New developments in PCa evaluation: Pathology & Radiomics

10 November 2018

EMUC interactive audience

EMUC prides itself on being a multidisciplinary meeting on genito-urinary cancers and one draw for the audience is the opportunity to ask experts from other disciplines for an honest view on shared problems in diagnosis and treatment.

Such was the case for Prof. Jonathan Epstein, expert pathologist from Baltimore (US) who structured his talk in the shape of “questions on PCa pathology you were afraid to ask”. The audience members certainly didn’t show their fear after his talk, as many took the opportunity to ask some very specific questions that they had been stewing on.

Epstein spoke on the second day of EMUC18, the 10th European Multidisciplinary Congress on Urological Cancers in Amsterdam.

Patient impact

Prof. Epstein highlighted several subtleties in pathology that clinicians might not be aware of but that certainly impact the patients that they are treating. The case of extra-prostatic extension (EPE) at radical prostatectomy, which can be classified as focal, or non-focal. Epstein: “Both kinds are currently staged as pT3a, with no distinction between the two. However, focal EPE has much better prognosis than non-focal with grade influential.”

“Some recommendations to routinely do adjuvant radiotherapy following radical prostatectomy with EPE is not supported by data, especially with lower grade cancer and those with focal EPE in the absence of a positive margin,” Epstein said on the implications for treatment.

Similarly, distinction between positive margins can be made based on location, extent and grade. The location of the positive margin has no influence on the prognosis, but the extent of the positive margin does affect the risk of recurrence. There is a proportion to the extent, but the cut-off of 3mm positive margin has been shown to have prognostic value. Epstein: “The grade at the margin also correlates with the risk of recurrence, especially critical with Gleason score 7 tumours as the tumour at margin can vary.”

Other topics covered by Epstein included high-grade prostatic intraepithelial neoplasia and ductal adenocarcinoma.

Prof. Alberto Briganti (Milan, IT) acted as discussant and asked some questions from the treating urologist’s perspective, specifically on how the clinician could help the pathologist achieve better results. Briganti asked for the most important biopsy quality indicators. Prof. Epstein noted that the total core length of the biopsy is very important but is too rarely reported.

Also, the definition of clinically insignificant disease is up for debate. Epstein: “Current definitions stem from a time when active surveillance was a new and controversial concept. The definitions were very strict and can be relaxed a bit.”


The second speaker in the same session was radiation oncologist Prof. Philippe Lambin (Maastricht, NL), who gave the audience an overview of emerging radiomic technologies. Rather than investing in new hardware (9T MR) or developing new imaging biomarkers (PSMA), new smart software could already extract more information from existing imaging data.

Medical images hold more information than the human eye can identify. With machine learning and image analysis, current images can be converted into minable data and knowledge. This kind of image processing can extract diagnostic, theragnostic, prognostic and predictive radiomic signatures.

After a demonstration of emerging image processing techniques, Prof. Lambin concluded: “Radiomics is an emerging field that can translate medical images into quantitative data to enable phenotypic profiling for diagnosis, treatment decisions and treatment evaluation. There are several potential applications that relate to prostate cancer, such as screening, image-guided biopsies and active surveillance. It’s time to test radiomic approaches systematically in clinical trials.”

Dr. Jochen Walz (Marseille, FR) concurred, explaining that the radiomics approach was already in clinical use, and showed great potential for improving PCa management in the future. “In fact, AI solutions will replace the traditional workload and change the medical landscape and perhaps even put some specialists out of a job.”