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

J Biomech. 2014 Mar 3;47(4):834-46. doi: 10.1016/j.jbiomech.2014.01.012. Epub 2014 Jan 14.

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.

Keywords: Atherosclerosis; Fluid–structure interaction; IVUS-based modeling; MRI-based modeling; Vulnerable plaques.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Review

MeSH terms

  • Disease Progression
  • Humans
  • Magnetic Resonance Imaging / methods*
  • Magnetic Resonance Imaging / standards*
  • Models, Cardiovascular*
  • Plaque, Atherosclerotic / pathology*
  • Plaque, Atherosclerotic / physiopathology*
  • Predictive Value of Tests
  • Reproducibility of Results
  • Uncertainty