| Prostate cancer (PCa) recurrences are often predicted by assessing the status of surgical margins (SM)---positive surgical margins (PSM) increase the chances of biochemical recurrence by 2-4 times which may lead to PCa recurrence. At present, there are no available tools that are being readily used in the operating room to detect PSMs. To address this need, a multi-frequency multi-channel electrical impedance acquisition system with a microendoscopic probe was developed and employed in an ex-vivo study of human prostates. This system measures the tissue bioimpedance over a range of frequencies (1 kHz to 1MHz), and computes a number of Composite Impedance Metrics (CIM). A support vector machine (SVM) classifier based method (trained using CIM data) was used to compute the probability of probed tissue site being cancerous.;The system was used to collect the impedance spectra from 14 excised prostates, which were obtained from men undergoing radical prostatectomy, for a total of 23 cancerous and 53 benign measurements. The data revealed statistically significant (p<0.05) differences in the impedance properties of the benign and tumorous tissues, and among the measurements taken on the apical, base, and lateral surface of the prostate. Further, in the leave-one-patient-out cross validation, a maximum predictive accuracy of 90.79% was achieved by combining high frequency CIM phase data to train the SVM classifier. The observations are consistent with the physiology and morphology of benign and malignant prostate tissue. CIMs were found to be an effective tool in distinguishing benign from cancerous tissues in the ex-vivo study. |
