A Numerical Study of the Influence of Different Factors on Mechanical Characterization of Tumors via a 2D Tactile Sensor
This paper presents a numerical study of the influence of different factors on tumor detection via a 2D tactile sensor. The 2D tactile sensor entails a polydimethylsiloxane (PDMS) microstructure embedded with a 3 × 3 sensing-plate/transducer array. By pressing the sensor against a tissue region with a predefined indentation depth pattern, the tissue stiffness distribution is extracted from the measured slopes of the deflections of the sensing-plate array versus the indentation depth. In this work, we numerically investigate the influence of curved tissue surface, curved substrate and tissue viscoelasticity on the measured sensor deflection distribution, which is representative of the tissue stiffness distribution. A set of numerical models are created in COMSOL Multiphysics to investigate the influence of the above-mentioned factors separately. A purely elastic numerical model with a flat substrate and a flat tissue surface is created as the reference model. Two other numerical models are created with one having a curved surface and the other having a curved substrate. The same tumor is embedded in these three models. Given the same 2D sensor, how the measured sensor deflection distribution is affected by different curved surfaces and curved substrates is compared with the results from the reference model. The three tumor parameters (elasticity, size and depth) are also varied for their influence on the measured results. A separate viscoelastic numerical model is created to study how the time-dependent behavior of a tumor varies with its viscoelasticity. This model provides the guidance on tailoring the testing parameters in a pre-defined indentation protocol for quantitatively maximizing the difference in viscoelasticity among different tumors.