PI-RADS Score Research Articles

MP30-11 CLINICAL UTILITY OF EXOSOMEDX WHEN COMBINED WITH PSA, TRUS AND MPMRI FOR THE DETECTION OF HIGH-GRADE PROSTATE CANCER

You have accessJournal of UrologyProstate Cancer: Detection & Screening III (MP30)1 Sep 2021MP30-11 CLINICAL UTILITY OF EXOSOMEDX WHEN COMBINED WITH PSA, TRUS AND MPMRI FOR THE DETECTION OF HIGH-GRADE PROSTATE CANCER Claire de la Calle, Vittorio Fasulo, Martina Maggi, Nicolò Buffi, Matthew Cooperberg, Peter Carroll, Katsuto Shinohara, and Hao Nguyen Claire de la CalleClaire de la Calle More articles by this author , Vittorio FasuloVittorio Fasulo More articles by this author , Martina MaggiMartina Maggi More articles by this author , Nicolò BuffiNicolò Buffi More articles by this author , Matthew CooperbergMatthew Cooperberg More articles by this author , Peter CarrollPeter Carroll More articles by this author , Katsuto ShinoharaKatsuto Shinohara More articles by this author , and Hao NguyenHao Nguyen More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002027.11AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: How to integrate liquid biomarkers for prostate cancer (PCa) screening has not been clearly defined. We aimed to determine number of biopsies avoided and missed high-grade PCa using urine-based biomarker ExosomeDx when combined with prostate specific antigen density (PSAD), transrectal ultrasonography (TRUS) and multiparametric magnetic resonance imaging (mpMRI). METHODS: Patients referred to our institution between 2016 and 2019 with elevated PSA were retrospectively reviewed. High-grade PCa was defined as Gleason grade group (GG) ≥2. The frequency of potentially avoided biopsies was determined as the number of negative tests divided by the total cohort. The frequency of potentially missed GG≥2 PCa was determined as the number of false negative tests divided by all high-grade diagnoses in the cohort of biopsied patients. RESULTS: Of the 369-patient cohort, 334 (90.5%) had a TRUS and PSAD, 274 (74.3%) had a mpMRI, and 167 (45.3%) underwent prostate biopsy. Median age was 64.9 years (IQR 60.0–70.7), median PSA 7.01 ng/ml (IQR 5.00–9.90), and median ExosomeDx score 21.3 (IQR 12.3–37.0). ExosomeDx score higher than manufacturer cutoff (≥15.6) was associated with PI-RADS scores 3-5 (p<0.001), and GG≥2 PCa (p<0.001). Combining ExosomeDx with mpMRI would have resulted in avoiding 18.6–23.7% unnecessary biopsies overall, while missing only 3.23–4.84% GG≥2 PCa in those biopsied. Combining ExosomeDx with PSAD or TRUS clinical staging however would have also resulted in avoiding 22.2–22.5% unnecessary biopsies overall while only 1.47–1.54% GG≥2 PCa in the biopsy group would have been missed. Finally combining ExosomeDx with PSAD and mpMRI would have resulted in missing zero GG≥2 PCa in those biopsied but only 11.0–13.6% biopsies overall would have been avoided (Table 1). CONCLUSIONS: In our clinical practice combining ExosomeDx with PSAD, TRUS and/or mpMRI would have resulted in missing very few clinically significant PCas while still avoiding unnecessary biopsies. ExosomeDx combined with PSAD and/or TRUS would have missed very few clinically significant PCas without the need for mpMRI. Such screening algorithms are likely already widely used in clinical practice and should be validated with prospective trials. Source of Funding: UCSF Goldberg-Benioff Program in Cancer Translational Biology © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e503-e504 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Claire de la Calle More articles by this author Vittorio Fasulo More articles by this author Martina Maggi More articles by this author Nicolò Buffi More articles by this author Matthew Cooperberg More articles by this author Peter Carroll More articles by this author Katsuto Shinohara More articles by this author Hao Nguyen More articles by this author Expand All Advertisement Loading ...

MP30-03 POSITIVE PREDICTIVE VALUE OF MPMRI IN MEN UNDER ACTIVE SURVEILLANCE: CAN THE BIOPSY HISTORY INFLUENCE RADIOLOGICAL ASSESSMENT?

MP30-03 POSITIVE PREDICTIVE VALUE OF MPMRI IN MEN UNDER ACTIVE SURVEILLANCE: CAN THE BIOPSY HISTORY INFLUENCE RADIOLOGICAL ASSESSMENT?

MP22-08 NEGATIVE PREDICTIVE VALUE OF PROSTATE MRI IN REAL WORLD PRACTICE: RESULTS FROM A STATEWIDE SURGICAL COLLABORATIVE

You have accessJournal of UrologyImaging/Radiology: Uroradiology II (MP22)1 Sep 2021MP22-08 NEGATIVE PREDICTIVE VALUE OF PROSTATE MRI IN REAL WORLD PRACTICE: RESULTS FROM A STATEWIDE SURGICAL COLLABORATIVE John Michael DiBianco, Ji Qi, Anna Johnson, Stephanie Ferrante, Ali Dabaja, Karla Witzke, Alice Semerjian, Arvin K. George, and for the Michigan Urological Surgery Improvement Collaborative John Michael DiBiancoJohn Michael DiBianco More articles by this author , Ji QiJi Qi More articles by this author , Anna JohnsonAnna Johnson More articles by this author , Stephanie FerranteStephanie Ferrante More articles by this author , Ali DabajaAli Dabaja More articles by this author , Karla WitzkeKarla Witzke More articles by this author , Alice SemerjianAlice Semerjian More articles by this author , Arvin K. GeorgeArvin K. George More articles by this author , and for the Michigan Urological Surgery Improvement Collaborative More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002013.08AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Prostate MRI may help reduce unnecessary biopsies given the reported negative predictive value (NPV) for the presence of clinically significant prostate cancer (PCa). However, wide variation in the quality of MRI acquisition and interpretation exists. We aimed to determine the NPV of prostate MRI across diverse practices in the Michigan Urological Surgery Improvement Collaborative (MUSIC). METHODS: The MUSIC clinical registry was used to identify biopsy naïve patients who underwent biopsy with negative MRI between 4/2018-11/2020 and patients with a negative MRI in the setting of active surveillance (AS) between 7/2016-11/2020. Negative MRI was defined as absence of PI-RADS 3-5 lesions. Clinically significant PCa was defined as ≥Grade Group (GG) 2. Patients were stratified by prostate specific antigen (PSA), PSA density and digital rectal exam (DRE) findings. RESULTS: A total of 433 negative MRI and biopsies were identified across 21 practices. There were 169 (39%) performed in the biopsy naïve setting, and 264 (61%) performed during AS. Median age was 65 years (IQR 60–70), median PSA was 5.5 (IQR 4–8), 10.9% had positive DRE and 25.6% had a positive family history for PCa. The figure demonstrates the proportion of patients with negative prostate MRI by biopsy results. The NPV of prostate MRI for ≥GG2 PCa in biopsy-naïve patients was 81.7%. The NPV of prostate MRI for ≥GG2 PCa in men considering or enrolled on AS was 76.9%. The combined NPV for both cohorts was 78.6%. In biopsy naïve patients, PSA density was associated with ≥GG2 PCa (p<0.05). In AS patients, PSA and PSA density were significantly associated with biopsy resulting in ≥GG2 PCa (p<0.05 for each). CONCLUSIONS: Across diverse urologic practices in the community, the NPV of prostate MRI is consistent with published level 1 evidence at expert centers. The NPV for ≥GG2 PCa determined by PIRADS score performs similarly in different clinical settings. Source of Funding: Funding from Blue Cross Blue Shield of Michigan © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e393-e394 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information John Michael DiBianco More articles by this author Ji Qi More articles by this author Anna Johnson More articles by this author Stephanie Ferrante More articles by this author Ali Dabaja More articles by this author Karla Witzke More articles by this author Alice Semerjian More articles by this author Arvin K. George More articles by this author for the Michigan Urological Surgery Improvement Collaborative More articles by this author Expand All Advertisement Loading ...

MP11-06 PREDICTORS OF GLEASON GRADE UPGRADING ON WHOLEMOUNT PATHOLOGY AFTER MRI-TARGETED VERSUS SYSTEMATIC BIOPSY

You have accessJournal of UrologyProstate Cancer: Staging (MP11)1 Sep 2021MP11-06 PREDICTORS OF GLEASON GRADE UPGRADING ON WHOLEMOUNT PATHOLOGY AFTER MRI-TARGETED VERSUS SYSTEMATIC BIOPSY Nabila Khondakar, Michael Ahdoot, Luke O'Connor, Michael Daneshvar, Nitin Yerram, Cheyenne Williams, Jeunice Owens-Walton, Sandeep Gurram, Patrick Gomella, Jillian Egan, Sherif Mehralivand, Maria Merino, Bradford Wood, Baris Turkbey, and Peter Pinto Nabila KhondakarNabila Khondakar More articles by this author , Michael AhdootMichael Ahdoot More articles by this author , Luke O'ConnorLuke O'Connor More articles by this author , Michael DaneshvarMichael Daneshvar More articles by this author , Nitin YerramNitin Yerram More articles by this author , Cheyenne WilliamsCheyenne Williams More articles by this author , Jeunice Owens-WaltonJeunice Owens-Walton More articles by this author , Sandeep GurramSandeep Gurram More articles by this author , Patrick GomellaPatrick Gomella More articles by this author , Jillian EganJillian Egan More articles by this author , Sherif MehralivandSherif Mehralivand More articles by this author , Maria MerinoMaria Merino More articles by this author , Bradford WoodBradford Wood More articles by this author , Baris TurkbeyBaris Turkbey More articles by this author , and Peter PintoPeter Pinto More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000001984.06AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Despite limitations in diagnostic accuracy, transrectal ultrasound guided-systematic biopsy remains the most common method of prostate cancer (PCa) staging. Many low-risk PCa patients are deemed eligible for active surveillance based on systematic biopsy alone. The objective of this study was to analyze characteristics of patients eligible for AS based on systematic biopsy, who later underwent radical prostatectomy and were found to have Gleason Grade (GG) ≥3 disease. METHODS: Patients were enrolled in a nationally registered clinical trial to evaluate the use of MRI-targeted combined biopsy (NCT00102544). We queried our institutional database for patients who underwent radical prostatectomy between June 2007 and July 2020. Patients with GG1 or GG2 on systematic biopsy were included. Upgrading was determined by comparing GG on systematic and targeted biopsies, to GG on wholemount prostate specimen. Logistic regression models adjusted for age, BMI, and total prostate volume were used to identify predictors of upgrading to GG ≥3 disease. Chi-squared tests were used to compare categorical variables. RESULTS: A total of 773 patients who underwent radical prostatectomy between June 2007 and July 2020 were identified in our institutional database. Among patients who underwent combined biopsy (n = 495), 280 were diagnosed with GG1 (n=03) or GG2 (n=177) on systematic biopsy. The rate of upgrading to GG ≥ 3 was significantly higher for systematic than targeted biopsy (20.0% vs 5.0%, p<0.0001). Increased age at time of surgery was associated with increased odds of upgrading to GG≥ 3 (OR: 1.13, 95% CI: 1.03–1.25, p=.014). Targeted biopsy GG was associated with increased odds of upgrading to GG ≥3 on wholemount pathology (OR: 2.91, 95% CI: 1.74-5.38, p<0.001). Total number of lesions found on MRI was associated with lower odds of upgrading (OR: 0.41, 95% CI: 0.21-0.70, p=0.003). PSA at time of surgery, BMI, highest PIRADS score on MRI, and total prostate volume on MRI were not associated with upgrading to GG ≥ 3 on wholemount pathology (p>0.05). CONCLUSIONS: Approximately 1 in 5 patients eligible for AS based on 12-core TRUS-systematic biopsy portion of combined biopsy have GG ≥3 on wholemount histopathology after radical prostatectomy. Older age, GG on MRI-targeted biopsy, and fewer total lesions on pre-biopsy MRI are associated with upgrading to GG ≥3 on wholemount histopathology. Our findings support the use of MRI-targeted biopsy for risk-stratifying patients on AS. Source of Funding: NIH Intramural Funding, NIH Medical Research Scholars Program, Foundation for the NIH © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e179-e180 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Nabila Khondakar More articles by this author Michael Ahdoot More articles by this author Luke O'Connor More articles by this author Michael Daneshvar More articles by this author Nitin Yerram More articles by this author Cheyenne Williams More articles by this author Jeunice Owens-Walton More articles by this author Sandeep Gurram More articles by this author Patrick Gomella More articles by this author Jillian Egan More articles by this author Sherif Mehralivand More articles by this author Maria Merino More articles by this author Bradford Wood More articles by this author Baris Turkbey More articles by this author Peter Pinto More articles by this author Expand All Advertisement Loading ...

MP05-07 THE PROFILE STUDY—TARGETED SCREENING USING GERMLINE GENETICS IN MEN WITH A FAMILY HISTORY OF PROSTATE CANCER: THE ROLE OF MULTIPARAMETRIC MRI

MP05-07 THE PROFILE STUDY—TARGETED SCREENING USING GERMLINE GENETICS IN MEN WITH A FAMILY HISTORY OF PROSTATE CANCER: THE ROLE OF MULTIPARAMETRIC MRI

MP43-12 ASSESSING THE NEED FOR SYSTEMATIC BIOPSIES IN ADDITION TO TARGETED BIOPSIES ACCORDING TO THE VOLUME OF THE INDEX LESION DIAGNOSED AT MPMRI. RESULTS FROM A LARGE, MULTI-INSTITUTIONAL DATABASE

MP43-12 ASSESSING THE NEED FOR SYSTEMATIC BIOPSIES IN ADDITION TO TARGETED BIOPSIES ACCORDING TO THE VOLUME OF THE INDEX LESION DIAGNOSED AT MPMRI. RESULTS FROM A LARGE, MULTI-INSTITUTIONAL DATABASE

MP22-15 ARE UROLOGISTS READY FOR INTERPRETATION OF MULTIPARAMETRIC MRI FINDINGS? A PROSPECTIVE MULTICENTRIC EVALUATION

MP22-15 ARE UROLOGISTS READY FOR INTERPRETATION OF MULTIPARAMETRIC MRI FINDINGS? A PROSPECTIVE MULTICENTRIC EVALUATION

MP05-12 SHOULD WE ROUTINELY RECOMMEND A CENTRAL REVIEW OF MAGNETIC RESONANCE IMAGING OF THE PROSTATE IN MEN WITH POSITIVE MP-MRI? IMPLICATION FOR TARGETED BIOPSIES

MP05-12 SHOULD WE ROUTINELY RECOMMEND A CENTRAL REVIEW OF MAGNETIC RESONANCE IMAGING OF THE PROSTATE IN MEN WITH POSITIVE MP-MRI? IMPLICATION FOR TARGETED BIOPSIES

MP43-03 MACHINE LEARNING IMPROVES DETECTION OF CLINICALLY SIGNIFICANT PROSTATE CANCER IN EQUIVOCAL LESIONS ON MPMRI

You have accessJournal of UrologyProstate Cancer: Detection & Screening IV (MP43)1 Sep 2021MP43-03 MACHINE LEARNING IMPROVES DETECTION OF CLINICALLY SIGNIFICANT PROSTATE CANCER IN EQUIVOCAL LESIONS ON MPMRI Maxime D. Rappaport, Indrani Bhattacharya, Richard E. Fan, Mirabela Rusu, and Geoffrey A. Sonn Maxime D. RappaportMaxime D. Rappaport More articles by this author , Indrani BhattacharyaIndrani Bhattacharya More articles by this author , Richard E. FanRichard E. Fan More articles by this author , Mirabela RusuMirabela Rusu More articles by this author , and Geoffrey A. SonnGeoffrey A. Sonn More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002064.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: PIRADS version 2.1 is a standardized method for evaluating prostate multiparametric MRI (mpMRI). While a PIRADS score of 5 is highly specific for clinically significant prostate cancer (csPCa), false positives are very common in lesions scored PIRADS 3 or 4. These lesions present a dilemma to urologists seeking to maximize csPCa detection, while minimizing unnecessary biopsies. Radiomics, a method of extracting quantitative features from medical images, has the potential to differentiate equivocal lesions containing csPCa from those containing benign tissue. We aimed to develop a machine leaning (ML) algorithm that identifies csPCa within PIRADS 3 and 4 lesions to reduce unnecessary biopsies. METHODS: We identified 133 patients with PIRADS 3 or 4 lesions on mpMRI who underwent subsequent targeted prostate biopsy. Ground truth for presence of csPCa within a lesion was a targeted biopsy core with Gleason grade group ≥2. We created a data pipeline (Fig 1A) that involved processing mpMRI lesions, identifying relevant radiomic features, and training logistic regression models using 5-fold cross validation (CV). We selected ten radiomic features (Fig 1B) and two clinical values, age and PSA density, to train our models to detect csPCa. Each model was tested on an independent test set of 31 PIRADS 3 and 4 lesions and evaluated by the area under the curve (AUC) statistic (Fig 1C). Finally, the utility of using our classifier results to determine lesions requiring biopsy was evaluated by the proportion of false negative cases in our predictions. RESULTS: Our binary classifier models achieved a mean AUC of 0.86 ± 0.06 (mean ± standard deviation) and a csPCa detection accuracy of 75 ± 13%. The models had a sensitivity of 0.78 ± 0.11, specificity of 0.75 ± 0.15, positive predictive value of 0.58 ± 0.14, and negative predictive value of 0.89 ± 0.07. Using our classifiers to select lesions for targeted biopsy would have reduced the number of PIRADS 3 and 4 lesions requiring biopsy by 59 ± 9%, while missing csPCa in only 6.5 ± 3% of those lesions. CONCLUSIONS: We developed a binary classifier for csPCa detection in equivocal lesions (PIRADS 3 or 4) based on radiomic and clinical features. With further refinement and external validation, ML models have the potential to help urologists decide which lesions warrant targeted biopsy and which can be safely observed. Source of Funding: None © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e782-e782 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Maxime D. Rappaport More articles by this author Indrani Bhattacharya More articles by this author Richard E. Fan More articles by this author Mirabela Rusu More articles by this author Geoffrey A. Sonn More articles by this author Expand All Advertisement Loading ...

Results from a PI-RADS-based MRI-directed diagnostic pathway for biopsy-naive patients in a non-university hospital

PurposeTo assess the safety and performance of a MRI-directed diagnostic pathway for patients with first-time suspicion of prostate cancer in a non-university hospital.MethodsBetween May 2017 and December 2018 all biopsy-naive patients examined in our hospital followed a MRI-directed diagnostic work-up algorithm based on PI-RADS score. In short, PI-RADS 1–2 was generally not biopsied and PI-RADS 3–5 was reviewed by a multidisciplinary team. Patients with PI-RADS 4-5 were all referred to biopsy, either transrectal ultrasound-guided biopsy or MRI in-bore biopsy for small tumors and for sites difficult to access. PI-RADS scores were compared to the histopathology from biopsies and surgical specimens for patients who had prostatectomy. Non-biopsied patients were referred to a safety net monitoring regimen.ResultsTwo hundred and ninety-eight men were enrolled. 97 (33%) had PI-RADS 1–2, 44 (15%) had PI-RADS 3, and 157 (53%) had PI-RADS 4–5. 116 (39%) of the patients avoided biopsy. None of these were diagnosed with significant cancer within 2–3.5 years of safety net monitoring. Almost all high ISUP grade groups (≥ 3) were in the PI-RADS 4–5 category (98%). Prostatectomy specimens and systematic biopsies from MRI-negative areas indicated that very few clinically significant cancers were missed by the MRI-directed diagnostic pathway.ConclusionOur findings add to evidence that a MRI-directed diagnostic pathway can be safely established in a non-university hospital. The pathway reduced the number of biopsies and reliably detected the site of the most aggressive cancers.Graphic abstract

External validation of a prostate cancer nomogram on magnetic resonance/transrectal ultrasound fusion biopsy in men with prior negative systematic biopsy.

To observe how the nomogram, which was created by Truong et al, works in an independent patient group by performing external validation. One hundred and eighty-one patients who had at least one prior negative 12-core standard systematic biopsy and lesions with PI-RADS scores of 3 or higher that were detected as a result of mpMRI were included in the study. Targeted biopsy with 12-core standard systematic biopsy was performed on all patients. Clinical and pathological features of the patients were recorded. The discrimination, calibration and decision curve analysis were performed to externally validate the nomogram. A total of 181 patients with previous negative 12-core systematic biopsies were analysed. One hundred and thirty-four patients (74%) had benign pathology. Radiological volume and PI-RADS scores of 4 and 5 were found as independent predictors of benign pathology. The area under the curve (CI 95%) was found to be 0.80 (0.73-0.87), indicating good discrimination. The median residual was calculated as -0.0873, the intercept as -0.0690, the slope as 0.8927 and r2 as 0.2586, indicating good calibration. The standardised net benefit of follow-up decisions was found to be 0.54 and 0.36 at the probability threshold of 0.7 and 0.8, respectively. The original model showed good discrimination and calibration with our data. Defining a high probability threshold for clinical use would be appropriate for centres with high benign biopsy rates similar to our centre.

PO-1362 The prognostic value of PI-RADS score in ultra-hypofractionated radiotherapy for prostate cancer.

PO-1362 The prognostic value of PI-RADS score in ultra-hypofractionated radiotherapy for prostate cancer.

Does Adding Standard Systematic Biopsy to Targeted Prostate Biopsy in PI-RADS 3 to 5 Lesions Enhance the Detection of Clinically Significant Prostate Cancer? Should All Patients with PI-RADS 3 Undergo Targeted Biopsy?

Introduction. Our aim was to assess the value of adding standard biopsy to targeted biopsy in cases of suspicious multiparametric magnetic resonance imaging (mp-MRI) and also to evaluate when a biopsy of a PI-RADS 3 lesion could be avoided. Methods: A retrospective study of patients who underwent targeted biopsy plus standard systematic biopsy between 2016–2019 was performed. All the 1.5 T magnetic resonance images were evaluated according to PI-RADSv.2. An analysis focusing on the clinical scenario, lesion location, and PI-RADS score was performed. Results. A total of 483 biopsies were evaluated. The mean age was 65 years, with a PSA density of 0.12 ng/mL/cc. One-hundred and two mp-MRIs were categorized as PI-RADS-3. Standard biopsy was most helpful in detecting clinically significant prostate cancer (csPCa) in patients in the active surveillance (AS) cohort (increasing the detection rate 12.2%), and in peripheral lesions (6.5%). Adding standard biopsy showed no increase in the detection rate for csPCa in patients with PI-RADS-5 lesions. Considering targeted biopsy in patients with PI-RADS 3 lesions, a higher detection rate was shown in biopsy-naïve patients versus AS and in patients with a previous negative biopsy (p = 0.002). Furthermore, in these patients, the highest rate of csPCa detection was in anterior lesions [42.9% (p = 0.067)]. Conclusions. Our results suggest that standard biopsy could be safely omitted in patients with anterior lesions and in those with PI-RADS-5 lesions. Targeted biopsy for PI-RADS-3 lesions would be less effective in peripheral lesions with a previous negative biopsy.

Accelerated T2-Weighted TSE Imaging of the Prostate Using Deep Learning Image Reconstruction: A Prospective Comparison with Standard T2-Weighted TSE Imaging.

Simple SummaryMultiparametric magnetic resonance imaging (mpMRI) has become an important diagnostic tool in the assessment of clinically significant prostate cancer. The disadvantages of this technique are primarily related to its long examination time and limited availability. This prospective study presents a novel accelerated deep learning image reconstructed T2-weighted turbo spin echo (TSE) sequence providing an acquisition time reduction of more than 60%. The study results show that the acquisition of three imaging planes of the prostate is feasible within 3:50 min, using deep learning image reconstruction, compared to 10:21 min in standard imaging. Additionally, image quality parameters were evaluated to be superior in deep learning imaging.Multiparametric MRI (mpMRI) of the prostate has become the standard of care in prostate cancer evaluation. Recently, deep learning image reconstruction (DLR) methods have been introduced with promising results regarding scan acceleration. Therefore, the aim of this study was to investigate the impact of deep learning image reconstruction (DLR) in a shortened acquisition process of T2-weighted TSE imaging, regarding the image quality and diagnostic confidence, as well as PI-RADS and T2 scoring, as compared to standard T2 TSE imaging. Sixty patients undergoing 3T mpMRI for the evaluation of prostate cancer were prospectively enrolled in this institutional review board-approved study between October 2020 and March 2021. After the acquisition of standard T2 TSE imaging (T2S), the novel T2 TSE sequence with DLR (T2DLR) was applied in three planes. Overall, the acquisition time for T2S resulted in 10:21 min versus 3:50 min for T2DLR. The image evaluation was performed by two radiologists independently using a Likert scale ranging from 1–4 (4 best) applying the following criteria: noise levels, artifacts, overall image quality, diagnostic confidence, and lesion conspicuity. Additionally, T2 and PI-RADS scoring were performed. The mean patient age was 69 ± 9 years (range, 49–85 years). The noise levels and the extent of the artifacts were evaluated to be significantly improved in T2DLR versus T2S by both readers (p < 0.05). Overall image quality was also evaluated to be superior in T2DLR versus T2S in all three acquisition planes (p = 0.005–<0.001). Both readers evaluated the item lesion conspicuity to be superior in T2DLR with a median of 4 versus a median of 3 in T2S (p = 0.001 and <0.001, respectively). T2-weighted TSE imaging of the prostate in three planes with an acquisition time reduction of more than 60% including DLR is feasible with a significant improvement of image quality.

Development and validation of a predictive model for determining clinically significant prostate cancer in men with negative magnetic resonance imaging after transrectal ultrasound-guided prostate biopsy.

The interpretation of negative magnetic resonance imaging (MRI) screening results for clinically significant prostate cancer (csPCa) (International Society of Urological Pathology grade ≥group 2) is debatable and poses a clinical dilemma for urologists. No nomograms have been developed to predict csPCa in such populations. In this study, we aimed to develop and validate a model for predicting the probability of csPCa in men with negative MRI (PI-RADS score 1-2) results after transrectal ultrasound-guided systematic prostate biopsy. The development cohort consisted of 728 patients with negative MRI results who underwent subsequent prostate biopsy at our center between January 1, 2014 and December 31, 2017. The patients' clinicopathologic data were recorded. The Lasso regression was used for data dimension reduction and feature selection, then multivariable binary logistic regression was used to build a predictive model with regression coefficients. The model was validated in an independent cohort of 334 consecutive patients from January 1, 2018 and June 30, 2020. The performance of the predictive model was assessed with respect to discrimination, calibration, and decision curve analysis. The predictors incorporated in this model included age, history of previous negative prostate biopsy, prostate specific antigen density (PSAD), and lower urinary tract symptoms, with PSAD being the strongest predictor. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.875 (95% confidence interval, 0.816-0.933) and good calibration (unreliability test, p = .540). Decision curve analysis demonstrated that the model was clinically useful. This study presents a good nomogram that can aid pre-biopsy risk stratification for the detection of csPCa, and that may help inform biopsy decisions in patients with negative MRI results.

Assessing the accuracy of 68 Ga-PSMA PET/CT compared with MRI in the initial diagnosis of prostate malignancy: A cohort analysis of 114 consecutive patients.

Prostate cancer diagnosis is shifting towards a minimally invasive approach, maintaining accuracy and efficacy while reducing morbidity. We aimed to assess if PSMA-Ga68 PET/CT can accurately grade and localise prostatic malignancy using objective methods, compared with pathology and MRI. Retrospective analysis on 114 consecutive patients undergoing staging PSMA PET/CT scans over 12 months was carried out. The SUVmax and site of highest PSMA activity within the prostate gland were recorded. Pathology/biopsy review assessed maximum Gleason score (and location). MRI analysis assessed the highest PIRADS score and location. The grade, location and size of malignant tissue on biopsy, and PSA, were correlated with the SUVmax and the PIRADS score. SUVmax was significantly elevated in cases with PSA ≥10 (P = 0.003) and Gleason score ≥8 (P = 0.0002). SUVmax demonstrated equivalent sensitivity to MRI-PIRADS in predicting Gleason ≥8 disease, with higher specificity when tested under a high-specificity regime (SUVmax ≥10, PIRADS = 5, P = 0.002). Furthermore, the region of highest SUVmax was superior to MRI-PIRADS for localising the highest grade tumour region, correctly identifying 71% of highest grade regions compared to 54% with MRI (P = 0.015). PSMA PET/CT is as effective as MRI in identifying high-grade prostate malignancy. Our findings also support previous studies in showing a significant relationship between SUVmax and Gleason grade. These benefits, along with the known advantage in identifying distant metastases and the reduced cost, further support the argument that PSMA PET/CT should be offered as an initial investigation in the workup of prostate cancer.

Quantitative ultrasound shear wave elastography (USWE)-measured tissue stiffness correlates with PIRADS scoring of MRI and Gleason score on whole-mount histopathology of prostate cancer: implications for ultrasound image-guided targeting approach

ObjectiveTo correlate quantitative tissue stiffness measurements obtained by transrectal ultrasound shear wave elastography (USWE) with PI-RADS scoring of multiparametric magnetic imaging resonance (mpMRI) using Gleason scores of radical prostatectomy as a reference standard.Patients and methods196 men with localised prostate cancer were prospectively recruited into the study and had quantitative prostate tissue stiffness measurements in kilopascals (kPa) using transrectal USWE prior to radical prostatectomy. PI-RADS scores of mpMRI were also obtained in all the men. Imaging and histopathology of radical prostatectomy specimen were oriented to each other using patient specific customised 3D moulds to guide histopathology grossing of radical prostatectomy specimens. All included patients had confirmed PCa on TRUS-guided biopsies, had both USWE and mpMRI imaging data, and underwent radical prostatectomy. Chi-square test with 95% confidence interval was used to assess the difference between Gleason score (GS) of radical prostatectomy and PI-RADS classification, as well as GS of radical prostatectomy and stiffness (in Kpa) using USWE. The correlation coefficient (r) was calculated in order to investigate relation between PI-RADS classification and tissue stiffness in kPa.ResultsThere was a statistically significant correlation between USWE-measured tissue stiffness and GS (χ2 (2, N = 196) = 23.577, p < 0.001). Also, there was a statistically significant correlation between Gleason score and PI-RADS score (χ2 (2, N = 196) = 12.838, p = 0.002). High PIRADS on MRI and high stiffness on USWE (> 100 kPa) detected more than 80% and 90% high risk prostate cancer disease. However, a weak correlation coefficient of 0.231 was observed between PI-RADS score and level of tissue stiffness measured in kPa.ConclusionQuantitative USWE and mpMRI using PI-RADS classification provide a good degree of prediction for Gleason score of clinically significant prostate cancer (csPCa). Stiffer lesions on ultrasound showed a weak correlation with PI-RADS scoring system. USWE could be used to target suspected prostate cancer.

Utility of Quantitative T2-Mapping Compared to Conventional and Advanced Diffusion Weighted Imaging Techniques for Multiparametric Prostate MRI in Men with Hip Prosthesis.

Diffusion weighted imaging (DWI) is fundamental for prostate cancer (PCa) detection with MRI; however, limited by susceptibility artifact from hip prosthesis. To evaluate image quality and ability to detect PCa with quantitative T2-mapping and DWI in men with hip prosthesis undergoing prostate MRI. Prospective, cross-sectional study. Thirty consecutive men with hip replacement (18 unilateral, 12 bilateral) undergoing prostate MRI from 2019 to 2021. 3-T; multiparametric MRI (T2W, DCE-MRI, echo-planar [EPI]-DWI), T2-mapping (Carr-Purcell-Meiboom-Gill), FOCUS-EPI-DWI, PROPELLER-DWI. Five blinded radiologists independently evaluated MRI image quality using a 5-point Likert scale. PI-RADS v2.1 scores were applied in four interpretation strategies: 1) T2W-FSE+DCE-MRI+EPI-DWI, 2) T2W-FSE+DCE-MRI+EPI-DWI+FOCUS-EPI-DWI, 3) T2W-FSE+DCE-MRI+EPI-DWI+PROPELLER-DWI, 4) T2W-FSE+DCE-MRI+EPI-DWI+T2-maps. Five-point confidence scores were recorded. ANOVA, Kruskal-Wallis with pair-wise comparisons by Wilcoxon sign-rank, and paired t-tests, P < 0.05 was considered significant. Cohen's Kappa (k) for PI-RADSv2.1 scoring and proportion of correctly classified lesions tabulated for pathology-confirmed cases with 95% confidence intervals (CIs). For all radiologists, T2-map image quality was significantly higher than EPI-DWI, FOCUS-EPI-DWI, and PROPELLER-DWI and similar (P=0.146-0.706) or significantly better (for two readers) than T2W-FSE and DCE-MRI. PI-RADS v2.1 agreement improved comparing strategy A (k=0.46) to strategy B (k=0.58) to strategy C (k=0.58) and was highest with strategy D which included T2-maps (k=1.00). Radiologists' confidence was significantly highest with strategy D. Strategies B and C had similar confidence (P=0.051-0.063) both significantly outperforming strategy A. Twelve men with 17 lesions had pathology confirmed diagnoses (13 PCa, 4 benign). Strategy D had the highest proportion of correctly classified lesions (76.5-82.4%) with overlapping 95% confidence intervals. T2-mapping may be a valuable adjunct to prostate MRI in men with hip replacement resulting in improved image quality, higher reader confidence, interobserver agreement, and accuracy in PI-RADS scoring. 1 TECHNICAL EFFICACY STAGE: 2.

Machine learning algorithms can more efficiently predict biochemical recurrence after robot-assisted radical prostatectomy.

To develop a model for predicting biochemical recurrence (BCR) in patients with long follow-up periods using clinical parameters and the machine learning (ML) methods. Patients who underwent robot-assisted radical prostatectomy between January 2014 and December 2019 were retrospectively reviewed. Patients who did not have BCR were assigned to Group 1, while those diagnosed with BCR were assigned to Group 2. The patient's demographic data, preoperative and postoperative parameters were all recorded in the database. Three different ML algorithms were employed: random forest, K-nearest neighbour, and logistic regression. Three hundred and sixty-eight patients were included in this study. Among these patients, 295 (80.1%) did not have BCR (Group 1), while 73 (19.8%) had BCR (Group 2). The mean duration of follow-up and duration until the diagnosis of BCR was calculated as 35.2 ± 16.7 and 11.5 ± 11.3 months, respectively. The multivariate analysis revealed that NLR, PSAd, risk classification, PIRADS score, T stage, presence or absence of positive surgical margin, and seminal vesicle invasion were predictive for BCR. Classic Cox regression analysis had an area under the curve (AUC) of 0.915 with a sensitivity and specificity of 90.6% and 79.8%. The AUCs for receiver-operating characteristic curves for random forest, K nearest neighbour, and logistic regression were 0.95, 0.93, and 0.93, respectively. All ML models outperformed the conventional statistical regression model in the prediction of BCR after prostatectomy. The construction of more reliable and potent models will provide the clinicians and patients with advantages such as more accurate risk classification, prognosis estimation, early intervention, avoidance of unnecessary treatments, relatively lower morbidity and mortality. The ML methods are cheap, and their powers increase with increasing data input; we believe that their clinical use will increase over time.

Manyetik rezonans görüntüleme- ultrason füzyon prostat biyopsisi tek merkez sonuçları

Objective: We aimed to evaluate magnetic resonance imaging-ultrasound guided fusion prostate biopsy (MRI- US FPBx) results from a single center and to compare with current literature. Material and Methods: Between January 2016 and July 2019, MRI-US FPBx pathological and imaging results of 358 men were retrospectively analyzed. PI-RADS scores were determined as 3, 4 and 5 in 222 (62%), 107 (29.8%) and 29 (8.1%) patients, respectively. Totally 454 lesions were underwent MRI-US FPBx. 303 (66.7%) lesions were scored as PI-RADS 3, 120 (26.4%) lesions were scored as PI-RADS 4 and 31 (6.8%) lesions were scored as PI-RADS 5. 315 (69.3%) of lesions were in peripheral zone, 26 (5.7%) were in central zone, 111 (24.4%) were in transitional zone and 2 of them were in anterior fibromuscular stroma. Results: Overall prostate cancer detection rate was 36.3%. Concerning detection rates, MRI-US FPBx alone and transrectal ultrasonography guided prostate biopsy (TRUS-Bx) alone were 27.6% and 26.5%, respectively. Cancer detection rate only through MRI-US FPBx PIRADS-3 and PI-RADS 4&amp;5 were 6.9% and 20.6%, respectively. Clinically significant prostate cancer (csPCa) rates were evaluated and csPCa to overall prostate cancer (PCa) rates for TRUS-Bx, MRI-US FPBx and combined techniques were 16.8%, 35.4% and 39.2%, respectively. Results of 11 patients were evaluated as benign. Conclusion: MRI-US FPBx significantly increases success rate of prostate biopsy procedure. Regarding current MRI technology, it is not appropriate to consider MRI-US FPBx as a stand-alone biopsy option without concomitant with TRUS-Bx. Keywords: prostate cancer; biopsy; MRI; fusion