In this study, we evaluated the association between the PPAT volume and the prognosis of PCa patients after LRP. We retrospectively analysed data of 189 PCa patients who underwent LRP in Beijing Chaoyang Hospital. Volumes of PPAT and prostate were measured by magnetic resonance imaging (MRI), and normalized PPAT volume was computed (PPAT volume divided by prostate volume). Patients were then stratified into the high-PPAT group ( n = 95) and low-PPAT group ( n = 94) by the median of normalized PPAT volume (73%). The high-PPAT group had significantly higher Gleason score (total score 8 or more, 39.0% vs. 4.3%, p < 0.001) and pathological stage (stage T3b, 28.4% vs. 13.8%, p = 0.048). No significant correlation between normalized PPAT volume and body mass index (ρ = −0.012, p = 0.872) was observed. Kaplan-Meier curve analysis showed the high-PPAT group had significantly shorter biochemical recurrence (BCR) interval (median progression-free survival time 15.9 months vs. 32.7 months, p = 0.001). Univiarate and multivariate Cox regression analyses showed high normalized PPAT volume (>73%) (hazard ratio 1.787 [1.075–3.156], p = 0.002) were independent risk factors for BCR post-operatively. In conclusion, MRI-measured PPAT volume is of significant prognostic value for PCa patients undergoing LRP.

In this study, we retrospectively evaluated the data of 901 men undergoing ultrasonography-guided systematic prostate biopsy between March 2013 and May 2022. Adipose features, including periprostatic adipose tissue (PPAT) thickness and subcutaneous fat thickness, were measured using MRI before biopsy. Prediction models of all PCa and clinically significant PCa (csPCa) (Gleason score higher than 6) were established based on variables selected by multivariate logistic regression and prediction nomograms were constructed. Patients with PCa had higher PPAT thickness (4.64 [3.65–5.86] vs. 3.54 [2.49–4.51] mm, p < 0.001) and subcutaneous fat thickness (29.19 [23.05–35.95] vs. 27.90 [21.43–33.93] mm, p = 0.013) than those without PCa. Patients with csPCa had higher PPAT thickness (4.78 [3.80–5.88] vs. 4.52 [3.80–5.63] mm, p = 0.041) than those with non-csPCa. Adding adipose features to the prediction models significantly increased the area under the receiver operating characteristics curve for the prediction of all PCa (0.850 vs . 0.819, p < 0.001) and csPCa (0.827 vs . 0.798, p < 0.001). Based on MRI-measured adipose features and clinical parameters, we established two nomograms that were simple to use and could improve patient selection for prostate biopsy in Chinese population.

Background: Bone was the most common site of metastasis in prostate cancer(PCa) patients and was correlated with poor prognosis and increasing economicalburden. Studies were limited on the prognostic prediction for metastatic PCapatients with the assistance of neural network. Methods: Four convolutional neural network (CNN) models were developed andevaluated to predict overall survival (OS) of PCa patients with bone metastasis.All the CNN models were first trained with 64 samples and evaluated with 10samples, two models used only bone scan images and two models used both bonescan images and clinical parameters (CPs). Predictions of the best models werecompared with those of two urology surgeons on 20 test samples. Results: Our best models could predict OS of PCa patients with bone metastasiswith AUC = 0.8022 by using only bone scan images and AUC = 0.8132 by usingboth bone scan image and CPs on 20 test samples. When the sensitivities(specificities) set equal to average level of urology surgeons, their specificities(sensitivities) were 0%(7.2%) and 30.77%(7.7%) higher, which showedsignificant advantages of CNN models. Conclusion: The CNN models were suitable to predict OS in PCa patients withbone metastasis using bone scan images and CPs. Our models showed betterperformance in terms of accuracy and stability than urology surgeons. Keywords: Bone Metastasis; Bone Scan; Convolutional Neural Network;Prostate Cancer; Overall Survival

Background Skull is a relatively rare metastasis site for prostate cancer (PCa). There is no evidence regarding the prognostic indication of skull metastasis (SM) in PCa patients. In this study, we analyzed the prognostic value of SM for metastatic PCa patients receiving androgen deprivation therapy (ADT). Methods 107 consecutive patients were included from September 2008 to August 2021. All patients were administered with standard ADT. Abiraterone plus glucocorticoid and/or docetaxel chemotherapy were given after failure to castration-resistant prostate cancer. Clinical parameters and follow-up prognostic data were retrospectively analyzed. The association of clinical and pathological parameters with SM were analyzed. The progression-free survival (PFS) and overall survival (OS) were assessed using Kaplan–Meier analysis and Cox regression analyses. Results Patients with SM (n = 26) had significantly higher biopsy Gleason scores, higher clinical T stage, higher prostate-specific antigen level at diagnosis, and were more likely to have high-burden metastasis and lymph node metastasis, compared with those without SM (n = 81). They also showed significantly lower level of hemoglobin, albumin and serum calcium, along with higher level of alkaline phosphatase. SM was significantly associated with shorter medium PFS (9.4 vs. 18.3 months, p < 0.001) and OS (22.2 vs. 58.2 months, p < 0.001). Cox analysis demonstrated that SM was an independent risk factor for shorter PFS (hazard ratio 2.327 [1.429–3.789], p = 0.001) and shorter OS (hazard ratio 2.810 [1.615–4.899], p < 0.001). Conclusion In this study, we found that SM was significantly correlated with more aggressive disease and indicated poor prognosis in PCa patients with bone metastasis. Our study may provide useful reference for the risk stratification of PCa patients.