Value of perilesional biopsies in multiparametric magnetic resonance imaging-targeted biopsy and systematic biopsy in detection of prostate cancer: results of a prospective, non-randomized, surgeon-blinded study.

PURPOSE: The goal of this study is to address if detection rates of clinically significant prostate cancer (csPCa) can be increased by additional perilesional biopsies (PB) in magnetic resonance (MR)/ultrasound fusion prostate biopsy in biopsy-naïve men. METHODS: This prospective, non-randomized, surgeon-blinded study was conducted between February 2020 and July 2022. Patients were included with PSA levels < 20 ng/ml and ≥ one PI-RADS lesion (grades 3-5) per prostate lobe. Prostate biopsy was performed by two urologists. The first performed the MR-fusion biopsy with 3-5 targeted biopsies (TB) and 6 PB in a standardized pattern. The second performed the systematic (12-fold) biopsy (SB) without knowledge of the MR images. Primary outcome of this study is absence or presence of csPCa (≥ ISUP grade 2) comparing TB, PB and SB, using McNemar test. RESULTS: Analyses were performed for each PI-RADS lesion (n = 218). There was a statistically significant difference in csPC detection rate of TB + SB between PI-RADS 3, 4 and 5 lesions (18.0% vs. 42.5% vs. 82.6%, p < 0.001) and TB + PB (19.7% vs. 29.1% vs. 78.3%). Comparing only maximum ISUP grade per lesion, even SB plus TB plus PB did not detect more csPCa compared to SB plus TB (41.3% vs. 39.9%, p > 0.05). CONCLUSION: We present prospective study data investigating the role of perilesional biopsy in detection of prostate cancer. We detected no statistically significant difference in the detection of csPCa by the addition of PB. Therefore, we recommend continuing 12-fold bilateral SB in addition to TB.

Membranous urethral length is the single independent predictor of urinary continence recovery at 12 months following Retzius-sparing robot-assisted radical prostatectomy.

The influence of anatomical parameters on urinary continence (UC) after Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) remains uncharted. Our objective was to evaluate their association with UC at 3, 6 and 12 months post-operatively. Data from patients who underwent RS-RARP were prospectively collected. Continence was defined as no pad use. Anatomic variables were measured on preoperative magnetic resonance imaging (MRI). Regression analyses were performed to identify predictors of UC at each time point. We included 158 patients with a median age of 60 years, most of whom had a localized tumor (≤ cT2). On multivariate analyses, at 3 months post-surgery, urinary incontinence (UI) rises with age, odds ratio (OR) 1.07 [95% confidence interval (CI) 1.004-1.142] and with prostate volume (PV), OR 1.029 (95% CI 1.006-1.052); it reduces with longer membranous urethral length (MUL), OR 0.875 (95% CI 0.780-0.983) and with higher membranous urethral volume (MUV), OR 0.299 (95% CI 0.121-0.737). At 6 months, UI rises with PV, OR 1.033 (95% CI 1.011-1.056) and decreases with MUV, OR 0.1504 (95% CI 0.050-0.444). Significantly, at 12 months post-surgery, the only predictor of UI is MUL, OR 0.830 (95% CI 0.706-0.975), establishing a threshold associated with a risk of UI of 5% (MUL > 15 mm) in opposition to a risk of 25% (MUL < 10 mm). This single institutional study requires external validation. To our knowledge, this is the first prospective cohort study supporting MUL as the single independent predictor of UC at 12 months post-surgery. By establishing MUL thresholds, we enable precise patient counseling.

Multiparametric MRI and 18F-PSMA-1007 PET/CT for the Detection of Clinically Significant Prostate Cancer.

Background Multiparametric MRI (mpMRI) is effective for detecting prostate cancer (PCa); however, there is a high rate of equivocal Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions and false-positive findings. Purpose To investigate whether fluorine 18 (18F) prostate-specific membrane antigen (PSMA) 1007 PET/CT after mpMRI can help detect localized clinically significant PCa (csPCa), particularly for equivocal PI-RADS 3 lesions. Materials and Methods This prospective study included participants with elevated prostate-specific antigen (PSA) levels referred for prostate mpMRI between September 2020 and February 2022. 18F-PSMA-1007 PET/CT was performed within 30 days of mpMRI and before biopsy. PI-RADS category and level of suspicion (LOS) were assessed. PI-RADS 3 or higher lesions at mpMRI and/or LOS 3 or higher lesions at 18F-PSMA-1007 PET/CT underwent targeted biopsies. PI-RADS 2 or lower and LOS 2 or lower lesions were considered nonsuspicious and were monitored during a 1-year follow-up by means of PSA testing. Diagnostic accuracy was assessed, with histologic examination serving as the reference standard. International Society of Urological Pathology (ISUP) grade 2 or higher was considered csPCa. Results Seventy-five participants (median age, 67 years [range, 52-77 years]) were assessed, with PI-RADS 1 or 2, PI-RADS 3, and PI-RADS 4 or 5 groups each including 25 participants. A total of 102 lesions were identified, of which 80 were PI-RADS 3 or higher and/or LOS 3 or higher and therefore underwent targeted biopsy. The per-participant sensitivity for the detection of csPCa was 95% and 91% for mpMRI and 18F-PSMA-1007 PET/CT, respectively, with respective specificities of 45% and 62%. 18F-PSMA-1007 PET/CT was used to correctly differentiate 17 of 26 PI-RADS 3 lesions (65%), with a negative and positive predictive value of 93% and 27%, respectively, for ruling out or detecting csPCa. One additional significant and one insignificant PCa lesion (PI-RADS 1 or 2) were found at 18F-PSMA-1007 PET/CT that otherwise would have remained undetected. Two participants had ISUP 2 tumors without PSMA uptake that were missed at PET/CT. Conclusion 18F-PSMA-1007 PET/CT showed good sensitivity and moderate specificity for the detection of csPCa and ruled this out in 93% of participants with PI-RADS 3 lesions. Clinical trial registration no. NCT04487847 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Turkbey in this issue.

The role of PSMA PET/CT in predicting downgrading in patients with Gleason score 4+4 prostate cancer in prostate biopsy.

BACKGROUND: To investigate the predictable parameters associated with downgrading in patients with a Gleason score (GS) 8 (4+4) in prostate biopsy after radical prostatectomy. METHODS: We retrospectively analyzed 62 patients with a GS of 4+4 on prostate biopsy who underwent robotic radical prostatectomy between 2017 and 2022. RESULTS: 38 of 62 (61.2%) were downgraded. In multivariable logistic regression model, Ga-68 prostate-specific membrane antigen (PSMA) positron-emission tomography (PET)/computed tomography (CT) SUV max was independent predictor of downgrading (OR 0.904; p = 0.011) and a Logistic Regression model was constructed using the following formula: Y = 1.465-0.95 (PSMA PET/CT SUV max). The model using this variable correctly predicted the downgrading in 72.6% of patients. The AUC for PSMA PET/CT SUV max was 0.709 the cut off being 8.8. A subgroup analysis was performed in 37 patients who had no other European Association of Urology (EAU) high risk features. 25 out of 37 (67.5%) were downgraded, and 21 of these 25 had organ confined disease. Low PSMA SUV max (<8.1) and percentage of GS 4+4 biopsy cores to cancer bearing cores (45.0%) were independently associated with downgrading to GS 7. CONCLUSION: PSMA PET/CT can be used to predict downgrading in patients with GS 4+4 PCa. Patients with GS 4+4 disease, but no other EAU high risk features, low percentage of GS 4+4 biopsy cores to cancer bearing cores, and a low PSMA PET/CT SUV max are associated with a high likelihood of the cancer reclassification to intermediate risk group.

A bi-directional segmentation method for prostate ultrasound images under semantic constraints.

Due to the lack of sufficient labeled data for the prostate and the extensive and complex semantic information in ultrasound images, accurately and quickly segmenting the prostate in transrectal ultrasound (TRUS) images remains a challenging task. In this context, this paper proposes a solution for TRUS image segmentation using an end-to-end bidirectional semantic constraint method, namely the BiSeC model. The experimental results show that compared with classic or popular deep learning methods, this method has better segmentation performance, with the Dice Similarity Coefficient (DSC) of 96.74% and the Intersection over Union (IoU) of 93.71%. Our model achieves a good balance between actual boundaries and noise areas, reducing costs while ensuring the accuracy and speed of segmentation.

Evaluation of a Cascaded Deep Learning-based Algorithm for Prostate Lesion Detection at Biparametric MRI.

Background Multiparametric MRI (mpMRI) improves prostate cancer (PCa) detection compared with systematic biopsy, but its interpretation is prone to interreader variation, which results in performance inconsistency. Artificial intelligence (AI) models can assist in mpMRI interpretation, but large training data sets and extensive model testing are required. Purpose To evaluate a biparametric MRI AI algorithm for intraprostatic lesion detection and segmentation and to compare its performance with radiologist readings and biopsy results. Materials and Methods This secondary analysis of a prospective registry included consecutive patients with suspected or known PCa who underwent mpMRI, US-guided systematic biopsy, or combined systematic and MRI/US fusion-guided biopsy between April 2019 and September 2022. All lesions were prospectively evaluated using Prostate Imaging Reporting and Data System version 2.1. The lesion- and participant-level performance of a previously developed cascaded deep learning algorithm was compared with histopathologic outcomes and radiologist readings using sensitivity, positive predictive value (PPV), and Dice similarity coefficient (DSC). Results A total of 658 male participants (median age, 67 years [IQR, 61-71 years]) with 1029 MRI-visible lesions were included. At histopathologic analysis, 45% (294 of 658) of participants had lesions of International Society of Urological Pathology (ISUP) grade group (GG) 2 or higher. The algorithm identified 96% (282 of 294; 95% CI: 94%, 98%) of all participants with clinically significant PCa, whereas the radiologist identified 98% (287 of 294; 95% CI: 96%, 99%; P = .23). The algorithm identified 84% (103 of 122), 96% (152 of 159), 96% (47 of 49), 95% (38 of 40), and 98% (45 of 46) of participants with ISUP GG 1, 2, 3, 4, and 5 lesions, respectively. In the lesion-level analysis using radiologist ground truth, the detection sensitivity was 55% (569 of 1029; 95% CI: 52%, 58%), and the PPV was 57% (535 of 934; 95% CI: 54%, 61%). The mean number of false-positive lesions per participant was 0.61 (range, 0-3). The lesion segmentation DSC was 0.29. Conclusion The AI algorithm detected cancer-suspicious lesions on biparametric MRI scans with a performance comparable to that of an experienced radiologist. Moreover, the algorithm reliably predicted clinically significant lesions at histopathologic examination. ClinicalTrials.gov Identifier: NCT03354416 © RSNA, 2024 Supplemental material is available for this article.

Prostate intra-fraction motion recorded by transperineal ultrasound.

Infra-fraction motion of the prostate was recorded during 3.423 fractions of image guided radiotherapy (IGRT) in 191 patients, 14 of which were treated by intensity modulated radiation therapy (IMRT), and 177 of which were treated by volumetric arc therapy (VMAT). The prostate was imaged by three-dimensional and time-resolved transperineal ultrasound (4D-US) of type Clarity by Elekta AB, Stockholm, Sweden. The prostate volume was registered and the prostate position (center of volume) was recorded at a frequency of 2.0 samples per second. This raw data set contains a total of 1.985.392 prostate and patient couch positions over a time span of 272 hours, 52 minutes and 34 seconds of life radiotherapy as exported by the instrument software. This data set has been used for the validation of models of prostate intra-fraction motion and for the estimation of the dosimetric impact of actual intra-fraction motion on treatment quality and side effects. We hope that this data set may be reused by other groups for similar purposes.

A PSMA PET/CT-based risk model for prediction of concordance between targeted biopsy and combined biopsy in detecting prostate cancer.

PURPOSE: This study is to investigate the diagnostic value of 68Ga-PSMA-11 in improving the concordance between mpMRI-TB and combined biopsy (CB) in detecting PCa. METHODS: 115 consecutive men with 68Ga-PSMA-11 PET/CT prior to prostate biopsy were included for analysis. PSMA intensity, quantified as maximum standard uptake value (SUVmax), minimum apparent diffusion coefficient (ADCmin) and other clinical characteristics were evaluated relative to biopsy concordance using univariate and multivariate logistic regression analyses. A prediction model was developed based on the identified parameters, and a dynamic online diagnostic nomogram was constructed, with its discrimination evaluated through the area under the ROC curve (AUC) and consistency assessed using calibration plots. To assess its clinical applicability, a decision curve analysis (DCA) was performed, while internal validation was conducted using bootstrapping methods. RESULTS: Concordance between mpMRI-TB and CB occurred in 76.5% (88/115) of the patients. Multivariate logistic regression analyses performed that SUVmax (OR= 0.952; 95% CI 0.917-0.988; P= 0.010) and ADCmin (OR= 1.006; 95% CI 1.003-1.010; P= 0.001) were independent risk factors for biopsy concordance. The developed model showed a sensitivity, specificity, accuracy and AUC of 0.67, 0.78, 0.81 and 0.78 in the full sample. The calibration curve demonstrated that the nomogram's predicted outcomes closely resembled the ideal curve, indicating consistency between predicted and actual outcomes. Furthermore, the decision curve analysis (DCA) highlighted the clinical net benefit achievable across various risk thresholds. These findings were reinforced by internal validation. CONCLUSIONS: The developed prediction model based on SUVmax and ADCmin showed practical value in guiding the optimization of prostate biopsy pattern. Lower SUVmax and Higher ADCmin values are associated with greater confidence in implementing mono-TB and safely avoiding SB, effectively balancing benefits and risks.

Inter-fractional error and intra-fractional motion of prostate and dosimetry comparisons of patient position registrations with versus without fiducial markers during treatment with carbon-ion radiotherapy.

A few reports have discussed the influence of inter-fractional position error and intra-fractional motion on dose distribution, particularly regarding a spread-out Bragg peak. We investigated inter-fractional and intra-fractional prostate position error by monitoring fiducial marker positions. In 2020, data from 15 patients with prostate cancer who received carbon-ion beam radiotherapy (CIRT) with gold markers were investigated. We checked marker positions before and during irradiation to calculate the inter-fractional positioning and intra-fractional movement and evaluated the CIRT dose distribution by adjusting the planning beam isocenter and clinical target volume (CTV) position. We compared the CTV dose coverages (CTV receiving 95% [V95%] or 98% [V98%] of the prescribed dose) between skeletal and fiducial matching irradiation on the treatment planning system. For inter-fractional error, the mean distance between the marker position in the planning images and that in a patient starting irradiation with skeletal matching was 1.49 ± 1.11 mm (95th percentile = 1.85 mm). The 95th percentile (maximum) values of the intra-fractional movement were 0.79 mm (2.31 mm), 1.17 mm (2.48 mm), 1.88 mm (4.01 mm), 1.23 mm (3.00 mm), and 2.09 mm (8.46 mm) along the lateral, inferior, superior, dorsal, and ventral axes, respectively. The mean V95% and V98% were 98.2% and 96.2% for the skeletal matching plan and 99.5% and 96.8% for the fiducial matching plan, respectively. Fiducial matching irradiation improved the CTV dose coverage compared with skeletal matching irradiation for CIRT for prostate cancer.

Prostatic stromal tumor of uncertain malignant potential: a case report and literature review.

Prostatic stromal tumors, encompassing prostatic sarcoma and stromal tumors of uncertain malignant potential (STUMP), represent an exceedingly rare category of prostatic diseases, with a prevalence of less than 1%. We present a rare case involving a man in his early 40s diagnosed with STUMP. Despite presenting with normal prostate-specific antigen (PSA) concentrations, the patient experienced persistent dysuria and gross hematuria for >7 months, leading to an initial misdiagnosis of benign prostatic hyperplasia. Persistent symptoms prompted further investigation, with magnetic resonance imaging (MRI) revealing a suspicious lesion on the left side of the prostate, initially thought to be malignant. Transrectal prostatic biopsy subsequently confirmed the presence of mucinous liposarcoma, with no medical history of diabetes, coronary heart disease, or hypertension. The treatment approach comprised robot-assisted laparoscopic radical prostatectomy, culminating in a postoperative pathological definitive diagnosis of STUMP. This case underscores the indispensable role of early MRI in the diagnostic process, highlighting the necessity of detailed pathological examination for a conclusive diagnosis. Our report aims to illuminate the diagnostic challenges and potential treatment pathways for STUMP, emphasizing its consideration in the differential diagnosis of prostatic tumors to advance clinical outcomes in this rare but important condition.

A novel model incorporating quantitative contrast-enhanced ultrasound into PI-RADSv2-based nomogram detecting clinically significant prostate cancer.

The diagnostic accuracy of clinically significant prostate cancer (csPCa) of Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) is limited by subjectivity in result interpretation and the false positive results from certain similar anatomic structures. We aimed to establish a new model combining quantitative contrast-enhanced ultrasound, PI-RADSv2, clinical parameters to optimize the PI-RADSv2-based model. The analysis was conducted based on a data set of 151 patients from 2019 to 2022, multiple regression analysis showed that prostate specific antigen density, age, PI-RADSv2, quantitative parameters (rush time, wash-out area under the curve) were independent predictors. Based on these predictors, we established a new predictive model, the AUCs of the model were 0.910 and 0.879 in training and validation cohort, which were higher than those of PI-RADSv2-based model (0.865 and 0.821 in training and validation cohort). Net Reclassification Index analysis indicated that the new predictive model improved the classification of patients. Decision curve analysis showed that in most risk probabilities, the new predictive model improved the clinical utility of PI-RADSv2-based model. Generally, this new predictive model showed that quantitative parameters from contrast enhanced ultrasound could help to improve the diagnostic performance of PI-RADSv2 based model in detecting csPCa.

The impact of prostate volume estimation on the risk-adapted biopsy decision based on prostate-specific antigen density and magnetic resonance imaging score.

PURPOSE: Utility of prostate-specific antigen density (PSAd) for risk-stratification to avoid unnecessary biopsy remains unclear due to the lack of standardization of prostate volume estimation. We evaluated the impact of ellipsoidal formula using multiparametric magnetic resonance (MRI) and semi-automated segmentation using tridimensional ultrasound (3D-US) on prostate volume and PSAd estimations as well as the distribution of patients in a risk-adapted table of clinically significant prostate cancer (csPCa). METHODS: In a prospectively maintained database of 4841 patients who underwent MRI-targeted and systematic biopsies, 971 met inclusions criteria. Correlation of volume estimation was assessed by Kendall's correlation coefficient and graphically represented by scatter and Bland-Altman plots. Distribution of csPCa was presented using the Schoots risk-adapted table based on PSAd and PI-RADS score. The model was evaluated using discrimination, calibration plots and decision curve analysis (DCA). RESULTS: Median prostate volume estimation using 3D-US was higher compared to MRI (49cc[IQR 37-68] vs 47cc[IQR 35-66], p < 0.001). Significant correlation between imaging modalities was observed (τ = 0.73[CI 0.7-0.75], p < 0.001). Bland-Altman plot emphasizes the differences in prostate volume estimation. Using the Schoots risk-adapted table, a high risk of csPCa was observed in PI-RADS 2 combined with high PSAd, and in all PI-RADS 4-5. The risk of csPCa was proportional to the PSAd for PI-RADS 3 patients. Good accuracy (AUC of 0.69 and 0.68 using 3D-US and MRI, respectively), adequate calibration and a higher net benefit when using 3D-US for probability thresholds above 25% on DCA. CONCLUSIONS: Prostate volume estimation with semi-automated segmentation using 3D-US should be preferred to the ellipsoidal formula (MRI) when evaluating PSAd and the risk of csPCa.

Prostate Cancer Screening With PSA, Kallikrein Panel, and MRI: The ProScreen Randomized Trial.

Importance: Prostate-specific antigen (PSA) screening has potential to reduce prostate cancer mortality but frequently detects prostate cancer that is not clinically important. Objective: To describe rates of low-grade (grade group 1) and high-grade (grade groups 2-5) prostate cancer identified among men invited to participate in a prostate cancer screening protocol consisting of a PSA test, a 4-kallikrein panel, and a magnetic resonance imaging (MRI) scan. Design, Setting, and Participants: The ProScreen trial is a clinical trial conducted in Helsinki and Tampere, Finland, that randomized 61 193 men aged 50 through 63 years who were free of prostate cancer in a 1:3 ratio to either be invited or not be invited to undergo screening for prostate cancer between February 2018 and July 2020. Interventions: Participating men randomized to the intervention underwent PSA testing. Those with a PSA level of 3.0 ng/mL or higher underwent additional testing for high-grade prostate cancer with a 4-kallikrein panel risk score. Those with a kallikrein panel score of 7.5% or higher underwent an MRI of the prostate gland, followed by targeted biopsies for those with abnormal prostate gland MRI findings. Final data collection occurred through June 31, 2023. Main Outcomes and Measures: In descriptive exploratory analyses, the cumulative incidence of low-grade and high-grade prostate cancer after the first screening round were compared between the group invited to undergo prostate cancer screening and the control group. Results: Of 60 745 eligible men (mean [SD] age, 57.2 [4.0] years), 15 201 were randomized to be invited and 45 544 were randomized not to be invited to undergo prostate cancer screening. Of 15 201 eligible males invited to undergo screening, 7744 (51%) participated. Among them, 32 low-grade prostate cancers (cumulative incidence, 0.41%) and 128 high-grade prostate cancers (cumulative incidence, 1.65%) were detected, with 1 cancer grade group result missing. Among the 7457 invited men (49%) who refused participation, 7 low-grade prostate cancers (cumulative incidence, 0.1%) and 44 high-grade prostate cancers (cumulative incidence, 0.6%) were detected, with 7 cancer grade groups missing. For the entire invited screening group, 39 low-grade prostate cancers (cumulative incidence, 0.26%) and 172 high-grade prostate cancers (cumulative incidence, 1.13%) were detected. During a median follow-up of 3.2 years, in the group not invited to undergo screening, 65 low-grade prostate cancers (cumulative incidence, 0.14%) and 282 high-grade prostate cancers (cumulative incidence, 0.62%) were detected. The risk difference for the entire group randomized to the screening invitation vs the control group was 0.11% (95% CI, 0.03%-0.20%) for low-grade and 0.51% (95% CI, 0.33%-0.70%) for high-grade cancer. Conclusions and Relevance: In this preliminary descriptive report from an ongoing randomized clinical trial, 1 additional high-grade cancer per 196 men and 1 low-grade cancer per 909 men were detected among those randomized to be invited to undergo a single prostate cancer screening intervention compared with those not invited to undergo screening. These preliminary findings from a single round of screening should be interpreted cautiously, pending results of the study's primary mortality outcome. Trial Registration: ClinicalTrials.gov Identifier: NCT03423303.

Head-to-head comparison of prostate-specific membrane antigen positron emission tomography/computed tomography and multiparametric magnetic resonance imaging in the detection of biochemical recurrence of prostate cancer: a systematic review and meta-analysis.

AIM: Our main goal of this meta-analytical analysis was to evaluate the diagnostic effectiveness of prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/computed tomography (CT) against multiparametric magnetic resonance imaging (mpMRI) in the context of identifying biochemical recurrence in patients with prostate cancer (PCa). MATERIALS AND METHODS: A thorough search covering articles published until March 2023 was carried out across major databases such as PubMed, Embase, and Web of Science. Studies examining the direct comparison of PSMA PET/CT and mpMRI in patients with PCa suffering biochemical recurrence were included in the inclusion criteria. Using the renowned Quality Assessment of Diagnostic Performance Studies-2 technique, each study's methodological rigor was assessed. RESULTS: We analyzed data from six eligible studies involving 290 patients in total. The combined data showed that for PSMA PET/CT and mpMRI, respectively, the pooled overall detection rates for recurrent PCa after definitive treatment were 0.69 (95% confidence interval [CI]: 0.45-0.89) and 0.70 (95% CI: 0.44-0.91). The detection rates for local recurrence were specifically 0.52 (95% CI: 0.39-0.65) and 0.62 (95% CI: 0.31-0.89), while they were 0.50 (95% CI: 0.26-0.74) and 0.32 (95% CI: 0.18-0.48) for lymph node metastasis. Notably, there was no discernible difference between the two imaging modalities in terms of the overall detection rate (P = 0.95). The detection rates for local recurrence and lymph node metastasis did not differ statistically significantly (P = 0.55, 0.23). CONCLUSION: The performance of PSMA PET/CT and mpMRI in identifying biochemical recurrence in PCa appears to be comparable. However, the meta-analysis' findings came from research with modest sample sizes. In this context, more extensive research should be conducted in the future.

Benign ectopic prostate-a rare differential for a presacral mass.

A man in his mid-40s presented to the colorectal surgery clinic with complaints of chronic perianal pain for over 20 years. He had episodes of urinary incontinence associated with pain. There were no other symptoms to suspect bowel pathology. On examination, he was found to have a tender mass in the retro-rectal plane without any evidence of rectal mucosal irregularity. He underwent an MRI of the pelvis, which showed a well-defined T2 hyperintense partly cystic lesion in the presacral region abutting the mesorectal fascia and a normal prostate gland. With a suspicion of a tailgut cyst or a duplication cyst, he underwent an excision of the presacral mass. Intraoperatively, there was a 2 × 2 cm well-defined firm, cystic lesion anterior to the fifth sacral vertebra and coccyx. The lesion was adherent to the mesorectum and was excised. On histopathology, there were features of muscular stroma and bilayered glandular epithelium with clear cytoplasm conclusive of a benign ectopic prostate.

FastMRI Prostate: A public, biparametric MRI dataset to advance machine learning for prostate cancer imaging.

Magnetic resonance imaging (MRI) has experienced remarkable advancements in the integration of artificial intelligence (AI) for image acquisition and reconstruction. The availability of raw k-space data is crucial for training AI models in such tasks, but public MRI datasets are mostly restricted to DICOM images only. To address this limitation, the fastMRI initiative released brain and knee k-space datasets, which have since seen vigorous use. In May 2023, fastMRI was expanded to include biparametric (T2- and diffusion-weighted) prostate MRI data from a clinical population. Biparametric MRI plays a vital role in the diagnosis and management of prostate cancer. Advances in imaging methods, such as reconstructing under-sampled data from accelerated acquisitions, can improve cost-effectiveness and accessibility of prostate MRI. Raw k-space data, reconstructed images and slice, volume and exam level annotations for likelihood of prostate cancer are provided in this dataset for 47468 slices corresponding to 1560 volumes from 312 patients. This dataset facilitates AI and algorithm development for prostate image reconstruction, with the ultimate goal of enhancing prostate cancer diagnosis.

Combination of prostate volume and apparent diffusion coefficient can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies.

BACKGROUND: Nowadays, there are many patients who undergo unnecessary prostate biopsies after receiving a prostate imaging reporting and data system (PI-RADS) score of 3. Our purpose is to identify cutoff values of the prostate volume (PV) and minimum apparent diffusion coefficient (ADCmin) to stratify those patients to reduce unnecessary prostate biopsies. METHODS: Data from 224 qualified patients who received prostate biopsies from January 2019 to June 2023 were collected. The Mann-Whitney U test was used to compare non-normal distributed continuous variables, which were recorded as median (interquartile ranges). The correlation coefficients were calculated using Spearman's rank correlation analysis. Categorical variables are recorded by numbers (percentages) and compared by χ2 test. Both univariate and multivariate logistic regression analysis were used to determine the independent predictors. The receiver-operating characteristic curve and the area under the curve (AUC) were used to evaluate the diagnostic performance of clinical variables. RESULTS: Out of a total of 224 patients, 36 patients (16.07%) were diagnosed with clinically significant prostate cancer (csPCa), whereas 72 patients (32.14%) were diagnosed with any grade prostate cancer. The result of multivariate analysis demonstrated that the PV (p < 0.001, odds ratio [OR]: 0.952, 95% confidence interval [95% CI]: 0.927-0.978) and ADCmin (p < 0.01, OR: 0.993, 95% CI: 0.989-0.998) were the independent factors for predicting csPCa. The AUC values of the PV and ADCmin were 0.779 (95% CI: 0.718-0.831) and 0.799 (95% CI: 0.740-0.849), respectively, for diagnosing csPCa. After stratifying patients by PV and ADCmin, 24 patients (47.06%) with "PV < 55 mL and ADCmin < 685 µm2/s" were diagnosed with csPCa. However, only one patient (1.25%) with PV ≥ 55 mL and ADCmin ≥ 685 µm2/s were diagnosed with csPCa. CONCLUSIONS: In this study, we found the combination of PV and ADCmin can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies. These patients with "PV ≥ 55 mL and ADCmin ≥ 685 µm2/s" may safely avoid prostate biopsies.

The role of urology and radiology in prostate biopsy: current trends and future perspectives.

PURPOSE: Prostate biopsy is central to the accurate histological diagnosis of prostate cancer. In current practice, the biopsy procedure can be performed using a transrectal or transperineal route with different technologies available for targeting of lesions within the prostate. Historically, the biopsy procedure was performed solely by urologists, but with the advent of image-guided techniques, the involvement of radiologists in prostate biopsy has become more common. Herein, we discuss the pros, cons and future considerations regarding their ongoing role. METHODS: A narrative review regarding the current evidence was completed. PubMed and Cochrane central register of controlled trials were search until January 2024. All study types were of consideration if published after 2000 and an English language translation was available. RESULTS: There are no published studies that directly compare outcomes of prostate biopsy when performed by a urologist or radiologist. In all published studies regarding the learning curve for prostate biopsy, the procedure was performed by urologists. These studies suggest that the learning curve for prostate biopsy is between 10 and 50 cases to reach proficiency in terms of prostate cancer detection and complications. It is recognised that many urologists are poorly able to accurately interpret multi parametric (mp)-MRI of the prostate. Collaboration between the specialities is of importance with urology offering the advantage of being involved in prior and future care of the patient while radiology has the advantage of being able to expertly interpret preprocedure MRI. CONCLUSION: There is no evidence to suggest that prostate biopsy should be solely performed by a specific specialty. The most important factor remains knowledge of the relevant anatomy and sufficient volume of cases to develop and maintain skills.