Mathematical Modeling of Human Atherosclerotic Plaques for 
Clinical Predictions


DALIN TANG

John E. Sinclair Professor of Mathematics 
Professor of Biomedical Engineering   
Worcester Polytechnic Institute


Abstract.  Accurate and reliable computational predictions for
biological systems must be based on a) accurate experimental
measurements; b) reliable modeling; c) well-chosen and sufficiently
validated risk indicators (biological and mechanical markers).  For
arterial diseases, experimental measurements include vessel
morphology, material properties, and flow information.  Models for
blood flow in diseased arteries have evolved from 1-D model, 2D and 3D
models, to our recently introduced 3D multi-component models with
fluid-structure interactions based on anatomically-accurate geometries
of human atherosclerotic plaques.    Results from different models can
differ considerably (difference can be from 50% to more than 800%) so
proper bench mark should be set so that accurate and reliable
predictions can be made using computational models.

Results from our 3D MRI-based FSI models for atherosclerotic plaques
will be presented.  In particular, a computational scheme to derive
computational plaque vulnerability index (CPVI) based on
histopathological analysis will be presented.  CPVI has the potential
to be used as a plaque rupture risk indicator which can be monitored
non-invasively and used to make predictions for possible stroke and
heart attack.