Background and purpose: Two previous “Patterns Of Practice” surveys (POP I and POP II), including more than 4000 patients affected by prostate cancer treated with radical external beam radiotherapy (EBRT) between 1980 and 2003, established a “benchmark” Italian data source for prostate cancer radiotherapy. This report (POP III) updates the previous studies. Methods: Data on clinical management and outcome of 2525 prostate cancer patients treated by EBRT from 2004 to 2011 were collected and compared with POP II and, when feasible, also with POP I. This report provides data on clinical presentation, diagnostic workup, radiation therapy management, and toxicity as collected within the framework of POP III. Results: More than 50% of POP III patients were classified as low or intermediate risk using D’Amico risk categories as in POP II; 46% were classified as ISUP grade group 1. CT scan, bone scan, and endorectal ultrasound were less frequently prescribed. Dose-escalated radiotherapy (RT), intensity modulated radiotherapy (IMRT), image guided radiotherapy (IGRT), and hypofractionated RT were more frequently offered during the study period. Treatment was commonly well tolerated. Acute toxicity improved compared to the previous series; late toxicity was influenced by prescribed dose and treatment technique. Five-year overall survival, biochemical relapse free survival (BRFS), and disease specific survival were similar to those of the previous series (POP II). BRFS was better in intermediate- and high-risk patients treated with ≥ 76 Gy. Conclusions: This report highlights the improvements in radiotherapy planning and dose delivery among Italian Centers in the 2004–2011 period. Dose-escalated treatments resulted in better biochemical control with a reduction in acute toxicity and higher but acceptable late toxicity, as not yet comprehensively associated with IMRT/IGRT. CTV-PTV margins >8 mm were associated with increased toxicity, again suggesting that IGRT—allowing for tighter margins—would reduce toxicity for dose escalated RT. These conclusions confirm the data obtained from randomized controlled studies.

The performances of two autosegmentation algorithms were evaluated on 28 anonymized pelvic CT scans as a pilot study for the clinical implementation of a semi-automatic workflow. Four organs at risk (OARs), namely the rectum, bladder, and femoral heads, were contoured manually by an expert radiation oncologist (RO)—considered as the ground truth (GT)—and by model-based segmentation (MBS) and deep learning (DL) algorithms. Autocontouring performances were evaluated using a qualitative scoring system, contouring time analysis, and five geometrical indices: the 95th percentile Hausdorff Distance (95HD), Dice Similarity Coefficient (DSC), Surface Dice Similarity Coefficient (SDSC), Added Path Length (APL), and Relative Added Path Length (RAPL). Considering total median value for the four OARs, both MBS and DL showed clinically acceptable results with differences between the two algorithms being not statistically significant for almost all indices. The DL autocontouring algorithm achieved high geometric accuracy, high scores from the ROs, and consistent performances with all validation indices for every OAR. The MBS algorithm achieved high geometric accuracy for the femoral heads and bladder. The DL algorithm required 30 s to contour all the OARs, and the MBS algorithm required 90 s, showing a time gain compared with the manual contours, which took 20 min for each case. The DL autocontouring algorithm obtained promising but preliminary results with every evaluation metric and for every analyzed OAR. The application of the MBS algorithm as the only contouring tool still presents challenges.