Speaker: 

Dalin Tang

Institution: 

WPI

Time: 

Monday, February 5, 2007 - 4:00pm

Location: 

MSTB 254

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 in vivo patient-specific geometries. 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.

It is well-accepted that atherosclerosis initiation and progression correlate positively with low and oscillating flow wall shear stresses. However, this low and oscillating shear stress hypothesis cannot explain why intermediate and advanced plaques continue to grow under elevated high flow shear stress conditions. It is also natural that people think that plaque rupture may be related to maximum stress conditions. We will challenge those popular views and present evidence which support new hypotheses for plaque progression and rupture conditions. Patient-specific multi-year serial MRI were acquired to provide plaque morphology and progression data. A 3D multi-component model with fluid-structure interactions (FSI) was introduced to obtain the flow and stress/strain distributions in the plaque to better understand mechanisms governing plaque progression and rupture process. Our results indicate that plaque thickness and plaque progression correlate positively with low structure wall stress for intermediate and advanced plaques which supports a possible new hypothesis: Low structure stress in the plaque has positive correlation with plaque growth, and may create favorable mechanical conditions for further plaque progression. For plaque vulnerability assessment, our results also indicate that maximum stress conditions are often found at healthy site of the vessel and are not good indicators of rupture risk. A computational plaque vulnerability index (CPVI) based on local stress conditions at critical sites was proposed. Plaque assessments (34 plaque MRI samples) using CPVI method had 90% agreement rate with histopathological analysis. With more patient study validations, our research may serve as the starting points for further plaque progression and rupture investigations. The work has been supported by the National Sciences Foundation (DMS and BIO), National Institutes of Health (NIBIB and NIGMS), and the Whitaker Foundation.