Effect of Tumor Variables and Sensor Design on the Measured Stiffness Distribution of Tumor-Embedded Tissues: A Numerical Study

Abstract

This paper reports on a numerical study on how the measured stiffness distribution of a tumor-embedded tissue via a two-dimensional (2D) tactile sensor varies with the tumor variables (i.e., elasticity, size and depth) and the sensor design parameters. The sensor entails a polydimethylsiloxane (PDMS) microstructure embedded with a 3×3 sensing-plate/transducer array sitting on a Pyrex substrate. Pressing the sensor against a tissue region with a pre-defined indentation depth pattern, the tissue stiffness distribution is extracted from the measured slopes of the deflections of the 3×3 sensing-plate array versus the indentation depth. A finite element model (FEM) of the tissue-sensor interaction, which includes the Pyrex substrate, the microstructure, and a tumor-embedded tissue, is created using COMSOL Multiphysics. The tumor variables and the sensor design parameters are varied in the model to examine how the measured tissue stiffness distribution is affected by them. Based on the numerical results, the relation of the measured tissue stiffness distribution to the tumor variables and sensor design parameters is obtained, shedding insight on establishing a threshold on the stiffness contrast for tumor identification.