Three-Dimensional Carotid Plaque Progression Simulation Using Meshless Generalized Finite Difference Method Based on
Chun Yang1, Dalin Tang, Satya Atluri
1School of Mathematical Sciences, Beijing Normal University, Lab of Math and Complex Systems, Ministry of Education, Beijing, China.
Insights
This study introduces a computational method to simulate atherosclerotic plaque progression using serial MRI scans. The simulation accurately predicts plaque growth, improving cardiovascular disease risk assessment.
Area of Science:
- Biomedical Engineering
- Computational Medicine
- Cardiovascular Research
Background:
- Cardiovascular disease (CVD) is the leading global cause of death, often driven by atherosclerotic plaque rupture.
- Understanding the mechanisms of plaque progression is crucial for preventing heart attack and stroke.
- Current methods lack the ability to precisely quantify individual plaque component growth over time.
Purpose of the Study:
- To develop and validate a computational procedure for simulating patient-specific atherosclerotic plaque progression.
- To quantify plaque growth functions using serial magnetic resonance imaging (MRI) data.
- To enhance the prediction accuracy of plaque rupture risk by incorporating a temporal dimension.
Main Methods:
- Utilized a three-dimensional meshless generalized finite difference (MGFD) method with serial MRI data from patients scanned over approximately 18 months.
- Modeled the atherosclerotic plaque as a uniform, homogeneous, isotropic, linear, and nearly incompressible material using a linear elastic model.
- Developed four distinct growth functions to predict plaque progression based on vessel wall thickness, stress, and neighboring point data.
- Simulated plaque progression iteratively from T2 to T3 geometry, adjusting wall thickness until the target geometry was reached.
Main Results:
- The computational simulation demonstrated high accuracy in predicting plaque progression, with errors ranging from 4.45% to 11.56% compared to actual T3 plaque geometry.
- The study successfully simulated 3D plaque progression using multi-year patient tracking data, a novel approach.
- The developed growth functions effectively predicted future plaque growth based on historical data.
Conclusions:
- This novel serial MRI-based simulation approach provides a temporal dimension for assessing plaque vulnerability.
- The computational method offers a significant improvement in predicting potential plaque rupture risk.
- The findings pave the way for more accurate and personalized cardiovascular risk stratification.
Abstract:
Cardiovascular disease (CVD) is becoming the number one cause of death worldwide. Atherosclerotic plaque rupture and progression are closely related to most severe cardiovascular syndromes such as heart attack and stroke. Mechanisms governing plaque rupture and progression are not well understood. A computational procedure based on three-dimensional meshless generalized finite difference (MGFD) method and serial magnetic resonance imaging (MRI) data was introduced to quantify patient-specific carotid atherosclerotic plaque growth functions and simulate plaque progression. Participating patients were scanned three times (T1, T2, and T3, at intervals of about 18 months) to obtain plaque progression data. Vessel wall thickness (WT) changes were used as the measure for plaque progression. Since there was insufficient data with the current technology to quantify individual plaque component growth, the whole plaque was assumed to be uniform, homogeneous, isotropic, linear, and nearly incompressible. The linear elastic model was used. The 3D plaque model was discretized and solved using a meshless generalized finite difference (GFD) method. Four growth functions with different combinations of wall thickness, stress, and neighboring point terms were introduced to predict future plaque growth based on previous time point data. Starting from the T2 plaque geometry, plaque progression was simulated by solving the solid model and adjusting wall thickness using plaque growth functions iteratively until T3 is reached. Numerically simulated plaque progression agreed very well with the target T3 plaque geometry with errors ranging from 11.56%, 6.39%, 8.24%, to 4.45%, given by the four growth functions. We believe this is the first time 3D plaque progression simulation based on multi-year patient-tracking data was reported. Serial MRI-based progression simulation adds time dimension to plaque vulnerability assessment and will improve prediction accuracy for potential plaque rupture risk.
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