Comparative study of time- and frequency-difference electrical impedance tomography for breast cancer detection

A multifrequency electrical impedance tomography (EIT) system was evaluated for its ability to detect conductive inclusions simulating carcinomas in breast phantoms, with a comparative analysis of time-difference and frequency-difference reconstruction approaches. The proposed EIT V5 system employs two concentric rings of 16 electrodes to acquire surface voltage measurements at multiple excitation frequencies (50 kHz, 500 kHz, and 1 MHz). Image reconstruction was performed using the Linear Back Projection (LBP) algorithm, and system performance was quantitatively assessed through spatial overlap metrics (intersection over union, IoU, and F1-score), contrast-to-noise ratio (CNR), and confusion-matrix-derived metrics (sensitivity, specificity, and precision). The area under the receiver operating characteristic curve (AUC) was also computed as a pixel-level, threshold-independent separability metric. Experimental phantoms were designed to approximate breast tissue composition, consisting primarily of adipose material with embedded conductive inclusions representing tumors. The results show that frequency-difference EIT consistently outperforms time-difference reconstruction across all evaluated scenarios, achieving higher CNR values (> 2.4) and improved spatial agreement (IoU and F1-score), while time-difference reconstructions exhibit significant variability and reduced contrast at lower frequencies. Although high AUC values (> 0.99) are observed for the frequency-difference approach, these should be interpreted as indicators of conductivity separability within individual reconstructions rather than diagnostic performance. Reconstructions obtained from the lower electrode ring demonstrate increased sensitivity, highlighting the influence of electrode geometry and inclusion proximity on detection performance. Importantly, frequency-difference reconstructions enhance contrast between conductive inclusions and surrounding tissue without requiring a prior baseline measurement. These findings indicate that multifrequency, frequency-difference EIT provides a robust and reliable approach for detecting conductive anomalies in controlled phantom conditions, reducing reconstruction artifacts and improving tissue discrimination. The proposed methodology shows strong potential as an auxiliary tool for early breast cancer detection, intracranial hemorrhage monitoring, and the development of wearable biomedical imaging systems.