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Human Carotid Atherosclerotic Plaque Growth Function and Progression Simulation Using Meshless GFD and Statistical Methods Based on Multi-Year In Vivo MRI

[+] Author Affiliations
Chun Yang

Beijing Normal University, Beijing, China

Joseph D. Petruccelli, Zhongzhao Teng, Dalin Tang

Worcester Polytechnic Institute, Worcester, MA

Chun Yuan, Gador Canton, Fei Liu, Thomas S. Hatsukami

University of Washington, Seattle, WA

Paper No. IMECE2008-66759, pp. 93-94; 2 pages
doi:10.1115/IMECE2008-66759
From:
  • ASME 2008 International Mechanical Engineering Congress and Exposition
  • Volume 2: Biomedical and Biotechnology Engineering
  • Boston, Massachusetts, USA, October 31–November 6, 2008
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-4863-0 | eISBN: 978-0-7918-3840-2
  • Copyright © 2008 by ASME

abstract

Atherosclerotic plaque rupture and progression have been the focus of intensive investigations in recent years. The mechanisms governing plaque progression and rupture process are not well understood. Using computational models based on patient-specific multi-year in vivo MRI data, our recent results indicated that 18 out of 21 patients studied showed significant negative correlation between plaque progression measured by vessel wall thickness increase (WTI) and plaque wall (structural) stress (PWS) [1]. In this paper, a computational procedure based on meshless generalized finite difference (MGFD) method and serial magnetic resonance imaging (MRI) data was introduced to simulate plaque progression. Participating patients were scanned three times (T1 , T2 , and T3 , at intervals of approximately 18 months) to obtain plaque progression data. Vessel wall thickness (WT) changes were used as the measure for plaque progression. Starting from T2 plaque geometry, plaque progression was simulated by solving the solid model and adjusting wall thickness using plaque growth functions iteratively until time T3 is reached. Numerically simulated plaque progression showed very good agreement with actual plaque geometry at T3 given by MRI data. We believe this is the first time plaque progression simulation results based on multi-year patient-tracking data are reported. Multi-year tracking data and MRI-based progression simulation add time dimension to plaque vulnerability assessment and will improve prediction accuracy.

Copyright © 2008 by ASME

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