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Prostate cancer (PCa) is a major cause of death since ancient time documented in Egyptian Ptolemaic mummy imaging. PCa detection is critical to personalized medicine and varies considerably under an MRI scan. 172 patients with 2,602 morphologic images (axial 2D T2-weighted imaging) of the prostate were obtained. A deep learning with deep convolutional neural network (DCNN) and a non-deep learning with SIFT image feature and bag-of-word (BoW), a representative method for image recognition and analysis, were used to distinguish pathologically confirmed PCa patients from prostate benign conditions (BCs) patients with prostatitis or prostate benign hyperplasia (BPH). In fully automated detection of PCa patients, deep learning had a statistically higher area under the receiver operating characteristics curve (AUC) than non-deep learning ( P  = 0.0007 < 0.001). The AUCs were 0.84 (95% CI 0.78–0.89) for deep learning method and 0.70 (95% CI 0.63–0.77) for non-deep learning method, respectively. Our results suggest that deep learning with DCNN is superior to non-deep learning with SIFT image feature and BoW model for fully automated PCa patients differentiation from prostate BCs patients. Our deep learning method is extensible to image modalities such as MR imaging, CT and PET of other organs.

Objectives To explore the associations between T1 and T2 magnetic resonance fingerprinting (MRF) measurements and corresponding tissue compartment ratios (TCRs) on whole mount histopathology of prostate cancer (PCa) and prostatitis. Materials and methods A retrospective, IRB-approved, HIPAA-compliant cohort consisting of 14 PCa patients who underwent 3 T multiparametric MRI along with T1 and T2 MRF maps prior to radical prostatectomy was used. Correspondences between whole mount specimens and MRI and MRF were manually established. Prostatitis, PCa, and normal peripheral zone (PZ) regions of interest (ROIs) on pathology were segmented for TCRs of epithelium, lumen, and stroma using two U-net deep learning models. Corresponding ROIs were mapped to T2-weighted MRI (T2w), apparent diffusion coefficient (ADC), and T1 and T2 MRF maps. Their correlations with TCRs were computed using Pearson’s correlation coefficient ( R ). Statistically significant differences in means were assessed using one-way ANOVA. Results Statistically significant differences ( p  < 0.01) in means of TCRs and T1 and T2 MRF were observed between PCa, prostatitis, and normal PZ. A negative correlation was observed between T1 and T2 MRF and epithelium ( R  = − 0.38, − 0.44, p  < 0.05) of PCa. T1 MRF was correlated in opposite directions with stroma of PCa and prostatitis ( R  = 0.35, − 0.44, p  < 0.05). T2 MRF was positively correlated with lumen of PCa and prostatitis ( R  = 0.57, 0.46, p  < 0.01). Mean T2 MRF showed significant differences ( p  < 0.01) between PCa and prostatitis across both transition zone (TZ) and PZ, while mean T1 MRF was significant ( p  = 0.02) in TZ. Conclusion Significant associations between MRF (T1 in the TZ and T2 in the PZ) and tissue compartments on corresponding histopathology were observed. Key Points • Mean T2 MRF measurements and ADC within cancerous regions of interest dropped with increasing ISUP prognostic groups (IPG). • Mean T1 and T2 MRF measurements were significantly different (p < 0.001) across IPGs, prostatitis, and normal peripheral zone (NPZ). • T2 MRF showed stronger correlations in the peripheral zone, while T1 MRF showed stronger correlations in the transition zone with histopathology for prostate cancer.

PurposePurpose of this study is to evaluate the diagnostic accuracy of quantitative T2/ADC values in differentiating between PCa and lesions showing non-specific inflammatory infiltrates and atrophy, features of chronic prostatitis, as the most common histologically proven differential diagnosis.MethodsIn this retrospective, single-center cohort study, we analyzed 55 patients suspected of PCa, who underwent mpMRI (3T) including quantitative T2 maps before robot-assisted mpMRI-TRUS fusion prostate biopsy. All prostate lesions were scored according to PI-RADS v2.1. Regions of interest (ROIs) were annotated in focal lesions and normal prostate tissue. Quantitative mpMRI values from T2 mapping and ADC were compared using two-tailed t tests. Receiver operating characteristic curves (ROCs) and cutoff were calculated to differentiate between PCa and chronic prostatitis.ResultsFocal lesions showed significantly lower ADC and T2 mapping values than normal prostate tissue (p < 0.001). PCa showed significantly lower ADC and T2 values than chronic prostatitis (p < 0.001). ROC analysis revealed areas under the receiver operating characteristic curves (AUCs) of 0.85 (95% CI 0.74–0.97) for quantitative ADC values and 0.84 (95% CI 0.73–0.96) for T2 mapping. A significant correlation between ADC and T2 values was observed (r = 0.70; p < 0.001).ConclusionT2 mapping showed high diagnostic accuracy for differentiating between PCa and chronic prostatitis, comparable to the performance of ADC values.

To investigate the multiparametric magnetic resonance imaging (mpMRI) characteristics of granulomatous prostatitis (GP) and share our experience with 31 pathologically confirmed GP lesions in 19 patients. This two-center retrospective study reviewed the pathological and imaging data of 856 patients who underwent prostate biopsy between January 2012 and April 2024. Of these, 19 patients with available prebiopsy mpMRI and a pathologically confirmed diagnosis of GP were included. Additionally, 280 biopsy-naïve patients diagnosed with clinically significant prostate cancer (csPCa) were included as a control group for comparative analysis. Prebiopsy mpMR images of patients with GP were assessed by consensus between two of three radiologists (M.V., B.C., S.D.), evaluating lesion location, size, shape, multifocality, extraprostatic extension (EPE), signal characteristics on T1-, T2-, and diffusion-weighted imaging (DWI), the mean apparent diffusion coefficient (ADC ) value, enhancement patterns, and prostate imaging reporting and data system (PI-RADS) scores. Statistical analyses were conducted using SPSS version 30.0. In 19 patients, 31 pathologically confirmed GP lesions were identified on prebiopsy mpMRI. Twenty-six lesions were located in the peripheral zone and five in the transitional zone. Multifocal involvement was observed in nine patients (47.3%). Thirty of 31 lesions were hypointense on T2-WI, and seven showed capsular bulging and/or irregularity, suggesting EPE. DWI revealed markedly impeded diffusion in all lesions. The median ADC value was 825 × 10 mm /s (IQR: 230 × 10 mm /s). On dynamic contrast-enhanced sequences, 25 lesions showed early enhancement, five showed prolonged enhancement, and one showed prolonged ring enhancement. Based on mpMRI findings, 17 lesions were assigned a PI-RADS score of 4, and 13 lesions were assigned a PI-RADS score of 5. Notably, 22 lesions (71%) in 14 patients with GP (73.7%) exhibited hyperintensity on T1-WI despite no prior prostate biopsy history. Statistical analysis comparing the GP and csPCa groups revealed that hyperintensity on T1-WI was significantly more frequent in GP, both on a per-patient basis (73.7% vs. 3.2%) and a per-lesion basis (71.0% vs. 3.1%) ( < 0.0001 for both). GP shares overlapping imaging features with prostate cancer on mpMRI. However, hyperintensity on T1-WI may serve as a distinguishing feature, potentially reducing unnecessary prostate interventions. Radiologists should consider GP in PI-RADS ≥4 lesions exhibiting T1-WI hyperintensity. Furthermore, given the high incidence of GP following intravesical Bacillus Calmette-Guérin (BCG) therapy, a thorough history of BCG treatment should be obtained. GP is recognized for its tendency to mimic PCa on mpMRI, a finding corroborated by this study. However, T1-WI hyperintensity emerged as a promising distinguishing feature for GP. Incorporating this marker into mpMRI interpretation criteria may help reduce unnecessary prostate interventions and improve patient outcomes.

PurposeAimed to investigate the role of multiparametric magnetic resonance imaging (mp-MRI) in the diagnosis of granulomatous prostatitis caused by intravesical Bacillus Calmette–Guérin (BCG).MethodsIn this prospective, single-center study, 10 male patients who were given intravesical BCG due to intermediate- and high-risk bladder cancer were included. Before transurethral resection of bladder tumors (TURB), all patients were evaluated by mp-MRI, serum prostate-specific antigen (PSA), and digital rectal examination (DRE). Serum PSA levels and DRE findings were evaluated before and after intravesical BCG treatment. Prostate mp-MRI was performed for patients with elevated levels of serum PSA and/or with abnormal DRE findings. Then, MRI fusion + systematic prostate biopsy was performed. Demographic data of the patients before and after intravesical BCG were compared.ResultsThe average age of the patients was 66.9 years (55–87 years). While PSA was 1.7 ng/ml before intravesical BCG treatment, it was 4.3 ng/ml after intravesical BCG treatment (p = 0.005). PSA density (PSAD) was 0.04 and 0.10 before and after the treatment, respectively (p = 0.012). DRE findings of all patients were normal before the treatment. However, abnormal findings were detected in 80% of them after the treatment (p = 0.008). PI-RADS ≥ 3 lesions were found to be significantly higher in all patients after intravesical BCG (p = 0.004).ConclusionGranulomatous prostatitis is a rare complication of intravesical BCG. High PSA, abnormal DRE, and PI-RADS ≥ 3 lesions detected after intravesical BCG should suggest granulomatous prostatitis and unnecessary biopsies may be avoided.

Evidence shows that chronic prostatitis/chronic pelvic pain syndrome hugely impacts the body and mind. The central mechanisms in patients with CP/CPPS resulted in increased attention as neuroimaging techniques developed. This review investigated the study design and major neuroimaging findings in CP/CPPS patients to provide comprehensive evidence. Seven databases were searched and screened: PubMed, EMBASE/SCOPUS, Cochrane Library Database, China National Knowledge Infrastructure, VIP, Wanfang, and China Biology Medicine disc. Nine studies were eventually included in the analysis. The results demonstrate that the insula, anterior cingulate gyrus, postcentral gyrus, and precuneus are significantly associated with CP/CPPS patients’ pain feelings and cause dysregulation of painful emotions, lowering patients’ tolerance to stimulus.

Prostatitis is frequently observed in false-positive lesions scored as 5 in the Prostate Imaging Reporting and Data System (PI-RADS), necessitating improved diagnostic tools. This study investigated the potential of magnetic resonance imaging (MRI) texture analysis of apparent diffusion coefficient (ADC) sequences to enhance the differentiation of prostatitis from prostate cancer (PCa) in PI-RADS 5 lesions. This retrospective study enrolled patients undergoing 3.0-T MRI with lesions scored as PI-RADS 5. Lesions were manually delineated on ADC maps, and texture features were extracted using FireVoxel. Clinical data and ADC texture parameters were collected. The diagnostic performance [area under the curve (AUC), sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV)] of the clinical data, ADC texture, and a combined model were calculated and compared using the DeLong test. The final cohort included 189 patients with 189 PI-RADS 5 lesions (164 PCa, 25 prostatitis). The combined model, incorporating clinical indicators (age, prostate-specific antigen density) and ADC texture parameters (signal coefficient of variation, ADC percentile), revealed the optimal diagnostic performance: SEN 98.7%, SPE 60.0%, PPV 97.9%, NPV 71.6%, and AUC 93.1%. Bootstrap resampling verified the robustness of the model. Decision curve analysis indicated an improved net benefit with the combined model for guiding biopsy decisions. ADC imaging texture parameters are valuable for the differential diagnosis of prostatitis from lesions scored as PI-RADS 5. Their combination with clinical indicators substantially improves diagnostic performance, providing valuable information to facilitate surgical decision-making and potentially reduce unnecessary biopsies. This study addresses a critical limitation of the current PI-RADS system, which exhibits a notable rate of false positives in high-risk PI-RADS 5 lesions. By demonstrating the added value of quantitative ADC texture analysis in this specific diagnostic challenge, this research offers a practical and potentially translatable approach to reducing the number of unnecessary biopsies for PI-RADS 5 lesions.

Xanthogranulomatous prostatitis (XGP) is a rare inflammatory condition that can closely mimic prostate adenocarcinoma both clinically and radiologically. We report the case of a man in his mid-60s who presented with pelvic discomfort, dysuria, reduced urine flow and fever. He had an elevated prostate-specific antigen (PSA) level of 17.5 ng/mL and abnormal findings on digital rectal examination. Multi-parametric MRI of the prostate revealed a prostate lesion suspicious for malignancy invading the rectal wall and right obturator internus muscle. However, transperineal prostate biopsies confirmed XGP with no evidence of cancer. The patient was treated with a 4-month course of ciprofloxacin, which resolved most of his symptoms, and alpha-blocker therapy was commenced to improve urine flow. This case emphasises the diagnostic challenges posed by XGP, which can mimic T4 prostate cancer and potentially lead to overtreatment. Awareness of this condition, along with systematic diagnostic strategies, is essential to avoid unnecessary interventions and optimise patient management.

To categorize multiparametric MRI features of Bacillus Calmette-Guérin (BCG)-related granulomatous prostatitis (GP) and discover potential manifestations for its differential diagnosis from prostate cancer. The cases of BCG-related GP in 24 male (mean age ± standard deviation, 66.0 ± 9.4 years; range, 50-88 years) pathologically confirmed between January 2011 and April 2019 were retrospectively reviewed. All patients underwent intravesical BCG therapy followed by a MRI scan. Additional follow-up MRI scans, including diffusion-weighted imaging (DWI), were performed in 19 patients. The BCG-related GP cases were categorized into three: A, B, or C. The lesions with diffusion restriction and homogeneous enhancement were classified as type A. The lesions with diffusion restriction and a poorly enhancing component were classified as type B. A low signal intensity on high b-value DWI (b = 1000 s/mm²) was considered characteristic of type C. Two radiologists independently interpreted the MRI scans before making a consensus about the types. The median lesion size was 22 mm with the interquartile range (IQR) of 18-26 mm as measured using the initial MRI scans. The lesion types were A, B, and C in 7, 15, and 2 patients, respectively. Cohen's kappa value for the inter-reader agreement for the interpretation of the lesion types was 0.837. On the last follow-up MRI scans of 19 patients, the size decreased (median, 5.8 mm; IQR, 3.4-8.5 mm), and the type changed from A or B to C in 11 patients. The lesions resolved in four patients. In five patients who underwent prostatectomy, caseous necrosis on histopathology matched with the non-enhancing components of type B lesions and the entire type C lesions. BCG-related GP demonstrated three imaging patterns on multiparametric MRI. Contrast-enhanced T1-weighted imaging and DWI may play a role in its differential diagnosis from prostate cancer.

The link between the microbiome and cancer has led researchers to search for a potential probe for intracellular targeting of bacteria and cancer. Herein, we developed near infrared-emitting ternary AgInSe/ZnS quantum dots (QDs) for dual bacterial and cancer imaging. Briefly, water-soluble AgInSe/ZnS QDs were synthesized in a commercial kitchen pressure cooker. The as-synthesized QDs exhibited a spherical shape with a particle diameter of 4.5 ± 0.5 nm, and they were brightly fluorescent with a photoluminescence maximum at 705 nm. The QDs showed low toxicity against mouse mammary carcinoma (FM3A-Luc), mouse colon carcinoma (C26), malignant fibrous histiocytoma-like (KM-Luc/GFP) and prostate cancer cells, a greater number of accumulations in Staphylococcus aureus, and good cellular uptake in prostate cancer cells. This work is an excellent step towards using ternary QDs for diagnostic and guided therapy for prostate cancer.