Image-based modeling for better understanding and assessment of atherosclerotic plaque progression and vulnerability: Data, modeling, validation, uncertainty and predictions

Dalin Tang, Roger D. Kamm, Chun Yang, Jie Zheng, Gador Canton, Richard Bach, Xueying Huang, Thomas S. Hatsukami, Jian Zhu, Genshan Ma, Akiko Maehara, Gary S. Mintz, Chun Yuan

Research output: Contribution to journalArticle

43 Scopus citations

Abstract

Medical imaging and image-based modeling have made considerable progress in recent years in identifying atherosclerotic plaque morphological and mechanical risk factors which may be used in developing improved patient screening strategies. However, a clear understanding is needed about what we have achieved and what is really needed to translate research to actual clinical practices and bring benefits to public health. Lack of in vivo data and clinical events to serve as gold standard to validate model predictions is a severe limitation. While this perspective paper provides a review of the key steps and findings of our group in image-based models for human carotid and coronary plaques and a limited review of related work by other groups, we also focus on grand challenges and uncertainties facing the researchers in the field to develop more accurate and predictive patient screening tools.

Original languageEnglish
Pages (from-to)834-846
Number of pages13
JournalJournal of Biomechanics
Volume47
Issue number4
DOIs
StatePublished - Mar 3 2014

Keywords

  • Atherosclerosis
  • Fluid-structure interaction
  • IVUS-based modeling
  • MRI-based modeling
  • Vulnerable plaques

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