Related Experiment Video
Updated: Jun 4, 2026
Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence
Published on: June 10, 2025
A retrospective study to reduce prostate biopsy cores by a real time interactive tool
Nicola Testoni1, Nicolò Speciale, Alessandro Bertaccini
1DEIS, Department of Electronics, Computer Sciences and Systems, University of Bologna, Italy. nicola.testoni@unibo.it
Objective:
Prostate carcinoma (PCa) is one of the most frequent neoplasms, with more than 110.000 new cases/year in Europe. As PCa is not clearly demonstrable at transrectal ultrasound (TRUS), guidelines on TRUS guided biopsy suggest to perform a random tissue sampling (at least 8-12 "cores" depending on gland volume). Although accuracy grows with core number, patient discomfort and adverse event probability grow as well. Thus it would be worth to aim to reduce the number of prostate biopsy cores without loss of diagnostic accuracy.
Materials And Methods:
A retrospective study was performed to evaluate the feasibility of an improved version of a rtCAB tool developed at DEIS (University of Bologna) for the reduction of prostate biopsy cores. rtCAB is an innovative processing technique which enhances TRUS video stream by a live false color overlay image that helps the physician to perform the biopsy by guiding the sampling into target zones. In order to train rtCAB, a monocentric, single operator prostate gland adenocarcinoma database has been built. The database enlists 81 patients, for a total of 743 prostate byoptic (PBx) cores and 14860 ROI. For each patient we collected age, PSA levels, digital rectal examination (DRE) findings, presence or absence of focal lesions, and prostate volume. During TRUS, raw ultrasound data were acquired and associated to each PBx core. For each core we collected both the radio frequency (RF) signal and the histological outcome.
Results:
The whole system was optimized for reducing the number of false positives while preserving an acceptable number of false negatives. Comparing to a classical PBx approach (8-12 cores), the estimated positive predictive value (PPV) of our method increased from 25% to 40%, with an overall sensitivity of 85%.
Conclusions:
Preliminary results show that the proposed tool can provide real-time feedback to the operator during TRUS. Sensitivity and PPV values suggest that a reduction of almost 50% the number of biopsy cores without losing in diagnostic accuracy is feasible. A prospective study is needed to further confirm these preliminary retrospective results.
