Bimodal Characterization of Breast Biopsy Tissues Using MEMS-Based Biochips: Toward Improved Tumor Delineation

Disordered systems are governed by scaling laws that provide a quantifiable description of the system. Recently such laws have been used to describe the growth of cancer cells, suggesting their wide range of applications. In this study, two modes of electrical transport in formalin-fixed paired breast tissue samples are modeled using scaling laws. MEMS-based biochips with interdigitated electrodes and a microheater are integrated with a table-top platform to develop a bimodal tissue characterization system. The system is used to perform temperature and frequency-dependent electrical transport studies on breast biopsies. Temperature-dependent direct current (DC) transport is modeled under the realm of general effective medium theory. Critical temperature ( {T}_{c} ) as a model fit parameter is higher for adjacent normal (42.8 ± 2.0 °C) compared to tumor (36.5 ± 0.9 °C), indicating an early transition from conducting to the insulating regime in tumor tissues. Frequency-dependenti alternating current (AC) transport follows the scaling law, which is the characteristic of disordered systems and growth in biological systems. The parameter onset frequency {f}_{c} is higher for adjacent normal (1.1 ± 0.37 MHz) than the tumor (33.5 ± 14.9 kHz), indicating higher disorder in tumor samples. Further, the value of the fit exponent in the AC conduction regime is higher for tumor tissue, confirming higher disorder in the tumor. The utility of the model fit parameters in classifying samples as tumor and normal is demonstrated using a support vector machine (SVM) classifier, which showed 91.7% accuracy when compared to 70% as obtained for the raw data.