Detection of invasive ductal carcinoma by electrical impedance spectroscopy implementing gaussian relaxation-time...

Breast cancer detection and differentiation of breast tissues are critical for accurate diagnosis and treatment planning. This study addresses the challenge of distinguishing between invasive ductal carcinoma (IDC), normal glandular breast tissues (nGBT), and adipose tissue using electrical impedance spectroscopy combined with Gaussian relaxation-time distribution (EIS-GRTD). The primary objective is to investigate the relaxation-time characteristics of these tissues and their potential to differentiate between normal and abnormal breast tissues. We applied a single-point EIS-GRTD measurement to ten mastectomy specimens across a frequency rangef= 4 Hz to 5 MHz. The method calculates the differential ratio of the relaxation-time distribution functionΔγbetween IDC and nGBT, which is denoted byΔγIDC-nGBT,andΔγbetween IDC and adipose tissues, which is denoted byΔγIDC-adipose.As a result, the differential ratio ofΔγbetween IDC and nGBTΔγIDC-nGBTis 0.36, and between IDC and adiposeΔγIDC-adiposeis 0.27, which included in theα-dispersion atτpeak1=0.033±0.001s.In all specimens, the relaxation-time distribution functionγof IDCγIDCis higher, and there is no intersection withγof nGBTγnGBTand adiposeγadipose.The difference inγsuggests potential variations in relaxation properties at the molecular or structural level within each breast tissue that contribute to the overall relaxation response. The average mean percentage errorδfor IDC, nGBT, and adipose tissues are 5.90%, 6.33%, and 8.07%, respectively, demonstrating the model's accuracy and reliability. This study provides novel insights into the use of relaxation-time characteristic for differentiating breast tissue types, offering potential advancements in diagnosis methods. Future research will focus on correlating EIS-GRTD finding with pathological results from the same test sites to further validate the method's efficacy.