Exploring the relationship between the dielectric properties and viability of human normal hepatic tissues from 10 Hz to 100 MHz based on grey relational analysis and BP neural network.

Journal: Computers in biology and medicine
Published Date:

Abstract

Liver is an important parenchyma organ, and its tissue viability plays an important role in liver transplantation and liver ischemic injury assessment. Dielectric property is a useful biophysical feature that provides insights into the structure and composition of biological tissues. This work aims to establish the relationship between the dielectric properties and viability of human normal hepatic tissues and explore the possibility of evaluating tissue viability by using dielectric properties. First, data on dielectric properties and tissue viability (including cell morphology and enzyme indicators) were collected from human liver tissues at 0.25-24 h after isolation. Grey relational analysis was conducted to select dielectric property and tissue viability indices that were highly correlated with prolonged ex vivo time as the inputs and outputs, respectively, of back-propagation (BP) neural network analysis. Finally, a BP neural network was developed with the Levenberg-Marquardt algorithm to explore the possibility of using dielectric properties as the basis for tissue viability evaluation. Results showed that the mean relative error for prediction was 2.40%, indicating that the model showed potential in forecasting liver tissue viability by applying dielectric properties.

Authors

  • Hang Wang
    Key Subject Laboratory of Nuclear Safety and Simulation Technology, Harbin Engineering University, Harbin, 150001, China. Electronic address: wanghang1990312@126.com.
  • Lei Wang
    Department of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Lin Yang
    National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, China.
  • Xuetao Shi
    Department of Medical Electronic Engineering, Faculty of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi, 710032, China.
  • Zhihong Wen
    School of Aerospace Medicine, Air Force Medical University, Xi'an, China.
  • Xiuzhen Dong
    School of Biomedical Engineering, Air Force Medical University, Xi'an, China. Electronic address: dongxiuzhen@fmmu.edu.cn.