification using MRI

描述（由申请人提供）： 在破裂/侵蚀的人类动脉粥样硬化病变上的急性血栓形成在急性冠状动脉综合征的发作和动脉粥样硬化的进展中起关键作用。病理学证据已明确表明，斑块的组成而不是狭窄的严重程度调节斑块的脆弱性和血栓形成。因此，检测和表征动脉粥样硬化病变的可能性将具有重要的临床意义。在不同的成像方式中，MRI似乎是最有前途的歧视方面，由于其非侵入性的性质。我们建议开发一个自动化的MRI图像分析系统，用于检测，测量和分类动脉粥样硬化斑块。拟议的项目将由一个在信号处理、模式识别、统计和产品开发方面经验丰富的专家团队与主要的心血管研究人员密切合作进行，这些研究人员在MRI成像和动脉粥样硬化方面具有特定的专业知识。自动化将建立一个快速、客观（独立于患者）和标准的斑块负荷诊断措施，允许在实验室之间、整个纵向研究中以及不同成像设备之间比较结果。在临床环境中，该系统将大大降低测量狭窄程度和检测血栓形成倾向斑块的诊断成本。

DESCRIPTION (provided by applicant): Acute thrombus formation on disrupted/eroded human atherosclerotic lesions plays a critical role on the onset of acute coronary syndromes and progression of atherosclerosis. Pathological evidence has clearly established that it is plaque composition rather than stenotic severity that modulates plaque vulnerability and thrombogenicity. Therefore, the possibility of detecting and characterizing atherosclerotic lesions would have significant clinical implications. Among the different imaging modalities, MRI seems to be the most promising in terms of discrimination and due to its non-invasive nature. We propose to develop an automated MRI image analysis system for detecting, measuring, and classifying atherosclerotic plaques. The proposed project will be conducted by a highly experienced team of experts in signal processing, pattern recognition, statistics, and product development in close collaboration with key cardiovascular researchers, with specific expertise in MRI imaging and atherosclerosis. Automation would establish a fast, objective (observer-independent), and standard diagnostic measure of plaque burden, allowing for comparison of results between laboratories, throughout longitudinal studies, and across different imaging equipment. In a clinical setting, this system would greatly reduce the diagnostic costs involved in measuring the degree of stenosis and detecting thrombosis-prone plaques.