Magnetic resonance (MR) imaging is an important tool for prostate cancer diagnosis, and accurate segmentation of MR prostate regions by computer-aided diagnostic techniques is important for the diagnosis of prostate cancer. In this paper, we propose an improved end-to-end three-dimensional image segmentation network using a deep learning approach to the traditional V-Net network (V-Net) network in order to provide more accurate image segmentation results. Firstly, we fused the soft attention mechanism into the traditional V-Net's jump connection, and combined short jump connection and small convolutional kernel to further improve the network segmentation accuracy. Then the prostate region was segmented using the Prostate MR Image Segmentation 2012 (PROMISE 12) challenge dataset, and the model was evaluated using the dice similarity coefficient (DSC) and Hausdorff distance (HD). The DSC and HD values of the segmented model could reach 0.903 and 3.912 mm, respectively. The experimental results show that the algorithm in this paper can provide more accurate three-dimensional segmentation results, which can accurately and efficiently segment prostate MR images and provide a reliable basis for clinical diagnosis and treatment.
Male ; Humans ; Prostate/diagnostic imaging* ; Image Processing, Computer-Assisted/methods* ; Magnetic Resonance Imaging/methods* ; Imaging, Three-Dimensional/methods* ; Prostatic Neoplasms/diagnostic imaging*

This study explored a new model of Prostate Imaging Reporting and Data System (PIRADS) and adjusted prostate-specific antigen density of peripheral zone (aPSADPZ) for predicting the occurrence of prostate cancer (PCa) and clinically significant prostate cancer (csPCa). The demographic and clinical characteristics of 853 patients were recorded. Prostate-specific antigen (PSA), PSA density (PSAD), PSAD of peripheral zone (PSADPZ), aPSADPZ, and peripheral zone volume ratio (PZ-ratio) were calculated and subjected to receiver operating characteristic (ROC) curve analysis. The calibration and discrimination abilities of new nomograms were verified with the calibration curve and area under the ROC curve (AUC). The clinical benefits of these models were evaluated by decision curve analysis and clinical impact curves. The AUCs of PSA, PSAD, PSADPZ, aPSADPZ, and PZ-ratio were 0.669, 0.762, 0.659, 0.812, and 0.748 for PCa diagnosis, while 0.713, 0.788, 0.694, 0.828, and 0.735 for csPCa diagnosis, respectively. All nomograms displayed higher net benefit and better overall calibration than the scenarios for predicting the occurrence of PCa or csPCa. The new model significantly improved the diagnostic accuracy of PCa (0.945 vs 0.830, P < 0.01) and csPCa (0.937 vs 0.845, P < 0.01) compared with the base model. In addition, the number of patients with PCa and csPCa predicted by the new model was in good agreement with the actual number of patients with PCa and csPCa in high-risk threshold. This study demonstrates that aPSADPZ has a higher predictive accuracy for PCa diagnosis than the conventional indicators. Combining aPSADPZ with PIRADS can improve PCa diagnosis and avoid unnecessary biopsies.
Male ; Humans ; Prostate/pathology* ; Prostate-Specific Antigen/analysis* ; Prostatic Neoplasms/diagnostic imaging* ; Biopsy ; Nomograms ; Retrospective Studies

The purpose of this study was to analyze the value of transrectal shear-wave elastography (SWE) in combination with multivariable tools for predicting adverse pathological features before radical prostatectomy (RP). Preoperative clinicopathological variables, multiparametric magnetic resonance imaging (mp-MRI) manifestations, and the maximum elastic value of the prostate (Emax) on SWE were retrospectively collected. The accuracy of SWE for predicting adverse pathological features was evaluated based on postoperative pathology, and parameters with statistical significance were selected. The diagnostic performance of various models, including preoperative clinicopathological variables (model 1), preoperative clinicopathological variables + mp-MRI (model 2), and preoperative clinicopathological variables + mp-MRI + SWE (model 3), was evaluated with area under the receiver operator characteristic curve (AUC) analysis. Emax was significantly higher in prostate cancer with extracapsular extension (ECE) or seminal vesicle invasion (SVI) with both P < 0.001. The optimal cutoff Emax values for ECE and SVI were 60.45 kPa and 81.55 kPa, respectively. Inclusion of mp-MRI and SWE improved discrimination by clinical models for ECE (model 2 vs model 1, P = 0.031; model 3 vs model 1, P = 0.002; model 3 vs model 2, P = 0.018) and SVI (model 2 vs model 1, P = 0.147; model 3 vs model 1, P = 0.037; model 3 vs model 2, P = 0.134). SWE is valuable for identifying patients at high risk of adverse pathology.
Male ; Humans ; Prostate/pathology* ; Seminal Vesicles/diagnostic imaging* ; Elasticity Imaging Techniques ; Retrospective Studies ; Extranodal Extension/pathology* ; Neoplasm Staging ; Prostatectomy/methods* ; Prostatic Neoplasms/pathology* ; Magnetic Resonance Imaging/methods*

Prostate cancer (PCa) is a pernicious tumor with high heterogeneity, which creates a conundrum for making a precise diagnosis and choosing an optimal treatment approach. Multiparametric magnetic resonance imaging (mp-MRI) with anatomical and functional sequences has evolved as a routine and significant paradigm for the detection and characterization of PCa. Moreover, using radiomics to extract quantitative data has emerged as a promising field due to the rapid growth of artificial intelligence (AI) and image data processing. Radiomics acquires novel imaging biomarkers by extracting imaging signatures and establishes models for precise evaluation. Radiomics models provide a reliable and noninvasive alternative to aid in precision medicine, demonstrating advantages over traditional models based on clinicopathological parameters. The purpose of this review is to provide an overview of related studies of radiomics in PCa, specifically around the development and validation of radiomics models using MRI-derived image features. The current landscape of the literature, focusing mainly on PCa detection, aggressiveness, and prognosis evaluation, is reviewed and summarized. Rather than studies that exclusively focus on image biomarker identification and method optimization, models with high potential for universal clinical implementation are identified. Furthermore, we delve deeper into the critical concerns that can be addressed by different models and the obstacles that may arise in a clinical scenario. This review will encourage researchers to design models based on actual clinical needs, as well as assist urologists in gaining a better understanding of the promising results yielded by radiomics.
Male ; Humans ; Artificial Intelligence ; Magnetic Resonance Imaging/methods* ; Prostatic Neoplasms/diagnostic imaging* ; Image Processing, Computer-Assisted/methods* ; Precision Medicine ; Retrospective Studies

OBJECTIVE: To investigate the diagnostic efficacy of targeted biopsy (TBx), systematic biopsy (SBx), TBx+6-core SBx in prostate cancer (PCa) / clinically significant prostate cancer (cs-PCa) for patients with prostate imaging reporting and data system (PI-RADS) score of 5, and thereby to explore an optimal sampling scheme. METHODS: The data of 585 patients who underwent multiparametric magnetic resonance imaging (mpMRI) with at least one lesion of PI-RADS score 5 at Peking University First Hospital from January 2019 to June 2022 were retrospectively analyzed. All patients underwent mpMRI / transrectal ultrasound (TRUS) cognitive guided biopsy (TBx+SBx). With the pathological results of combined biopsy as the gold standard, we compared the diagnostic efficacy of TBx only, SBx only, and TBx+6-core SBx for PCa/csPCa. The patients were grouped according to mpMRI T-stage (cT2, cT3, cT4) and the detection rates of different biopsy schemes for PCa/csPCa were compared using Cochran's Q and McNemar tests. RESULTS: Among 585 patients with a PI-RADS score of 5, 560 (95.7%) were positive and 25(4.3%) were negative via TBx+SBx. After stratified according to mpMRI T-stage, 233 patients (39.8%) were found in cT2 stage, 214 patients (36.6%) in cT3 stage, and 138 patients (23.6%) in cT4 stage. There was no statistically significant difference in the detection rate of PCa/csPCa between TBx+6-core SBx and TBx+SBx (all P>0.999). Also, there was no statistically significant difference in the detection rate of PCa/csPCa between TBx and TBx+SBx in the cT2, cT3, and cT4 subgroups (PCa: P=0.203, P=0.250, P>0.999; csPCa: P=0.700, P=0.250, P>0.999). The missed diagnosis rate of SBx for PCa and csPCa was 2.1% (12/560) and 1.8% (10/549), and that of TBx for PCa and csPCa was 1.8% (10/560) and 1.4% (8/549), respectively. However, the detection rate of TBx+6-core SBx for PCa and csPCa was 100%. Compared with TBx+SBx, TBx and TBx+6-core SBx had a fewer number of cores and a higher detection rate per core (P < 0.001). CONCLUSION For patients with a PI-RADS score of 5, TBx and TBx+6-core SBx showed the same PCa/csPCa detection rates and a high detection rates per core as that of TBx+SBx, which can be considered as an optimal scheme for prostate biopsy.
Male ; Humans ; Prostatic Neoplasms/pathology* ; Magnetic Resonance Imaging/methods* ; Retrospective Studies ; Prostate/diagnostic imaging* ; Image-Guided Biopsy/methods*

To efficiently remove all recurrent lymph nodes (rLNs) and minimize complications, we developed a combination approach that consisted of ⁶⁸Gallium prostate-specific membrane antigen (PSMA) ligand positron emission tomography (PET)/computed tomography (CT) and integrated indocyanine green (ICG)-guided salvage lymph node dissection (sLND) for rLNs after radical prostatectomy (RP). Nineteen patients were enrolled to receive such treatment. ⁶⁸Ga-PSMA ligand PET/CT was used to identify rLNs, and 5 mg of ICG was injected into the space between the rectum and bladder before surgery. Fluorescent laparoscopy was used to perform sLND. While extensive LN dissection was performed at level I, another 5 mg of ICG was injected via the intravenous route to intensify the fluorescent signal, and laparoscopy was introduced to intensively target stained LNs along levels I and II, specifically around suspicious LNs, with ⁶⁸Ga-PSMA ligand PET/CT. Next, both lateral peritonea were exposed longitudinally to facilitate the removal of fluorescently stained LNs at levels III and IV. In total, pathological analysis confirmed that 42 nodes were rLNs. Among 145 positive LNs stained with ICG, 24 suspicious LNs identified with ⁶⁸Ga-PSMA ligand PET/CT were included. The sensitivity and specificity of ⁶⁸Ga-PSMA ligand PET/CT for detecting rLNs were 42.9% and 96.6%, respectively. For ICG, the sensitivity was 92.8% and the specificity was 39.1%. At a median follow-up of 15 (interquartile range [IQR]: 6-31) months, 15 patients experienced complete biochemical remission (BR, prostate-specific antigen [PSA] <0.2 ng ml^-1), and 4 patients had a decline in the PSA level, but it remained >0.2 ng ml^-1. Therefore, ⁶⁸Ga-PSMA ligand PET/CT integrating ICG-guided sLND provides efficient sLND with few complications for patients with rLNs after RP.
Gallium Isotopes ; Gallium Radioisotopes ; Humans ; Indocyanine Green ; Ligands ; Lymph Node Excision ; Lymphatic Metastasis/diagnostic imaging* ; Male ; Neoplasm Recurrence, Local/surgery* ; Positron Emission Tomography Computed Tomography ; Prostate ; Prostatectomy ; Prostatic Neoplasms/surgery* ; Salvage Therapy

Prostate cancer is the most common malignant tumor in male urinary system, and the morbidity and mortality rate are increasing year by year. Traditional imaging examinations have some limitations in the diagnosis of prostate cancer, and the advent of molecular imaging probes and imaging technology have provided new ideas for the integration of diagnosis and treatment of prostate cancer. In recent years, prostate-specific membrane antigen (PSMA) has attracted much attention as a target for imaging and treatment of prostate cancer. PSMA ligand positron emission tomography (PET) has important reference value in the diagnosis, initial staging, detection of biochemical recurrence and metastasis, clinical decision-making guidance and efficacy evaluation of prostate cancer. This article briefly reviews the clinical research and application progress on PSMA ligand PET imaging in prostate cancer in recent years, so as to raise the efficiency of clinical applications.
Male ; Humans ; Prostate/pathology* ; Ligands ; Positron Emission Tomography Computed Tomography/methods* ; Prostatic Neoplasms/diagnostic imaging* ; Positron-Emission Tomography

Magnetic resonance imaging (MRI) is a very important imaging method for diagnosis and treatment of prostate cancer (PCa) in clinical practice. As functional MRI is growing and maturing, its quantitative parameters are expected to enhance the clinical value of MRI furtherly. Intravoxel incoherent motion diffusion imaging, diffusion tensor imaging, and diffusion kurtosis imaging, which were derived from diffusion weighted imaging, have provided richer and more accurate parameters. The newly-developed magnetic resonance elastography can complement the mechanical characteristics of PCa.
Diffusion Magnetic Resonance Imaging ; Diffusion Tensor Imaging ; Humans ; Magnetic Resonance Imaging ; Male ; Motion ; Prostatic Neoplasms/diagnostic imaging*

Objective: To investigate the risk factors for clinically significant PCa diagnosed by transrectal ultrasound-guided systematic prostate biopsy in patients with MRI-negative and PSA-abnormal findings. METHODS: From January 2014 to December 2017, 335 male patients with MRI-negative (PI-RADS 2.0 score ≤ 2) and PSA-abnormal (4－30 ng/ml ) findings underwent systematic prostate biopsy guided by transrectal ultrasound under local anesthesia in our department. We collected and analyzed the demographic data, clinical symptoms, complications, past history and PSA density (PSAD) of the patients. RESULTS: Clinically significant PCa was diagnosed in 21 (6.3%) of the 335 patients. Multivariate logistic regression analysis showed that the independent risk factors were higher age (AUC: 0.704, P < 0.01) and PSAD (AUC: 0.743, P < 0.01). The cutoff values of age and PSAD were 71 years and 0.18 ng/ml/ml, respectively. CONCLUSIONS Higher age and PSAD are risk factors for clinically significant PCa. Prostate biopsy, even repeated or saturated puncture, is recommended for those aged >71 years old or with PSAD >0.18 ng/ml/ml so as to avoid missed diagnosis and unnecessary invasive biopsy as well. /.
Aged ; Humans ; Magnetic Resonance Imaging ; Male ; Prostate-Specific Antigen ; Prostatic Neoplasms/diagnostic imaging* ; Risk Factors

The diagnosis of bone metastasis of prostate cancer (PC) is of great significance to the treatment and prognosis of patients with PC.Bone scan is the most commonly used in the early diagnosis of bone metastasis, but its specificity is low and there is a high false positive.In recent years, with the in-depth study of the application of CT, MRI, emission computed tomography (ECT), positron emission computed tomography/computed tomography (PET/CT) and deep learning algorithm-convolutional neural networks (CNN) in the diagnosis of bone metastasis, the combined application of various auxiliary parameters in the diagnosis of bone metastasis has significantly been improved. The therapeutic effect of PC patients with bone metastasis can also be evaluated, which is expected to achieve the treatment of bone metastasis as well as diagnosis. By systematically expounding the research progress of the above-mentioned techniques in the diagnosis of bone metastasis, it can provide clinicians with new methods for the diagnosis of bone metastasis and improve the diagnostic efficiency for bone metastasis.
Bone Marrow Diseases ; Bone Neoplasms/diagnostic imaging* ; Humans ; Magnetic Resonance Imaging ; Male ; Positron Emission Tomography Computed Tomography ; Prostatic Neoplasms/diagnostic imaging*