Vulnerable Plaques: Data, Modeling, Predictions and Clinical Applications

易损斑块：数据、建模、预测和临床应用

• 批准号: 8787593
• 负责人: Dalin Tang
• 金额: $ 0.7万
• 依托单位: WORCESTER POLYTECHNIC INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8787593
• 关键词: Area; Arterial Fatty Streak; Automation; Biomechanics; Blood Pressure; Cardiovascular Diseases; Cardiovascular system; Cause of Death; Clinical; Commit; Communities; Computer Simulation; Diagnostic Procedure; Disabled Persons; Discipline; Educational workshop; Engineering; Event; Genomics; Hemorrhage; Image; Imaging Techniques; Imaging technology; Individual; Inflammation; Link; Marketing; Mechanics; Medical Imaging; Medicare; Methods; Minority Groups; Modeling; Morphology; Myocardial Infarction; Operative Surgical Procedures; Participant; Patients; Play; Process; Property; Public Health; Research; Research Personnel; Resolution; Risk; Risk Factors; Role; Rupture; Severities; Stenosis; Stroke; Students; Surface; Techniques; Testing; Thick; Thrombosis; Training; Translations; Validation; Woman; base; clinical application; clinical practice; commercialization; cost; data acquisition; data modeling; dissemination research; frontier; knowledge base; model development; public health relevance; screening; skills; technique development; tool

DESCRIPTION (provided by applicant): Most cardiovascular events such as heart attack or stroke are caused by plaque rupture which often happens without prior warning. Available screening and diagnostic methods are insufficient to identify the victims before the event occurs. Medical imaging has emerged as powerful tool to quantify atherosclerotic plaque morphology, stenosis severity and plaque compositions. Patient-specific image-based modeling techniques have been developed to perform plaque mechanical analysis and have led to better understanding of mechanisms governing plaque progression and rupture. However, challenges for modeling development in the broader sense in data acquisition, image technology, model construction and automation, identification of risk factors, prediction methods, and final transition to clinical applications are calling for collaborative effort of the entire research community to bring research effort closer to actual applications. Researchers from different disciplines need to reach out to share their expertise, as well as to listen to other experts to understand the big picture, understand what their discipline can contribute, what other discipline needs from their discipline that they are in, what their discipline can benefit from others, and figure out future research directions. The objective of this workshop is to gather researchers from different disciplines related to image-based cardiovascular computational modeling to exchange state-of-the-art techniques in their respective fields, provide mutual professional training so that participants could broaden their skills and knowledge basis. The workshop will also identify challenges and critical needs in all related areas by listening to experts from other areas. The workshop will have four themes, corresponding to the 4 aims listed below. We propose a two-day workshop, with a half-day committed to each theme. Aim 1. Identify critical issues in medical imaging acquisition techniques related to vulnerable plaque research including image resolution, vulnerable plaque identification, cap thickness, intraplaque hemorrhage, and thrombosis; Aim 2. Identify critical issues in mechanical testing and quantification of material properties and other boundary conditions; Aim 3. Identify critical issues in image-based model development, plaque assessment, mechanisms, prediction of rupture and clinical events, and method sharing; Aim 4. Validation of model predictions and assessment plan; mechanical and modeling analysis in clinical and surgical applications; Research dissemination and commercialization. Experts as well as junior researchers and students will be invited from all areas related to image-based computational modeling for atherosclerotic plaque progression and rupture, including image data acquisition, imaging technique development, segmentation, histopathological analysis, mechanical engineering, modeling, patient study, risk factors, cellular and genomic studies, and commercialization. Special effort will be made to encourage participation from women, racial/ethnic minorities, persons with disabilities, and other underrepresented individuals in the planning and marketing process of the workshop.

描述（由申请人提供）：大多数心血管事件（如心脏病发作或中风）是由斑块破裂引起的，通常在没有事先警告的情况下发生。现有的筛查和诊断方法不足以在事件发生前确定受害者。医学影像学已成为量化动脉粥样硬化斑块形态、狭窄严重程度和斑块成分的有力工具。已经开发了患者特异性的基于图像的建模技术来执行斑块机械分析，并且已经导致更好地理解支配斑块进展和破裂的机制。然而，在数据采集、图像技术、模型构建和自动化、风险因素识别、预测方法以及最终过渡到临床应用的更广泛意义上的建模开发的挑战，需要整个研究界的共同努力，使研究工作更接近实际应用。来自不同学科的研究人员需要伸出手来分享他们的专业知识，并听取其他专家的意见，以了解大局，了解他们的学科可以做出什么贡献，其他学科需要他们所在的学科，他们的学科可以从其他学科受益，并找出未来的研究方向。本次研讨会的目的是聚集来自不同学科的研究人员与基于图像的心血管计算建模，以交流各自领域的最新技术，提供相互的专业培训，使参与者可以扩大他们的技能和知识基础。研讨会还将通过听取其他国家的专家的意见， 地区讲习班将有四个主题，与下列四个目标相对应。我们建议举办为期两天的研讨会，每个主题用半天时间。目标1.识别与易损斑块研究相关的医学成像采集技术中的关键问题，包括图像分辨率、易损斑块识别、帽厚度、斑块内出血和血栓形成;目的2。确定机械测试和材料性能和其他边界条件的量化中的关键问题;目标3。识别基于图像的模型开发、斑块评估、机制、破裂和临床事件预测以及方法共享中的关键问题;目标4。验证模型预测和评估计划;临床和外科应用中的机械和建模分析;研究传播和商业化。专家以及初级研究人员和学生将被邀请从所有领域相关的基于图像的计算建模动脉粥样硬化斑块的进展和破裂，包括图像数据采集，成像技术的发展，分割，组织病理学分析，机械工程，建模，病人研究，风险因素，细胞 基因组研究和商业化。将作出特别努力，鼓励妇女、少数种族/族裔、残疾人和其他代表性不足的个人参与讲习班的规划和营销过程。