Non-invasive mechanical properties estimation of embedded objects using tactile imaging sensor

Abstract

Non-invasive mechanical property estimation of an embedded object (tumor) can be used in medicine for characterization between malignant and benign lesions. We developed a tactile imaging sensor which is capable of detecting mechanical properties of inclusions. Studies show that stiffness of tumor is a key physiological discerning parameter for malignancy. As our sensor compresses the tumor from the surface, the sensing probe deforms, and the light scatters. This forms the tactile image. Using the features of the image, we can estimate the mechanical properties such as size, depth, and elasticity of the embedded object. To test the performance of the method, a phantom study was performed. Silicone rubber balls were used as embedded objects inside the tissue mimicking substrate made of Polydimethylsiloxane. The average relative errors for size, depth, and elasticity were found to be 67.5%, 48.2%, and 69.1%, respectively. To test the feasibility of the sensor in estimating the elasticity of tumor, a pilot clinical study was performed on twenty breast cancer patients. The estimated elasticity was correlated with the biopsy results. Preliminary results show that the sensitivity of 67% and the specificity of 91.7% for elasticity. Results from the clinical study suggest that the tactile imaging sensor may be used as a tumor malignancy characterization tool.