Modeling of human artery tissue with probabilistic approach. (1st April 2015)

• Record Type: Journal Article
• Authors: Xiong, Linfei; Chui, Chee-Kong; Fu, Yabo; Teo, Chee-Leong; Li, Yao
• Is Part Of: Computers in biology and medicine. Volume 59(2015)
• Page Start: 152
• Page End: 159
• Publication Date: 2015-04-01
• Subjects: Human arterial tissue -- Probabilistic approach -- Uncertainty analysis -- Tissue modeling -- Medical simulation; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2015.01.021
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: Accurate modeling of biological soft tissue properties is vital for realistic medical simulation. Mechanical response of biological soft tissue always exhibits a strong variability due to the complex microstructure and different loading conditions. The inhomogeneity in human artery tissue is modeled with a computational probabilistic approach by assuming that the instantaneous stress at a specific strain varies according to normal distribution. Material parameters of the artery tissue which are modeled with a combined logarithmic and polynomial energy equation are represented by a statistical function with normal distribution. Mean and standard deviation of the material parameters are determined using genetic algorithm (GA) and inverse mean-value first-order second-moment (IMVFOSM) method, respectively. This nondeterministic approach was verified using computer simulation based on the Monte-Carlo (MC) method. Cumulative distribution function (CDF) of the MC simulation corresponds well with that of the experimental stress–strain data and the probabilistic approach is further validated using data from other studies. By taking into account the inhomogeneous mechanical properties of human biological tissue, the proposed method is suitable for realistic virtual simulation as well as an accurate computational approach for medical device validation. Highlights: Probabilistic approach is used to model the inhomogeneity of human artery tissue. Tissue properties are represented by a statistical function with normal distribution. Mean value of the material parameters are identified using genetic algorithm. Empirical 3-sigma rule is used for reliability study of the statistical model. The statistical model represents the human artery properties accurately.