Prostate Imaging Reporting And Data System Score Research Articles

Diagnostic Value Analysis of PI-RADS v2.1 Combined with ADC Values in the Risk Stratification of Prostate Cancer Gleason Scores: A Retrospective Study.

Prostate cancer is a remarkable global health concern, necessitating accurate risk stratification for optimal treatment and outcome prediction. By highlighting the potential of imaging-based approaches to improve risk assessment in prostate cancer, this research aims to evaluate the diagnostic efficacy of the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 combined with apparent diffusion coefficient (ADC) values to gain increased context within the broad landscape of clinical needs and advancements in prostate cancer management. The clinical data of 145 patients diagnosed with prostate cancer were retrospectively analysed. The patients were divided into low-moderate- and high-risk groups on the basis of Gleason scores. PI-RADS v2.1 scores were assessed by senior radiologists and ADC values were calculated by using diffusion-weighted imaging. Statistical, univariate logistic regression, and receiver operating characteristic curve analyses were employed to evaluate the diagnostic efficacy of each index and combined PI-RADS v2.1 scores and ADC values. This study found significant differences in PI-RADS v2.1 scores and ADC values between the low-moderate- and high-risk groups (p < 0.001). Logistic regression analysis revealed associations of various clinical indicators, PI-RADS score and ADC values with Gleason risk classification. Amongst indices, mean ADC demonstrated the highest sensitivity (0.912) and area under curve (AUC) value (0.962) and the combination of PI-RADS v2.1 with mean ADC showed high predictive value for the Gleason risk grading of prostate cancer with a high AUC value (0.966). This study provides valuable evidence for the potential utility of imaging-based approaches, specifically PI-RADS v2.1 combined with ADC values, in enhancing the accuracy of risk stratification in prostate cancer.

Prognostic significance of the PI-RADS score in men with prostate cancer undergoing radical prostatectomy.

MRI-targeted biopsy (T-Bx) for which Prostate Imaging Reporting and Data System (PI-RADS) assessment categories are useful has been shown to more accurately detect clinically significant prostate cancer. However, the prognostic significance of the PI-RADS in prostate cancer patients needs further investigation. In the present study, we compared radical prostatectomy findings and postoperative oncologic outcomes in men with prostate cancer initially undergoing T-Bx for PI-RADS 3 vs. 4 vs. 5 lesions. We assessed consecutive patients undergoing T-Bx with concurrent systematic biopsy (S-Bx), followed by radical prostatectomy. Within our Surgical Pathology database, we identified a total of 207 men where prostatic adenocarcinoma was detected on either S-Bx or T-Bx, or both. Prostate cancer was detected on S-Bx only (n = 32; 15%), T-Bx only (n = 39; 19%), or both S-Bx and T-Bx (n = 136; 66%). These patients had PI-RADS 3 (n = 42; 20%), 4 (n = 86; 42%), or 5 (n = 79; 38%) lesions, while T-Bx detected cancer in 31 (74%) of PI-RADS 3 cases, 72 (84%) of PI-RADS 4 cases, and 72 (91%) of PI-RADS 5 cases. There were no significant differences in any of the clinicopathologic features examined, including tumor grade on biopsy or prostatectomy and pT or pN stage, among the PI-RADS 3 vs. 4 vs. 5 groups, except a significantly higher rate of positive margin and significantly larger tumor volume in PI-RADS 5 cases than in PI-RADS 3 cases. Univariate and multivariable analyses revealed significantly higher risks of biochemical recurrence after prostatectomy in patients with PI-RADS 5 lesion than in those with PI-RADS 3 or 4 lesion. Additionally, compared with respective controls, detection of any grade cancer (P = 0.046) or Grade Group 2 or higher cancer (P = 0.005) on T-Bx was associated with a significantly higher risk of recurrence in patients with PI-RADS 5 lesion, but not in those with PI-RADS 3 or 4 lesion. PI-RADS 5 lesions were thus found to independently predict a significantly poorer postoperative prognosis. Moreover, the failure of detection of any grade cancer or clinically significant cancer on T-Bx of PI-RADS 5 lesion may particularly indicate favorable outcomes in radical prostatectomy cases.

Prediction of T staging in PI-RADS 4–5 prostate cancer by combination of multiparametric MRI and 68Ga-PSMA-11 PET/CT

BackgroundIn this study, we explored the diagnostic performances of multiparametric magnetic resonance imaging (mpMRI), 68 Ga-PSMA-11 PET/CT and combination of 68 Ga-PSMA-11 PET/CT and mpMRI (mpMRI + PET/CT) for extracapsular extension (ECE). Based on the analyses above, we tested the feasibility of using mpMRI + PET/CT results to predict T staging in prostate cancer patients.MethodsBy enrolling 75 patients of prostate cancer with mpMRI and 68 Ga-PSMA-11 PET/CT before radical prostatectomy, we analyzed the detection performances of ECE in mpMRI, 68 Ga-PSMA-11 PET/CT and mpMRI + PET/CT on their lesion images matched with their pathological sample images layer by layer through receiver operating characteristics (ROC) analysis. By inputting the lesion data into Prostate Imaging Reporting and Data System (PI-RADS), we divided the lesions into different PI-RADS scores. The improvement of detecting ECE was analyzed by net reclassification improvement (NRI). The predictors for T staging were evaluated by using univariate and multivariable analysis. The Kappa test was used to evaluate the prediction ability.ResultsOne hundred three regions of lesion were identified from 75 patients. 50 of 103 regions were positive for ECE. The ECE diagnosis AUC of mpMRI + PET/CT is higher than that of mpMRI alone (ΔAUC = 0.101; 95% CI, 0.0148 to 0.1860; p < 0.05, respectively). Compared to mpMRI, mpMRI + PET/CT has a significant improvement in detecting ECE in PI-RADS 4–5 (NRI 36.1%, p < 0.01). The diagnosis power of mpMRI + PET/CT was an independent predictor for T staging (p < 0.001) in logistic regression analysis. In patients with PI-RADS 4–5 lesions, 40 of 46 (87.0%) patients have correct T staging prediction from mpMRI + PET/CT (κ 0.70, p < 0.01).ConclusionThe prediction of T staging in PI-RADS 4–5 prostate cancer patients by mpMRI + PET/CT had a quite good performance.

Clinical Trial Protocol for PRIMARY2: A Multicentre, Phase 3, Randomised Controlled Trial Investigating the Additive Diagnostic Value of [68Ga]Ga-PSMA-11 Positron Emission Tomography/Computed Tomography in Men with Negative or Equivocal Multiparametric Magnetic Resonance Imaging for the Diagnosis of Clinically Significant Prostate Cancer

BackgroundMultiparametric magnetic resonance imaging (mpMRI) has an established role for the diagnosis of clinically significant prostate cancer (sPCa). The PRIMARY trial demonstrated that [68Ga]Ga-PSMA-11 positron emission tomography/computed tomography (PET/CT) was associated with a significant improvement in sensitivity and negative predictive value for sPCa detection. ObjectiveTo demonstrate that addition of prostate-specific membrane antigen (PSMA) radioligand PET/CT will enable some men to avoid transperineal prostate biopsy without missing sPCa, and will facilitate biopsy targeting of PSMA-avid sites. Design, setting, and participantsThis multicentre, two-arm, phase 3, randomised controlled trial will recruit 660 participants scheduled to undergo biopsy. Eligible participants will have clinical suspicion of sPCa with a Prostate Imaging-Reporting and Data System (PI-RADS) score of 2 and red flags, or a PI-RADS score of 3 on mpMRI (PI-RADS v2). Participants will be randomised at a 1:1 ratio in permuted blocks stratified by centre. The trial is registered on ClinicalTrials.gov as NCT05154162. InterventionIn the experimental arm, participants will undergo pelvic PSMA PET/CT. Local and central reviewers will interpret scans independently using the PRIMARY score. Participants with a positive result will undergo targeted transperineal prostate biopsies, whereas those with a negative result will undergo prostate-specific antigen monitoring alone. In the control arm, all participants undergo template transperineal prostate biopsies. Participants will be followed for subsequent clinical care for up to 2 yr after randomisation. Outcome measurements and statistical analysissPCa is defined as Gleason score 3 + 4 (≥10%) = 7 disease (grade group 2) or higher on transperineal prostate biopsy. Avoidance of transperineal prostate biopsy will be measured at 6 mo from randomisation. The primary endpoints will be analysed on an intention-to-treat basis. ConclusionsPatient enrolment began in March 2022, with recruitment expected to take 36 mo. Patient summaryFor patients with suspected prostate cancer who have nonsuspicious or unclear MRI (magnetic resonance imaging) scan findings, a different type of scan (called PSMA PET/CT; prostate-specific membrane antigen positron emission tomography/computed tomography) may identify men who could avoid an invasive prostate biopsy. This type of scan could also help urologists in better targeting of samples from suspicious lesions during prostate biopsies.

Population-based Organised Prostate Cancer Testing: Results from the First Invitation of 50-year-old Men

BackgroundThe European Union recently recommended evaluation of the feasibility of organised prostate cancer screening. In Sweden, regional population-based organised prostate cancer testing (OPT) programmes were introduced in 2020. ObjectiveTo describe initial participation rates and diagnostic outcomes. Design, setting, and participantsThe three most populated Swedish regions invited all men aged 50 yr to OPT by a letter in 2020–2022. Men with prostate-specific antigen (PSA) ≥3 ng/ml were referred for prostate magnetic resonance imaging (MRI). PSA assays differed across regions. Men with Prostate Imaging Reporting and Data System (PI-RADS) 1–3 and PSA density ≥0.15 ng/ml/cm3 or PI-RADS 4–5 were referred for a biopsy. Data were obtained from the Swedish Register for Organised Prostate Cancer Testing. Outcome measurements and statistical analysisOverall and regional participation rates, PSA distributions, PI-RADS score distributions, cancer detection, and treatment were evaluated. Results and limitationsA total of 23 855 (35%) of 68 060 invited men participated; 696 (2.9%) had PSA ≥3 ng/ml, and of them, 306 (44%) had a biopsy indication and 221 (32%) had a biopsy. On biopsy, 93 (42%) had Gleason grade group ≥2 (0.39% of PSA-tested men) and 44 (20%) Gleason grade group 1 cancer. Most men with cancer had treatment with curative intent (70%) or were under active surveillance (28%). Across regions, proportions of men with PSA ≥3 ng/ml ranged from 2.3% to 4.0%, and those with PI-RADS score 4–5 ranged from 12% to 21%. A limitation is that results are applicable only to first testing of men in their early 50s. ConclusionsThe OPT programmes are feasible with good compliance to the diagnostic pathway. The use of MRI and PSA density avoided a biopsy for over half of the men with PSA ≥3 ng/ml. Inter-regional differences in diagnostic outcomes show a need for standardisation of the diagnostic pathway’s components. Patient summaryWe report the diagnostic outcomes of inviting 68 000 50-yr-old men to organised prostate cancer testing.

A transfer learning nomogram for predicting prostate cancer and benign conditions on MRI

BackgroundDeep learning has been used to detect or characterize prostate cancer (PCa) on medical images. The present study was designed to develop an integrated transfer learning nomogram (TLN) for the prediction of PCa and benign conditions (BCs) on magnetic resonance imaging (MRI).MethodsIn this retrospective study, a total of 709 patients with pathologically confirmed PCa and BCs from two institutions were included and divided into training (n = 309), internal validation (n = 200), and external validation (n = 200) cohorts. A transfer learning signature (TLS) that was pretrained with the whole slide images of PCa and fine-tuned on prebiopsy MRI images was constructed. A TLN that integrated the TLS, the Prostate Imaging–Reporting and Data System (PI-RADS) score, and the clinical factor was developed by multivariate logistic regression. The performance of the TLS, clinical model (CM), and TLN were evaluated in the validation cohorts using the receiver operating characteristic (ROC) curve, the Delong test, the integrated discrimination improvement (IDI), and decision curve analysis.ResultsTLS, PI-RADS score, and age were selected for TLN construction. The TLN yielded areas under the curve of 0.9757 (95% CI, 0.9613–0.9902), 0.9255 (95% CI, 0.8873–0.9638), and 0.8766 (95% CI, 0.8267–0.9264) in the training, internal validation, and external validation cohorts, respectively, for the discrimination of PCa and BCs. The TLN outperformed the TLS and the CM in both the internal and external validation cohorts. The decision curve showed that the TLN added more net benefit than the CM.ConclusionsThe proposed TLN has the potential to be used as a noninvasive tool for PCa and BCs differentiation.

Reproducibility and Accuracy of the PRIMARY Score on PSMA PET and of PI-RADS on Multiparametric MRI for Prostate Cancer Diagnosis Within a Real-World Database.

The PRIMARY score is a 5-category scale developed to identify clinically significant intraprostate malignancy (csPCa) on 68Ga-prostate-specific membrane antigen (PSMA)-11 PET/CT (68Ga-PSMA PET) using a combination of anatomic site, pattern, and intensity. Developed within the PRIMARY trial, the score requires evaluation in external datasets. This study aimed to assess the reproducibility and diagnostic accuracy of the PRIMARY score in a cohort of patients who underwent multiparametric MRI (mpMRI) and 68Ga-PSMA PET before prostate biopsy for the diagnosis of prostate cancer. Methods: In total, data from 242 men who had undergone 68Ga-PSMA PET and mpMRI before transperineal prostate biopsy were available for this ethics-approved retrospective study. 68Ga-PSMA PET and mpMRI data were centrally collated in a cloud-based deidentified image database. Six experienced prostate-focused nuclear medicine specialists were trained (1 h) in applying the PRIMARY score with 30 sample images. Six radiologists experienced in prostate mpMRI read images as per the Prostate Imaging-Reporting and Data System (PI-RADS), version 2.1. All images were read (with masking of clinical information) at least twice, with discordant findings sent to a masked third (or fourth) reader as necessary. Cohen κ was determined for both imaging scales as 5 categories and then collapsed to binary (negative and positive) categories (score 1 or 2 vs. 3, 4, or 5). Diagnostic performance parameters were calculated, with an International Society of Urological Pathology grade group of at least 2 (csPCa) on biopsy defined as the gold standard. Combined-imaging-positive results were defined as any PI-RADS score of 4 or 5 or as a PI-RADS score of 1-3 with a PRIMARY score of 3-5. Results: In total, 227 patients with histopathology, 68Ga-PSMA PET, and mpMRI imaging before prostate biopsy were included; 33% had no csPCa, and 67% had csPCa. Overall interrater reliability was higher for the PRIMARY scale (κ = 0.70) than for PI-RADS (κ = 0.58) when assessed as a binary category (benign vs. malignant). This was similar for all 5 categories (κ = 0.65 vs. 0.48). Diagnostic performance to detect csPCa was comparable between PSMA PET and mpMRI (sensitivity, 86% vs. 89%; specificity, 76% vs. 74%; positive predictive value, 88% vs. 88%; negative predictive value, 72% vs. 76%). Using combined imaging, sensitivity was 94%, specificity was 68%, positive predictive value was 86%, and negative predictive value was 85%. Conclusion: The PRIMARY score applied by first-user nuclear medicine specialists showed substantial interrater reproducibility, exceeding that of PI-RADS applied by mpMRI-experienced radiologists. Diagnostic performance was similar between the 2 modalities. The PRIMARY score should be considered when interpreting intraprostatic PSMA PET images.

Preoperative PI-RADS v2.1 Scoring System Improves Risk Classification in Patients Undergoing Radical Prostatectomy.

The purpose of this study was to examine the prognostic value of Prostate imaging-reporting and data system (PI-RADS) v2.1 scoring system in patients who underwent radical prostatectomy (RP). Clinical data of 294 patients who received RP between 2006 and 2018 were reviewed and multiple parameters including PI-RADS v2.1 score were employed to identify predictive factors for biochemical recurrence (BCR). Tumor volume was calculated from prostatectomy specimens. Median age at operation and initial PSA level were 67 years old and 7.68 ng/ml, respectively. 44.9 and 24.8% of patients were diagnosed with PI-RADS score 4 and 5 prior to biopsies, respectively. BCR was observed in 17% of patients and median observation period was 63.43 months. After multivariate analysis, PI-RADS v2.1 score 5 [hazard ratio (HR)=2.24, p=0.0124] was an independent predictive factor of BCR in addition to clinical T stage (≥2c) (HR=2.32, p=0.0093) and biopsy Gleason score (≥8) (HR=2.81, p=0.0007). Furthermore, PI-RADS score 5 significantly stratified the prognosis in D'Amico intermediate- and high-risk groups (p=0.0174 and p=0.0013, respectively). We established novel risk classifications including PI-RADS v2.1 score and found that prognostic capabilities were improved as compared to the D'Amico classification. The PI-RADS v2.1 score exhibited significant prognostic value in patients with localized prostate cancer following RP. Risk classifications based on PI-RADS v2.1 score might provide better ability for predicting oncological outcomes as compared to the D'Amico classification system.

Analysis of the relationship between PI-RADS scores and the pathological results of targeted biopsy based on MRI

Objective: To analyze the relationship between Prostate Imaging Reporting and Data System (PI-RADS) scores and the pathological results of transperineal magnetic resonance-ultrasound fusion guided biopsy. Methods: The clinical data, magnetic resonance imaging (MRI) results and prostate puncture biopsies of 517 patients who were assigned to PI-RADS score of 4 or 5 and underwent transperineal magnetic resonance-ultrasound fusion guided biopsy at The First Affiliated Hospital of Nanjing Medical University from June 2019 to March 2022 were retrospectively analyzed. Patients were divided into the PI-RADS 4 and PI-RADS 5 groups according to their PI-RADS scores and were stratified by their prostate specific antigen (PSA) values (PSA<10 ng/ml vs. PSA 10-20 ng/ml). The pathological negative rates from the biopsy, the distribution of the grade groups according to the grading system by World Health Organization/International Society of Urological Pathology (WHO/ISUP), the detection rates of prostate cancer (PCa) and clinically significant prostate cancer (CsPCa)between the groups were compared. Results: 369 patients with a PI-RADS score of 4 and 148 patients with a PI-RADS score of 5 were included in our research. The overall detection rates of PCa and CsPCa were 77.8% (402/517) and 66.7% (345/517), respectively. In the PI-RADS 4 group, patients with prostate negative biopsies or in WHO/ISUP 1, 2, 3, 4, or 5 grade groups accounted for 28.2%, 12.7%, 20.1%, 17.1%, 18.4% and 3.5%, respectively, whereas in the PI-RADS 5 group the rates were 7.4%, 6.8%, 22.3%, 22.3%, 26.4%, and 14.9%, respectively. The difference was statistically significant (P<0.001). The detection rates of PCa and CsPCa in the PI-RADS 4 group [71.8% (265/369) vs. 59.1% (218/369), P<0.001] were lower than those of the PI-RADS 5 group [92.6% (137/148) vs. 85.8% (127/148), P<0.001]. In the PI-RADS 4 group, the proportion of patients classified into WHO/ISUP 4-5 grade groups was lower than that of patients in the PI-RADS 5 group [22.0% (81/369) vs 41.2% (61/148) (P<0.001)]. The detection rates of PCa and CsPCa in the PSA<10 ng/ml stratification were less than that in the PSA 10-20 ng/ml stratification[74.1% (281/379) vs. 87.7% (121/138), P=0.001], and [60.9% (231/379) vs. 82.6% (114/138), P<0.001]. For patients with PSA<10 ng/ml, the detection rates of PCa and CsPCa in the PI-RADS 4 group were less than those in the PI-RADS5 group [70.9% (217/306) vs. 87.7% (64/73), P=0.003], and [56.2% (172/306) vs. 80.8% (59/73), P<0.001]. For those with a PSA value of 10-20 ng/ml, the detection rates of PCa and CsPCa in the PI-RADS 4 group were less than those in the PI-RADS 5 group [76.2% (48/63) vs. 97.3% (73/75), P<0.001], and [73.0% (46/63) vs. 90.7% (68/75), P=0.006]. There were statistically significant differences in the proportions of patients with prostate negative biopsy and those falling into WHO/ISUP grade groups 1, 2, 3, 4, or 5 (P<0.001) between the PI-RADS 4 group and the PI-RADS 5 group in both stratifications. Conclusions: In this study, the detection rates of CsPCa and PCa in the PI-RADS 4 group were less than those in the PI-RADS 5 group. With the increase of PI-RADS scores, the detection rate of high-grade PCa increased. The same results held for patients with PSA<10 ng/ml or with PSA 10-20 ng/ml.

Zone-specific computer-aided diagnosis system aimed at characterizing ISUP ≥ 2 prostate cancers on multiparametric magnetic resonance images: evaluation in a cohort of patients on active surveillance.

To assess a region-of-interest-based computer-assisted diagnosis system (CAD) in characterizing aggressive prostate cancer on magnetic resonance imaging (MRI) from patients under active surveillance (AS). A prospective biopsy database was retrospectively searched for patients under AS who underwent MRI and subsequent biopsy at our institution. MRI lesions targeted at baseline biopsy were retrospectively delineated to calculate the CAD score that was compared to the Prostate Imaging-Reporting and Data System (PI-RADS) version 2 score assigned at baseline biopsy. 186 patients were selected. At baseline biopsy, 51 and 15 patients had International Society of Urological Pathology (ISUP) grade ≥ 2 and ≥ 3 cancer respectively. The CAD score had significantly higher specificity for ISUP ≥ 2 cancers (60% [95% confidence interval (CI): 51-68]) than the PI-RADS score (≥ 3 dichotomization: 24% [CI: 17-33], p = 0.0003; ≥ 4 dichotomization: 32% [CI: 24-40], p = 0.0003). It had significantly lower sensitivity than the PI-RADS ≥ 3 dichotomization (85% [CI: 74-92] versus 98% [CI: 91-100], p = 0.015) but not than the PI-RADS ≥ 4 dichotomization (94% [CI:85-98], p = 0.104). Combining CAD findings and PSA density could have avoided 47/184 (26%) baseline biopsies, while missing 3/51 (6%) ISUP 2 and no ISUP ≥ 3 cancers. Patients with baseline negative CAD findings and PSAd < 0.15ng/mL2 who stayed on AS after baseline biopsy had a 9% (4/44) risk of being diagnosed with ISUP ≥ 2 cancer during a median follow-up of 41months, as opposed to 24% (18/74) for the others. The CAD could help define AS patients with low risk of aggressive cancer at baseline assessment and during subsequent follow-up.

Clinical value of prostate health index as an indicator for recommending magnetic resonance imaging in patients with gray-zone prostate-specific antigen level.

To evaluate the usefulness of prostate health index (PHI) as an indicator for recommending magnetic resonance imaging (MRI) in patients with prostate-specific antigen (PSA) gray zone level < 10ng/mL. 443 patients who underwent prostate biopsy (PB) after serum PHI test and MRI between April 2019 and December 2022 were enrolled. For patients with visible lesion on MRI with Prostate Imaging Reporting and Data System Score (PI-RADS) ≥ 3, MRI-targeted PB was performed in addition to systematic 12-core PB. The optimal cutoff value of PHI for predicting PI-RADS ≥ 3 lesions was 39.6, which was significantly associated with overall prostate cancer (OR 3.07, p = 0.018) and clinically significant prostate cancer (csPCa) (OR 4.15, p = 0.006) at MRI-targeted PB cores. When MRI was restricted to patients with PHI ≥ 39.6 alone, 28.7% of unnecessary MRI could be saved at the cost of missing 13.6% of csPCa. When omitting MRI for patients with PHI < 39.6 and PSAD < 0.12ng/mL2, unnecessary MRI could be reduced by 20.1% with the risk of missing 6.2% of csPCa. With addition of systematic PB, 21.0% of patients with negative MRI-targeted PB were diagnosed as csPCa. For patients in PSA gray zone, PHI of 39.6 might be an indicator for MRI and further MRI-targeted PB in additional to PSAD of 0.12ng/mL2, reducing 20.1% of unnecessary MRI with the minimal risk of missing 6.2% of csPCa. To maximize csPCa detection, combining both MRI-targeted and systematic PB should be also considered.

Prostate cancer detection using magnetic resonance imaging-transrectal ultrasound fusion biopsy: A retrospective cohort study

ABSTRACT Introduction: Transrectal ultrasound (TRUS) guided systematic prostate biopsy is conventionally used for the diagnosis of carcinoma prostate (CaP). However, magnetic resonance imaging (MRI) guided biopsies have been shown to have superior diagnostic performance. MRI-TRUS fusion biopsy improves the detection by combining the systematic and the targeted biopsies (TB). In this study, we evaluated the role of fusion biopsy in the detection of CaP as well as clinically significant carcinoma prostate (CsCaP). Methods: In this retrospective study, the patients who underwent fusion biopsy from January 2016 to July 2022 were evaluated. Patients underwent multiparametric MRI and the suspicious lesions were reported as per the Prostate Imaging Reporting and Data System (PIRADS) version 2. The clinical, imaging, and biopsy parameters were recorded and evaluated. Results: A total of 330 patients with PIRADS ≥3 underwent MRI-TRUS fusion biopsy and prostate cancer was detected in 187 patients (56.67%). With an increase in the PIRADS score, there was a significant rise in the detection of CaP (P &lt; 0.001) and CsCaP (P &lt; 0.0000001). Prostatitis was observed in 13%–18.1% of the patients with a lesion on MRI irrespective of the PIRADS score. The systematic and TB were comparable for the detection of CaP (P = 0.88) and CsCaP (P = 0.26). With a prostate-specific antigen density (PSAD) cutoff of 0.15 ng/mL/cc and 0.22 ng/mL/cc, biopsy could be safely avoided in 14.2% and 20.3% of the patients, missing only 0.3% of CaP and 0.9% of CsCaP, respectively. Different subgroups based on PSA levels, prostate volume, lesion dimension, and PIRADS score did not show a significant difference between the systematic and the targeted cores for the detection of CsCaP. Conclusion: This single center study of MRI-TRUS fusion prostate biopsy shows that in men with clinical suspicion of prostate cancer a pre-biopsy MRI and MRI-TRUS fusion combined systematic and targeted prostate biopsy improves the detection of prostate cancer and CsCaP. Patients with a PIRADS 3 lesion with a PSA density &lt;0.22 can safely avoid prostate biopsy, without a significant risk of missing clinically significant prostate cancer.

Deep Learning Super-Resolution Reconstruction for Fast and Motion-Robust T2-weighted Prostate MRI.

Background Deep learning (DL) reconstructions can enhance image quality while decreasing MRI acquisition time. However, DL reconstruction methods combined with compressed sensing for prostate MRI have not been well studied. Purpose To use an industry-developed DL algorithm to reconstruct low-resolution T2-weighted turbo spin-echo (TSE) prostate MRI scans and compare these with standard sequences. Materials and Methods In this prospective study, participants with suspected prostate cancer underwent prostate MRI with a Cartesian standard-resolution T2-weighted TSE sequence (T2C) and non-Cartesian standard-resolution T2-weighted TSE sequence (T2NC) between August and November 2022. Additionally, a low-resolution Cartesian DL-reconstructed T2-weighted TSE sequence (T2DL) with compressed sensing DL denoising and resolution upscaling reconstruction was acquired. Image sharpness was assessed qualitatively by two readers using a five-point Likert scale (from 1 = nondiagnostic to 5 = excellent) and quantitatively by calculating edge rise distance. The Friedman test and one-way analysis of variance with post hoc Bonferroni and Tukey tests, respectively, were used for group comparisons. Prostate Imaging Reporting and Data System (PI-RADS) score agreement between sequences was compared by using Cohen κ. Results This study included 109 male participants (mean age, 68 years ± 8 [SD]). Acquisition time of T2DL was 36% and 29% lower compared with that of T2C and T2NC (mean duration, 164 seconds ± 20 vs 257 seconds ± 32 and 230 seconds ± 28; P < .001 for both). T2DL showed improved image sharpness compared with standard sequences using both qualitative (median score, 5 [IQR, 4-5] vs 4 [IQR, 3-4] for T2C and 4 [IQR, 3-4] for T2NC; P < .001 for both) and quantitative (mean edge rise distance, 0.75 mm ± 0.39 vs 1.15 mm ± 0.68 for T2C and 0.98 mm ± 0.65 for T2NC; P < .001 and P = .01) methods. PI-RADS score agreement between T2NC and T2DL was excellent (κ range, 0.92-0.94 [95% CI: 0.87, 0.98]). Conclusion DL reconstruction of low-resolution T2-weighted TSE sequences enabled accelerated acquisition times and improved image quality compared with standard acquisitions while showing excellent agreement with conventional sequences for PI-RADS ratings. Clinical trial registration no. NCT05820113 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Turkbey in this issue.

Urine spermine and multiparametric magnetic resonance imaging for prediction of prostate cancer in Japanese men.

To investigate the role of urine spermine and spermine risk score in predicting prostate cancer (PCa) diagnoses in combination with multiparametric magnetic resonance imaging (mpMRI). Three hundred forty seven consecutive men with elevated prostate-specific antigen (PSA) with mpMRI examination were prospectively enrolled in this study. In 265 patients with PSA levels between 4 and20ng/ml, pre-biopsy urine samples were analyzed for spermine levels with ultra-high performance liquid chromatography (UPLC-MS/MS). Transperineal image-guided prostate biopsies with 16-18 cores were performed. Logistic regressions were used to form different models for the prediction of the PCa, and the performances were compared using the area under the curve (AUC). The median serum PSA level and prostate volume were 7.4ng/mL and 33.9mL, respectively. PCa and high-grade PCa (ISUP group ≥2, HGPCa) were diagnosed in 66.0% (175/265) and 132/265 (49.8%) cases, respectively. The urine spermine levels were significantly lower in men with PCa (0.87 vs. 2.20, P<0.001). Multivariate analyses showed that age, PSA, PV, urine spermine level, and Prostate Imaging Reporting and Data System (PI-RADS) findings were independent predictors for PCa. The Spermine Risk Score is a multivariable model including PSA, age, prostate volume, and urine spermine. Adding the Spermine Risk Score to PI-RADS improved the AUC from 0.73 to 0.86 in PCaand from 0.72 to 0.83 in high grade PCa (HGPCa) prediction (both P<0.001). At 90% sensitivity for HGPCa prediction using Spermine Risk Score, 31.1% of unnecessary biopsies could be avoided. In men with equivocal MRI PI-RADS score 3, the AUC for HGPCa prediction was 0.58, 0.79, and 0.87 for PSA, PSA density, and Spermine Risk Score, respectively. Urine Spermine Risk Score, including mpMRI could accurately identify men at high risk of HGPCa and reduce unnecessary prostate biopsies. Spermine Risk Score could more accurately predict HGPCa than PSA density in men with MRI showing equivocal PI-RADS 3 lesions.

A Prostate-Specific Membrane Antigen PET-Based Approach for Improved Diagnosis of Prostate Cancer in Gleason Grade Group 1: A Multicenter Retrospective Study.

The preoperative Gleason grade group (GG) from transrectal ultrasound-guided prostate biopsy is crucial for treatment decisions but may underestimate the postoperative GG and miss clinically significant prostate cancer (csPCa), particularly in patients with biopsy GG1. In such patients, an SUVmax of at least 12 has 100% specificity for detecting csPCa. In patients with an SUVmax of less than 12, we aimed to develop a model to improve the diagnostic accuracy of csPCa. Methods: The study retrospectively included 56 prostate cancer patients with transrectal ultrasound-guided biopsy GG1 and an SUVmax of less than 12 from 2 tertiary hospitals. All [68Ga]Ga-PSMA-HBED-CC PET scans were centrally reviewed in Xijing Hospital. A deep learning model was used to evaluate the overlap of SUVmax (size scale, 3 cm) and the level of Gleason pattern (size scale, 500 μm). A diagnostic model was developed using the PRIMARY score and SUVmax, and its discriminative performance and clinical utility were compared with other methods. The 5-fold cross-validation (repeated 1,000 times) was used for internal validation. Results: In patients with GG1 and an SUVmax of less than 12, significant prostate-specific membrane antigen (PSMA) histochemical score (H-score) H-score overlap occurred among benign gland, Gleason pattern 3, and Gleason pattern 4 lesions, causing SUVmax overlap between csPCa and non-csPCa. The model of 10 × PRIMARY score + 2 × SUVmax exhibited a higher area under the curve (AUC, 0.8359; 95% CI, 0.7233-0.9484) than that found using only the SUVmax (AUC, 0.7353; P = 0.048) or PRIMARY score (AUC, 0.7257; P = 0.009) for the cohort and a higher AUC (0.8364; 95% CI, 0.7114-0.9614) than that found using only the Prostate Imaging Reporting and Data System (PI-RADS) score of 5-4 versus 3-1 (AUC, 0.7036; P = 0.149) and the PI-RADS score of 5-3 versus 2-1 (AUC, 0.6373; P = 0.014) for a subgroup. The model reduced the misdiagnosis of the PI-RADS score of 5-4 versus 3-1 by 78.57% (11/14) and the PI-RADS score of 5-3 versus 2-1 by 77.78% (14/18). The internal validation showed that the mean 5-fold cross-validated AUC was 0.8357 (95% CI, 0.8357-0.8358). Conclusion: We preliminarily suggest that the model of 10 × PRIMARY score + 2 × SUVmax may enhance the diagnostic accuracy of csPCa in patients with biopsy GG1 and an SUVmax of less than 12 by maximizing PSMA information use, reducing the misdiagnosis of the PI-RADS score, and thereby aiding in making appropriate treatment decisions.

Yield of second-round MRI targeted ultrasound-guided fusion prostate biopsy after initial first-round targeted biopsy.

We aimed to determine the yield of second-round magnetic resonance imaging-ultrasound (MRI-US) fusion biopsy and factors that may predict eventual clinically significant (CS) prostate cancer (PCa) diagnosis. From 2013 to 2021, 85 men underwent second-round MRI-US fusion biopsy of 92 lesions (47.8% [44/92] peripheral zone and 52.2% [48/92] transition zone). Patient age, prostate-specific antigen (PSA), PSA density (PSAD), size/location of lesions, ADC value, Prostate Imaging-Reporting and Data System (PI-RADS), and PRECISE scores were recorded and compared to histopathological diagnosis (International Society of Urological Pathology [ISUP] grade-group 1 PCa, CS PCa=ISUP grade group ≥2 PCa) using logistic regression. Mean patient age, PSA, and PSAD were 64±7 years, 8.5±7.0 ng/ml, and 0.17±0.11, respectively. Results from first-round targeted biopsy were 63% (58/92) negative and 37% (34/92) clinically insignificant (grade group 1) PCa. Overall, second-round targeted biopsy identified 25% (23/92) CS PCa (grade group 2, n=19; grade group 3, n=4). Considering only lesions with initial negative targeted-biopsy results (n=58), 21% (12/58; grade group 2, n=8; grade group 3, n=4) CS PCa and 13 grade group 1 PCa were diagnosed at second-round biopsy. There was no difference in PSA (p=0.564), size (p=0.595), location (p=0.293), or PI-RADS score (p=0.342) of lesions by eventual CS PCa diagnosis. PSAD (0.2±1.4 vs. 0.16±0.10, p=0.167), ADC (0.748±0.199 vs. 0.833±0.257, p=0.151), and PRECISE score (p<0.01) showed a trend towards association or association with eventual CS PCa diagnosis. Repeat second-round targeted MRI-US fusion biopsy yielded CS PCa diagnosis in the targeted biopsy specimen in approximately 20% of patients in our study. PRECISE score may be a useful marker to help predict which patients require second-round biopsy.

PIRADS Score 3 of Multi-Parametric Magnetic Resonance Imaging in Patients with Suspicious Prostate Cancer, Is It Conclusive?

Background Prostate cancer (Pca) is the second most common type of cancer in men worldwide. One of the new modalities for diagnosis is multiparametric magnetic resonance imaging (mp-MRI). To improve the interpretation of mp-MRI, Prostate Imaging Reporting and Data System (PI-RADS) scoring system was suggested by the European Society of Urogenital Radiology (ESUR). PI-RADS score 3 was found to be equivocal by many studies. Aim of our study is analysis of demographic, clinical, and histological data of patients with PI-RADS score 3 by mp-MRI. Methods Fifty patients were enrolled. Full history taking, digital rectal examination (DRE), PSA, mp-MRI followed by trans-rectal ultrasound (TRUS) guided prostate biopsy were performed for all patients. We analyzed data of the 34 patients who were proved to have prostate lesions with PI-RADS 3 score by mp-MRI. Results 62.5% of the PI-RADS 3 lesions proved to be benign by TRUS guided biopsy, and the rest (37.5%) was detected as prostate cancer in biopsy. No statistically significant correlations were found between age, total PSA and density, prostate volume, or DRE and detection of Pca in patients with PI-RADS 3 score. Conclusion Lesions with score of PI-RADS 3 by mp-MRI cannot prove or exclude Pca and needs further evaluation by prostate biopsy.

Perilesional Targeted Biopsy Combined with MRI-TRUS Image Fusion-Guided Targeted Prostate Biopsy: An Analysis According to PI-RADS Scores.

A prostate-targeted biopsy (TB) core is usually collected from a site where magnetic resonance imaging (MRI) indicates possible cancer. However, the extent of the lesion is difficult to accurately predict using MRI or TB alone. Therefore, we performed several biopsies around the TB site (perilesional [p] TB) and analyzed the association between the positive cores obtained using TB and pTB and the Prostate Imaging Reporting and Data System (PI-RADS) scores. This retrospective study included patients who underwent prostate biopsies. The extent of pTB was defined as the area within 10 mm of a TB site. A total of 162 eligible patients were enrolled. Prostate cancer (PCa) was diagnosed in 75.2% of patients undergoing TB, with a positivity rate of 50.7% for a PI-RADS score of 3, 95.8% for a PI-RADS score of 4, and 100% for a PI-RADS score of 5. Patients diagnosed with PCa according to both TB and pTB had significantly higher positivity rates for PI-RADS scores of 4 and 5 than for a PI-RADS score of 3 (p < 0.0001 and p = 0.0009, respectively). Additional pTB may be performed in patients with PI-RADS ≥ 4 regions of interest for assessing PCa malignancy.

PI-RADS-Based Segmented Threshold of PSMA-PET SUVmax Is Better than Traditional Fixed Threshold for Diagnosing Clinically Significant Prostate Cancer Especially for PI-RADS 3 Lesions.

Our purpose was to compare the performance of prostate-specific membrane antigen (PSMA)-positron emission tomography (PET) traditional fixed threshold (FT) and newly established Prostate Imaging Reporting and Data System (PI-RADS)-based segmented threshold (ST) for diagnosing clinically significant prostate cancer (csPCa). The study retrospectively included 218 patients who underwent multiparametric magnetic resonance imaging (mpMRI) and PSMA-PET examination for suspected prostate cancer (PCa) from January 2018 to November 2021. Lesions with Gleason score ≥ 3 + 4 were diagnosed as csPCa. In PSMA-PET maximum standardized uptake value (SUVmax), the FT for all the lesions and STs for lesions with different PI-RADS score for diagnosing csPCa were determined by receiver operating characteristic (ROC) curves analysis and compared with Z test. The McNemar test was used to compare sensitivity and specificity. Among the 218 patients, there were 113 csPCa and 105 non-csPCa. The PSMA-PET FT was SUVmax > 5.3 (area under the curve, AUC = 0.842) and STs for PI-RADS 3/4/5 were SUVmax > 4.2/5.7/6.0 (AUCs = 0.870/0.867/0.882), respectively. The AUC of PSMA-PET ST was higher than that of PSMA-PET FT (0.872 vs. 0.842), especially for PI-RADS 3 (0.870 vs. 0.653). Multimodality diagnostic criteria combining PSMA-PET ST and PI-RADS scores of mpMRI was established and its AUC was higher than that of PSMA-PET ST (0.893 vs. 0.872) and significantly higher than that of PSMA-PET FT (0.893 vs. 0.842) with an improvement in sensitivity (93% vs. 78%, p < 0.05) without significantly sacrificing specificity (86% vs. 91%, p > 0.05). For diagnosing csPCa, PI-RADS-based PSMA-PET segmented threshold achieved better performance than traditional fixed threshold, especially for PI-RADS 3 lesions. Multimodality diagnostic criteria demonstrated higher diagnostic performance than segmented threshold and significantly better than PSMA-PET fixed threshold for detecting csPCa.

Exploration of the diagnostic capacity of PSAMR combined with PI-RADS scoring for clinically significant prostate cancer and establishment and validation of the Nomogram prediction model.

The objective of this investigation was to explore the diagnostic capability of Prostate Specific Antigen Mass Ratio (PSAMR) combined with Prostate Imaging Reporting and Data System (PI-RADS) scoring for clinically significant prostate cancer (CSPC), develop and validate a Nomogram prediction model for the probability of prostate cancer occurrence in patients who have not undergone prostate biopsy. Initially, we retrospectively collected clinical and pathological data of patients who underwent trans-perineal prostate puncture at Yijishan Hospital of Wanan Medical College from July 2021 to January 2023. Through logistic univariate and multivariate regression analysis, independent risk factors for CSPC were determined. Receiver Operating Characteristic (ROC) curves were generated to compare the ability of different factors for diagnosis of CSPC. Then, we split the dataset into a training set and validation set, compared their heterogeneity, and developed a Nomogram prediction model based on the training set. Finally, we validated the Nomogram prediction model in terms of discrimination, calibration, and clinical usefulness. Logistic multivariate regression analysis illustrated that age [64-69 (OR = 2.736, P = 0.029); 69-75 (OR = 4.728, P = 0.001); > 75 (OR = 11.344, P < 0.001)], PSAMR [0.44-0.73 (OR = 4.144, P = 0.028); 0.73-1.64(OR = 13.022, P < 0.001); > 1.64(OR = 50.541, P < 0.001)], and PI-RADS score [4 points (OR = 7.780, P < 0.001); 5 points (OR = 24.533, P < 0.001)] were independent risk factors for CSPC. The Area Under the Curve (AUC) of the ROC curves of PSA, PSAMR, PI-RADS score, and PSAMR combined with PI-RADS score were respectively 0.797, 0.874, 0.889, and 0.928. The performance of PSAMR and PI-RADS score for diagnosis of CSPC was superior to PSA, but inferior to PSAMR combined with PI-RADS. Age, PSAMR, and PI-RADS were included in the Nomogram prediction model. The AUCs of the training set ROC curve and the validation set ROC curve were 0.943 (95% CI 0.917-0.970) and 0.878 (95% CI 0.816-0.940), respectively, in the discrimination validation. The calibration curve showed good consistency, and the decision analysis curve suggested the model had good clinical efficacy. We found that PSAMR combined with PI-RADS scoring had a strong diagnostic capability for CSPC, and provided a Nomogram prediction model to predict the probability of prostate cancer occurrence combined with clinical data.