Multiparametric MRI for prostate cancer: a national survey of patterns of practice among radiation oncologists in Spain

Three-dimensional convolutional neural network model to identify clinically significant prostate cancer in transrectal ultrasound videos: a prospective, multi-institutional, diagnostic study

BACKGROUND

Identifying patients with clinically significant prostate cancer (csPCa) before biopsy helps reduce unnecessary biopsies and improve patient prognosis. The diagnostic performance of traditional transrectal ultrasound (TRUS) for csPCa is relatively limited. This study was aimed to develop a high-performance convolutional neural network (CNN) model (P-Net) based on a TRUS video of the entire prostate and investigate its efficacy in identifying csPCa.

METHODS

Between January 2021 and December 2022, this study prospectively evaluated 832 patients from four centres who underwent prostate biopsy and/or radical prostatectomy. All patients had a standardised TRUS video of the whole prostate. A two-dimensional CNN (2D P-Net) and three-dimensional CNN (3D P-Net) were constructed using the training cohort (559 patients) and tested on the internal validation cohort (140 patients) as well as on the external validation cohort (133 patients). The performance of 2D P-Net and 3D P-Net in predicting csPCa was assessed in terms of the area under the receiver operating characteristic curve (AUC), biopsy rate, and unnecessary biopsy rate, and compared with the TRUS 5-point Likert score system as well as multiparametric magnetic resonance imaging (mp-MRI) prostate imaging reporting and data system (PI-RADS) v2.1. Decision curve analyses (DCAs) were used to determine the net benefits associated with their use. The study is registered at https://www.chictr.org.cn with the unique identifier ChiCTR2200064545.

FINDINGS

The diagnostic performance of 3D P-Net (AUC: 0.85-0.89) was superior to TRUS 5-point Likert score system (AUC: 0.71-0.78, P = 0.003-0.040), and similar to mp-MRI PI-RADS v2.1 score system interpreted by experienced radiologists (AUC: 0.83-0.86, P = 0.460-0.732) and 2D P-Net (AUC: 0.79-0.86, P = 0.066-0.678) in the internal and external validation cohorts. The biopsy rate decreased from 40.3% (TRUS 5-point Likert score system) and 47.6% (mp-MRI PI-RADS v2.1 score system) to 35.5% (2D P-Net) and 34.0% (3D P-Net). The unnecessary biopsy rate decreased from 38.1% (TRUS 5-point Likert score system) and 35.2% (mp-MRI PI-RADS v2.1 score system) to 32.0% (2D P-Net) and 25.8% (3D P-Net). 3D P-Net yielded the highest net benefit according to the DCAs.

INTERPRETATION

3D P-Net based on a prostate grayscale TRUS video achieved satisfactory performance in identifying csPCa and potentially reducing unnecessary biopsies. More studies to determine how AI models better integrate into routine practice and randomized controlled trials to show the values of these models in real clinical applications are warranted.

FUNDING

The National Natural Science Foundation of China (Grants 82202174 and 82202153), the Science and Technology Commission of Shanghai Municipality (Grants 18441905500 and 19DZ2251100), Shanghai Municipal Health Commission (Grants 2019LJ21 and SHSLCZDZK03502), Shanghai Science and Technology Innovation Action Plan (21Y11911200), and Fundamental Research Funds for the Central Universities (ZD-11-202151), Scientific Research and Development Fund of Zhongshan Hospital of Fudan University (Grant 2022ZSQD07).

Multiparametric magnetic resonance imaging-guided salvage radiotherapy in prostate cancer

Aim

To analyse the efficacy and toxicity of postprostatectomy SRT in patients with a BCR evaluated with mpMRI.

Background

Multiparametric magnetic resonance imaging (mpMRI) has the ability to detect the site of pelvic recurrence in patients with biochemical recurrence (BCR) after radical prostatectomy (RP). However, we do not know the oncological outcomes of mpMRI-guided savage radiotherapy (SRT).

Results

Local, lymph node, and pelvic bone recurrence was observed in 13, 4 and 2 patients, respectively. PSA levels were significantly lower in patients with negative mpMRI (0.4 ng/mL [0.4]) vs. positive mpMRI (2.2 ng/mL [4.1], p = 0.003). Median planning target volume doses in patients with visible vs. non-visible recurrences were 76 Gy vs. 70 Gy. Overall, mean follow-up was 41 months (6-81). Biochemical relapse-free survival (bRFS) at 3 years was 82.3% and 82.5%, respectively, for the negative and positive mpMRI groups (p = 0.800). Three-year rates of late grade ≥2 urinary and rectal toxicity were 14.8% and 1.9%, respectively; all but one patient recovered without sequelae.

Conclusion

SRT to the macroscopic recurrence identified by mpMRI is a feasible and well-tolerated option. In this study, there were no differences in bRFS between MRI-positive and MRI-negative patients, indicating effective targeting of MRI-positive lesions.