title: Kidney tumor growth prediction by coupling reaction-diffusion and biomechanical model.
abstract: It is desirable to predict the tumor growth rate so that appropriate treatment can be planned in the early stage. Previously, we proposed a finite-element-method (FEM)-based 3-D kidney tumor growth prediction system using longitudinal images. A reaction-diffusion model was applied as the tumor growth model. In this paper, we not only improve the tumor growth model by coupling the reaction-diffusion model with a biomechanical model, but also take the surrounding tissues into account. Different diffusion and biomechanical properties are applied for different tissue types. An FEM is employed to simulate the coupled tumor growth model. Model parameters are estimated by optimizing an objective function of overlap accuracy using a hybrid optimization parallel search package. The proposed method was tested with kidney CT images of eight tumors from five patients with seven time points. The experimental results showed that the performance of the proposed method improved greatly compared to our previous work.
authors.affiliation: School of Electronics and Information Engineering, Soochow University, Suzhou City, Jiangsu 215006, China. xjchen@suda.edu.cn
authors.forename: Xinjian
authors.initials: X
authors.lastname: Chen
authors.forename: Ronald M
authors.initials: RM
authors.lastname: Summers
authors.forename: Jianhua
authors.initials: J
authors.lastname: Yao
mesh_terms: D000328:Adult; D001696:Biomechanical Phenomena; D004058:Diffusion; D005260:Female; D020342:Finite Element Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007680:Kidney Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology*; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D015203:Reproducibility of Results; D014057:Tomography, X-Ray Computed