Vulnerable Plaques: Data, Modeling, Predictions and Clinical Applications

Tang, Dalin

Abstract

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.

Public Health Relevance

The workshop will gather researchers from different disciplines related to image-based cardiovascular computational modeling for vulnerable atherosclerotic plaques to exchange state-of-the-art techniques in their respective fields, which will include including image data acquisition, imaging technique development, segmentation, histopathological analysis, mechanical engineering, modeling, patient study, risk factors, cellular and genomic studies, and commercialization. Researchers from different disciplines will reach out to share their expertise, 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.