Atherosclerosis is a disease in human circulation system affecting a large percentage of people, especially elderly people in the developed countries. To better predict plaque progression and prevent potential rupture, multi-year MRI patient-tracking data were obtained to quantify human atherosclerotic plaque progression. MRI-based 2D/3D models with multi-component plaque structure and fluid-structure interactions (FSI) were developed and solved by numerical methods based on the meshless local Petrov-Galerkin (MLPG) method (2D) and finite element method (2D/3D) to quantify plaque growth functions which can be used to simulate plaque progression for early prediction and diagnosis of atherosclerosis-related cardiovascular diseases. For the first time, quantitative human plaque growth functions were determined using structure stress and flow shear stress data. Use of multi-year data leads to verifiable simulations and improved accuracy of predictions. Our initial results support the new hypothesis that plaque progression has negative correlation with structural stress and flow shear stress conditions. Plaque growth functions using both structure stress and flow shear stress leads to much better agreement with patient plaque progression data than using either of them. More data and validations are needed to confirm our findings.