Electrical Impedance Spectroscopy for Ex-Vivo Breast Cancer Tissues Analysis

This paper describes a cancer detection procedure based on customised electrical impedance spectroscopy (EIS) in breast cancer surgical samples and an analysis of its outcomes. A tissue analyser was developed to inject a low-amplitude alternating current with penetrating electrodes into breast specimens along a broad spectrum of frequencies. Experimental measurements were carried out on more than one hundred excised breast cancer specimens, with the goal of discriminating between the tumour and surrounding non-neoplastic tissue. The probe was inserted in different locations immediately after surgical excision in order to measure tissue impedance (modulus and phase). Electrical impedance varied significantly between neoplastic and surrounding non-neoplastic tissues, with a low standard deviation among the different measurements, confirming good reproducibility. Tumours could be discriminated from non-neoplastic tissues according to their impedance modulus value for high frequencies and phase value for low frequencies. Impedance also varied significantly in both non-neoplastic and tumour tissues depending on the patient's age and tumour characteristics, such as size and histological sub-type. EIS is able to discriminate between healthy tissue and cancer. Future developments of this technology could be exploited for intraoperative real-time evaluation of the transition zone between cancer and normal tissues.

Automated summary

This paper presents a cancer detection procedure using customised electrical impedance spectroscopy (EIS) in breast cancer surgical samples and analyzes its outcomes. A tissue analyser was developed to measure tissue impedance in breast specimens using low-amplitude alternating current along a broad spectrum of frequencies. Experimental measurements on over one hundred excised breast cancer specimens showed significant differences in impedance between neoplastic and non-neoplastic tissues, with good reproducibility. EIS has the potential to discriminate between healthy tissue and cancer, and its further development may allow for real-time evaluation of the transition zone between cancer and normal tissues during surgery.