Background: This study aims to establish the value of apparent diffusion coefficient maps and other magnetic resonance sequences for active surveillance of prostate cancer. The study included 530 men with an average age of 66, who were under surveillance for prostate cancer. We have used multiparametric magnetic resonance imaging with subsequent transperineal biopsy (TPB) to verify the imaging findings. Results: We have observed a level of agreement of 67.30% between the apparent diffusion coefficient (ADC) maps, other magnetic resonance sequences, and the biopsy results. The sensitivity of the apparent diffusion coefficient is 97.14%, and the specificity is 37.50%. According to our data, apparent diffusion coefficient is the most accurate sequence, followed by diffusion imaging in prostate cancer detection. Conclusions: Based on our findings we advocate that the apparent diffusion coefficient should be included as an essential part of magnetic resonance scanning protocols for prostate cancer in at least bi-parametric settings. The best option will be apparent diffusion coefficient combined with diffusion imaging and T2 sequences. Further large-scale prospective controlled studies are required to define the precise role of multiparametric and bi-parametric magnetic resonance in the active surveillance of prostate cancer. Full article

Background: To assess the performance of prospectively accelerated and deep learning (DL) reconstructed T2-weighted (T2w) imaging in volunteers and patients with histologically proven prostate cancer (PCa). Methods: Prospectively undersampled T2w datasets were acquired with acceleration factors of 1.7 (reference), 3.4 and 4.8 in 10 healthy volunteers and 23 patients with histologically proven PCa. Image reconstructions using compressed SENSE (C-SENSE) and a combination of C-SENSE and DL-based artificial intelligence (C-SENSE AI) were analyzed. Qualitative image comparison was performed using a 6-point Likert scale (overall image quality, noise, motion artifacts, lesion detection, diagnostic certainty); the T2 and PI-RADS scores were compared between the two reconstructions. Additionally, quantitative image parameters were assessed (apparent SNR, apparent CNR, lesion size, line profiles). Results: All C-SENSE AI-reconstructed images received a significantly higher qualitative rating compared to the C-SENSE standard images. Analysis of the quantitative parameters supported this finding, with significantly higher aSNR and aCNR. The line profiles demonstrated a significantly steeper signal change at the border of the prostatic lesion and the adjacent normal tissue in the C-SENSE AI-reconstructed images, whereas the T2 and PI-RADS scores as well as the lesion size did not differ. Conclusion: In this prospective study, we demonstrated the clinical feasibility of a novel C-SENSE AI reconstruction enabling a 58% acceleration in T2w imaging of the prostate while obtaining significantly better image quality. Full article

A predictive model including age, PCa family history, biopsy status (initial vs repeat), DRE (normal vs abnormal), serum prostate-specific antigen (PSA), and DRE prostate volume ca-tegory was developed to stratify initial PCa suspicion in 1486 men with PSA > 3 ng/mL and/or abnormal DRE, in whom mpMRI followed; 2- to 4-core TRUS-guided biopsies where Prostate Imaging Report and Data System (PI-RADS) > 3 lesions and/or 12-core TRUS systematic biopsies were performed in one academic institution between 1 January 2016–31 December 2019. The csPCa detection rate, defined as International Society of Uro-Pathology grade group 2 or higher, was 36.9%. An external validation of designed BCN-RC 1 was carried out on 946 men from two other institutions in the same metropolitan area, using the same criteria of PCa suspicion and diagnostic approach, yielded a csPCa detection rate of 40.8%. The areas under the receiver operating characteristic curves of BCN-RC 1 were 0.823 (95% CI: 0.800–0.846) in the development cohort and 0.837 (95% CI: 0.811–0.863) in the validation cohort (p = 0.447). In both cohorts, BCN-RC 1 exhibited net benefit over performing mpMRI in all men from 8 and 12% risk thresholds, respectively. At 0.95 sensitivity of csPCa, the specificities of BCN-RC 1 were 0.24 (95% CI: 0.22–0.26) in the development cohort and 0.34 (95% CI: 0.31–0.37) in the validation cohort (p < 0.001). The percentages of avoided mpMRI scans were 17.2% in the development cohort and 22.3% in the validation cohort, missing between 1.8% and 2% of csPCa among men at risk of PCa. In summary, BCN-RC 1 can stratify initial PCa suspicion, reducing the demand of mpMRI, with an acceptable loss of csPCa. Full article

The risk of prostate cancer (PCa) in prostate imaging reporting and data system version 2 (PI-RADSv2) score-3 lesions is equivocal; it is regarded as an intermediate status of presented PCa. In this study, we evaluated the clinical utility of the prostate health index (PHI) for the diagnosis of PCa and clinically significant PCa (csPCa) in patients with PI-RADSv2 score-3 lesions. The study cohort included patients who underwent a transrectal ultrasound (TRUS)-guided, cognitive-targeted biopsy for PI-RADSv2 score-3 lesions between November 2018 and April 2021. Before prostate biopsy, the prostate-specific antigen (PSA) derivatives, such as total PSA (tPSA), [-2] proPSA (p2PSA) and free PSA (fPSA) were determined. The calculation equation of PHI is as follows: [(p2PSA/fPSA) × tPSA ½]. Using a receiver operating characteristic (ROC) curve analysis, the values of PSA derivatives measured by the area under the ROC curve (AUC) were compared. For this study, csPCa was defined as Gleason grade 2 or higher. Of the 392 patients with PI-RADSv2 score-3 lesions, PCa was confirmed in 121 (30.9%) patients, including 59 (15.1%) confirmed to have csPCa. Of all the PSA derivatives, PHI and PSA density (PSAD) showed better performance in predicting overall PCa and csPCa, compared with PSA (all p < 0.05). The AUC of the PHI for predicting overall PCa and csPCa were 0.807 (95% confidence interval (CI): 0.710–0.906, p = 0.001) and 0.819 (95% CI: 0.723–0.922, p < 0.001), respectively. By the threshold of 30, PHI was 91.7% sensitive and 46.1% specific for overall PCa, and was 100% sensitive for csPCa. Using 30 as a threshold for PHI, 34.4% of unnecessary biopsies could have been avoided, at the cost of 8.3% of overall PCa, but would include all csPCa. Full article

The correct identification of extracapsular extension (ECE) of prostate cancer (PCa) on multiparametric magnetic resonance imaging (mpMRI) is crucial for surgeons in order to plan the nerve-sparing approach in radical prostatectomy. Nerve-sparing strategies allow for better outcomes in preserving erectile function and urinary continence, notwithstanding this can be penalized with worse oncologic results. The aim of this study was to assess the ability of preoperative mpMRI to predict ECE in the final prostatic specimen (PS) and identify other possible preoperative predictive factors of ECE as a secondary end-point. We investigated a database of two high-volume hospitals to identify men who underwent a prostate biopsy with a pre-biopsy mpMRI and a subsequent RP. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of mpMRI in predicting ECE were calculated. A univariate analysis was performed to find the association between image staging and pathological staging. A multivariate logistic regression was performed to investigate other preoperative predictive factors. A total of 1147 patients were selected, and 203 out of the 1147 (17.7%) patients were classified as ECE according to the mpMRI. ECE was reported by pathologists in 279 out of the 1147 PS (24.3%). The PPV was 0.58, the NPV was 0.72, the sensitivity was 0.32, and the specificity was 0.88. The multivariate analysis found that PSA (OR 1.057, C.I. 95%, 1.016–1.100, p = 0.006), digital rectal examination (OR 0.567, C.I. 95%, 0.417–0.770, p = 0.0001), ratio of positive cores (OR 9.687, C.I. 95%, 3.744–25.006, p = 0.0001), and biopsy grade in prostate biopsy (OR 1.394, C.I. 95%, 1.025–1.612, p = 0.0001) were independent factors of ECE. The mpMRI has a great ability to exclude ECE, notwithstanding that low sensitivity is still an important limitation of the technique. Full article

Radiorecurrent prostate cancer is conventionally confirmed using systematic and/or targeted biopsies. The availability of multiparametric (mp) MRI and prostate specific membrane antigen (PSMA) PET/CT has increased diagnostic accuracy. The objective was to determine the positive predictive value (PPV) of combined mp-MRI and PSMA PET/CT and whether pathology verification with MR-targeted biopsies remains necessary for patients with radiorecurrent prostate cancer. Patients with locally recurrent prostate cancer who were referred for 19 Gy single-dose MRI-guided focal salvage high dose rate (HDR) brachytherapy between 2015 and 2018 were included in the current analysis. Patients were selected if they underwent pre-biopsy mp-MRI and PSMA PET/CT. Based on these images, lesions suspect for isolated tumor recurrence were transperineally biopsied using transrectal ultrasound fused with MRI. A total of 41 patients were identified from the database who underwent cognitive targeted (n = 7) or MRI/PSMA-transrectal ultrasound (TRUS) fused targeted (n = 34) biopsies. A total of 40 (97.6%) patients had positive biopsies for recurrent cancer. Five patients initially had negative biopsies (all MRI/PSMA-TRUS fusion targeted), four of whom recurrence was confirmed after a re-biopsy. One (2.4%) patient refused re-biopsy, leading to a positive predictive value (PPV) for combined imaging of 97.6%. Biopsies can therefore safely be withheld when the results of the combined mp-MRI and PSMA PET/CT are conclusive, avoiding an unnecessary invasive and burdensome procedure. Full article

Prostate-specific membrane antigen (PSMA)-directed positron emission tomography/computed tomography (PET/CT) is increasingly utilized for staging of men with prostate cancer (PC). To increase interpretive certainty, the standardized PSMA reporting and data system (RADS) has been proposed. Using PSMA-RADS, we characterized lesions in 18 patients imaged with ¹⁸F-PSMA-1007 PET/CT for primary staging and determined the stability of semi-quantitative parameters. Six hundred twenty-three lesions were categorized according to PSMA-RADS and manually segmented. In this context, PSMA-RADS-3A (soft-tissue) or -3B (bone) lesions are defined as being indeterminate for the presence of PC. For PMSA-RADS-4 and -5 lesions; however, PC is highly likely or almost certainly present [with further distinction based on absence (PSMA-RADS-4) or presence (PSMA-RADS-5) of correlative findings on CT]. Standardized uptake values (SUV_max, SUV_peak, SUV_mean) were recorded, and volumetric parameters [PSMA-derived tumor volume (PSMA-TV); total lesion PSMA (TL-PSMA)] were determined using different maximum intensity thresholds (MIT) (40 vs. 45 vs. 50%). SUV_max was significantly higher in PSMA-RADS-5 lesions compared to all other PSMA-RADS categories (p ≤ 0.0322). In particular, the clinically challenging PSMA-RADS-3A lesions showed significantly lower SUV_max and SUV_peak compared to the entire PSMA-RADS-4 or -5 cohort (p < 0.0001), while for PSMA-RADS-3B this only applies when compared to the entire PSMA-RADS-5 cohort (p < 0.0001), but not to the PSMA-RADS-4 cohort (SUV_max, p = 0.07; SUV_peak, p = 0.08). SUV_mean (p = 0.30) and TL-PSMA (p = 0.16) in PSMA-RADS-5 lesions were not influenced by changing the MIT, while PSMA-TV showed significant differences when comparing 40 vs. 50% MIT (p = 0.0066), which was driven by lymph nodes (p = 0.0239), but not bone lesions (p = 0.15). SUV_max was significantly higher in PSMA-RADS-5 lesions compared to all other PSMA-RADS categories in ¹⁸F-PSMA-1007 PET/CT. As such, the latter parameter may assist the interpreting molecular imaging specialist in assigning the correct PSMA-RADS score to sites of disease, thereby increasing diagnostic certainty. In addition, changes of the MIT in PSMA-RADS-5 lesions had no significant impact on SUV_mean and TL-PSMA in contrast to PSMA-TV. Full article

Despite the spectacular advances in molecular medicine, including genomics, proteomics, transcriptomics, lipidomics, and personalized medicine, supported by the discovery of the human genome, prostate cancer (PCa) remains the most frequent malignant tumor and a leading cause of oncological death in men. New methods for prognostic, diagnostic, and therapy evaluation are mainly based on the combination of imaging techniques with other methodologies, such as gene or protein profiling, aimed at improving PCa management and surveillance. However, the lack of highly specific and sensitive biomarkers for its early detection is a major hurdle to this goal. Apart from classical biomarkers, the study of endogenous volatile organic metabolites (VOMs) biosynthesized by different metabolic pathways and found in several biofluids is emerging as an innovative, efficient, accessible, and non-invasive approach to establish the volatilomic biosignature of PCa patients, unravelling potential biomarkers. This review provides a brief overview of the challenges of PCa screening methods and emergent biomarkers. We also focus on the potential of volatilomics for the establishment of PCa biomarkers from non-invasive matrices. Full article

Current routine screening methods for the diagnosis of prostate cancer (PCa) have significantly increased early detection of the disease but often show unsatisfactory analytical parameters. A class of promising markers represents urinary microRNAs (miRNAs). In the last five years, there has been an extensive increase in the number of studies on this topic. Thus, this review aims to update knowledge and point out technical aspects affecting urinary miRNA analysis. The review of relevant literature was carried out by searching the PubMed database for the keywords: microRNA, miRNA, urine, urinary, prostate cancer, and diagnosis. Papers discussed in this review were retrieved using PubMed, and the search strategy was as follows: (urine OR urinary) WITH (microRNA OR miRNA) AND prostate cancer. The search was limited to the last 5 years, January 2017 to December 2021. Based on the defined search strategy, 31 original publications corresponding to the research topic were identified, read and reviewed to present the latest findings and to assess possible translation of urinary miRNAs into clinical practice. Reviews or older publications were read and cited if they valuably extended the context and contributed to a better understanding. Urinary miRNAs are potentially valuable markers for the diagnosis of prostate cancer. Despite promising results, there is still a need for independent validation of exploratory data, which follows a strict widely accepted methodology taking into account the shortcomings and factors influencing the analysis. Full article