Clinically Significant Prostate Cancer Detection Research Articles

Predictors of prostate cancer detection in MRI PI-RADS 3 lesions - Reality of a tertiary center.

The Prostate Imaging Reporting and Data System (PI-RADS) score reports the likelihood of a clinically significant prostate cancer (CsPCa) based on various multiparametric prostate magnetic resonance imaging (mpMRI) characteristics. The PI-RADS category 3 is an intermediate status, with an equivocal risk of malignancy. The PSA density (PSAD) has been proposed as a tool to facilitate biopsy decisions on PI-RADS category 3 lesions. The objective of this study is to determine the frequency of CsPCa, assess the diagnostic value of targeted biopsy and identify clinical predictors to improve the CsPCa detection rate in PI-RADS category 3 lesions. Between 1st January 2017 and 31st December 2022, a total of 1661 men underwent a prostate biopsy at our institution. Clinical and mpMRI data of men with PI-RADS 3 lesions was reviewed. The study population was divided into two groups: target group, including those submitted to systematic plus targeted biopsy versus non-target group when only systematic or saturation biopsy were performed. Patients with PI-RADS 3 lesions were divided into three categories based on pathological biopsy results: benign, clinically insignificant disease (score Gleason = 6 or International Society of Urologic Pathologic (ISUP) 1) and clinically significant cancer (score Gleason ≥ 7 (3+4) or ISUP ≥ 2) according to target and non-target group. Univariate and multivariate analyses were performed to identify clinical predictors to improve the CsPCa detection rate in PI-RADS category 3 lesions. A total of 130 men with PIRADS 3 index lesions were identified. Pathologic results were benign in 77 lesions (59.2%), 19 (14.6%) were clinically insignificant (Gleason score 6) and 34 (26.2%) were clinically significant (Gleason score 7 or higher). Eighty-seven of the patients were included in the target group (66.9%) and 43 in the non-target group (33.1%). The CsPCa detection was higher in the non-target group (32.6%, n = 14 vs 23.0%, n = 20 respectively). When systematic and target biopsies were jointly performed, if the results of systematic biopsies are not considered and only the results of target biopsies are taken into account, a CsPCa diagnosis would be missed on 9 patients. The differences of insignificant cancer and CsPCa rates among the target or non-target group were not statistically significant (p = 0.50 and p = 0.24, respectively). on multivariate analysis, the abnormal DRE and lesions localized in Peripheral zone (PZ) were significantly associated with a presence of CsPCa in PI-RADS 3 lesions (oR = 3.61, 95% CI [1.22,10.72], p = 0.02 and oR = 3.31, 95% CI [1.35, 8.11], p = 0.01, respectively). A higher median PSAD significantly predisposed for CsPCa on univariate analyses (p = 0.05), however, was not significant in the multivariate analysis (p = 0.76). In our population, using 0.10 ng/ml/ml as a cut-off to perform biopsy, 41 patients would have avoided biopsy (31.5%), but 5 cases of CsPCa would not have been detected (3.4%). We could not identify any statistical significance between other clinical and imagiological variables and CsPCa detection. PI-RADS 3 lesions were associated with a low likelihood of CsPCa detection. A systematic biopsy associated or not with target biopsy is essential in PI-RADS 3 lesions, and targeted biopsy did not demonstrate to be superior in the detection of CsPCa. The presence of abnormal DRE and lesions localized in PZ potentially predict the presence of CsPCa in biopsied PI-RADS 3 lesions.

Comparison of Targeted Biopsy and Combined Biopsy to Avoid Unnecessary Systematic Biopsy in Patients with PI-RADS 5 Lesions.

To evaluate the detection rates of prostate cancer (PCa) and clinically significant prostate cancer (CSPCa) detection via target biopsy (TB), systematic biopsy (SB), and combined biopsy (CB) in patients with PI-RADS 5 lesions. Patients with at least one PI-RADS 5 lesion were retrospectively enrolled in a prospectively collected database. The patients underwent multiparametric magnetic resonance imaging (mpMRI) followed by transrectal TB of PI-RADS 5 lesions and SB. The PCa and CSPCa detection rates and cores of TB and SB were compared with those of CB. In 585 patients, prostate biopsy revealed PCa in 560 cases (95.73%) and CSPCa in 549 cases (93.85%). PCa was detected in T2 patients (93.13%, 217/233) and in T3/4 patients (97.44%, 343/352). CSPCa was detected in T2 patients (89.27%, 208/233) and in T3/4 patients (96.87%, 341/352). The positive rates of TB for T2/3/4, T3/4, and T2 were 94.02%, 96.21%, and 90.56%, respectively. SB added 1.71% (10/585) PCa and 1.37% (8/585) CSPCa detection to TB. There was no difference between TB and SB in detecting different stages of cancer (p > 0.05). In the biopsy core analysis, TB had fewer biopsy cores and a higher detection rate than SB (all p < 0.05). In patients with PI-RADS score 5 lesions, TB can achieve the same detection rate as, with fewer biopsy cores than, CB. SB adds minimal clinical value and can be omitted for these patients.

Significant Prostate Cancer in Patients with PI-RADS Category 3 Lesions: A Single-Center, Retrospective Cohort Study.

The Prostate Imaging-Reporting and Data System (PI-RADS) category 3 is the most ambiguous lesion with a variable clinically significant prostate cancer (CsPCa) detection rate. Prostate-specific antigen density (PSAD) has been investigated as an adjunctive factor to improve the diagnostic efficiency of PI-RADS categories. This study aimed to investigate the utility of PSAD as an adjunctive factor in predicting CsPCA risk in patients with PI-RADS 3 lesions. The patients with an initial PI-RADS 3 category lesion (n=142) scheduled for systematic and magnetic resonance imaging-guided prostate biopsy between 2018 and 2022 were retrospectively evaluated. Demographic and clinical variables, including PSAD, were collected. The rate of CsPCa was the primary outcome. The impact of PSAD on the CsPCa detection rate was the secondary outcome. The median age was 62 years. The rate of CsPCa was 8.5% (n=12). The patients with CsPCa have significantly lower prostate volüme and higher PSAD levels than those without CsPCa (p=0.016 and p=0.012). The cut-off values of PSAD in predicting CsPCa in all PI-RADS 3 patients and patients with CsPCa and clinically insignificant prostate cancer (n=26) were ≥0.181 ng/ml2. The sensitivity and specificity values for PSAD ≥0.181 ng/ml2 were of 75% (95% CI: 42.8%-94.5%) and 81.5% (95% CI: 73.4%-88.0%) in predicting CsPCa among PI-RADS 3 category. Conclusion: PSAD values higher than 0.181 ng/ml2 can be used as an adjunctive clinical parameter in predicting CsPCa in patients with PI-RADS 3 lesions and differentiating CsPCa from clinically insignificant prostate cancer cases.

MP55-20 A NOVEL MACHINE LEARNING FRAMEWORK FOR AUTOMATED DETECTION OF PROSTATE CANCER LESIONS CONFIRMED ON MRI-INFORMED TARGET BIOPSY

MP55-20 A NOVEL MACHINE LEARNING FRAMEWORK FOR AUTOMATED DETECTION OF PROSTATE CANCER LESIONS CONFIRMED ON MRI-INFORMED TARGET BIOPSY

Nomograms Combining PHI and PI-RADS in Detecting Prostate Cancer: A Multicenter Prospective Study

(1) Background: The study aimed to construct nomograms to improve the detection rates of prostate cancer (PCa) and clinically significant prostate cancer (CSPCa) in the Asian population. (2) Methods: This multicenter prospective study included a group of 293 patients from three hospitals. Univariable and multivariable logistic regression analysis was performed to identify potential risk factors and construct nomograms. Discrimination, calibration, and clinical utility were used to assess the performance of the nomogram. The web-based dynamic nomograms were subsequently built based on multivariable logistic analysis. (3) Results: A total of 293 patients were included in our study with 201 negative and 92 positive results in PCa. Four independent predictive factors (age, prostate health index (PHI), prostate volume, and prostate imaging reporting and data system score (PI-RADS)) for PCa were included, and four factors (age, PHI, PI-RADS, and Log PSA Density) for CSPCa were included. The area under the ROC curve (AUC) for PCa was 0.902 in the training cohort and 0.869 in the validation cohort. The AUC for CSPCa was 0.896 in the training cohort and 0.890 in the validation cohort. (4) Conclusions: The combined diagnosis of PHI and PI-RADS can avoid more unnecessary biopsies and improve the detection rate of PCa and CSPCa. The nomogram with the combination of age, PHI, PV, and PI-RADS could improve the detection of PCa, and the nomogram with the combination of age, PHI, PI-RADS, and Log PSAD could improve the detection of CSPCa.

Pulse Sequence Dependence of a Simple and Interpretable Deep Learning Method for Detection of Clinically Significant Prostate Cancer Using Multiparametric MRI

Multiparametric magnetic resonance imaging (mpMRI) is increasingly used for risk stratification and localization of prostate cancer (PCa). Thanks to the great success of deep learning models in computer vision, the potential application for early detection of PCa using mpMRI is imminent. Deep learning analysis of the PROSTATEx dataset. In this study, we show a simple convolutional neural network (CNN) with mpMRI can achieve high performance for detection of clinically significant PCa (csPCa), depending on the pulse sequences used. The mpMRI model with T2-ADC-DWI achieved 0.90 AUC score in the held-out test set, not significantly better than the model using Ktrans instead of DWI (AUC 0.89). Interestingly, the model incorporating T2-ADC- Ktrans better estimates grade. We also describe a saliency "heat" map. Our results show that csPCa detection models with mpMRI may be leveraged to guide clinical management strategies. Convolutional neural networks incorporating multiple pulse sequences show high performance for detection of clinically-significant prostate cancer, and the model including dynamic contrast-enhanced information correlates best with grade.

Combining prostate-specific antigen density with prostate imaging reporting and data system score version 2.1 to improve detection of clinically significant prostate cancer: A retrospective study.

Globally, Prostate cancer (PCa) is the second most common cancer in the male population worldwide, but clinically significant prostate cancer (CSPCa) is more aggressive and causes to more deaths. The authors aimed to construct the risk category based on Prostate Imaging Reporting and Data System score version 2.1 (PI-RADS v2.1) in combination with Prostate-Specific Antigen Density (PSAD) to improve CSPCa detection and avoid unnecessary biopsy. Univariate and multivariate logistic regression and receiver-operating characteristic (ROC) curves were performed to compare the efficacy of the different predictors. The results revealed that PI-RADS v2.1 score and PSAD were independent predictors for CSPCa. Moreover, the combined factor shows a significantly higher predictive value than each single variable for the diagnosis of CSPCa. According to the risk stratification model constructed based on PI-RADS v2.1 score and PSAD, patients with PI-RADS v2.1 score of ≤2, or PI-RADS V2.1 score of 3 and PSA density of <0.15 ng/mL2, can avoid unnecessary of prostate biopsy and does not miss clinically significant prostate cancer.

Does Experience Affect the Cancer Detection Rate in Cognitive Fusion Prostate Biopsy? A Comparison of the First and Last 60 Cases

Objective: We aimed to determine the contribution of the clinical experience gained in cognitive fusion prostate biopsy with the increase in the number of cases to the cancer detection rate. Materials and Methods: The records of 120 patients who underwent cognitive fusion biopsy were retrospectively analyzed. All patients underwent 3-T multiparametric magnetic resonance imaging (Mp-MRI) and they were evaluated with Prostate Imaging Reporting and Data System (PIRADS). The initial 60 cases were included in group 1, and the later subsequent 60 cases performed by the same surgeon were included in group 2. Any cancer and clinically significant prostate cancer (CSPrCa) detection rates in groups 1 and 2 were compared. Results: The mean ages of the patients for group 1 and group 2 were determined as 64.08 ± 8.15 and 65.15 ± 6.93 years, respectively. Age, prostate specific antigen (PSA), prostate volumes and the number of suspicious lesions of the groups were similar. Any cancer positivity rate was 33.3% for group 1, and 40% for group 2, without any significant intergroup difference (p=0.494). CSPrCa positivity was 40% and 70.83% for groups 1 and 2, respectively, and there was a significant improvement in CSPrCa detection in favor of group 2 (p=0.027). Conclusion: Regarding the cognitive fusion biopsies, a learning curve is required. It was concluded that the rate of detecting clinically significant prostate cancer was almost doubled with the increased experience in fusion biopsy. Keywords: Biopsy, Cognitive Fusion, Learning Curve, Magnetic Resonance Imaging, Prostate Cancer

Multi-institutional analysis of clinical and imaging risk factors for detecting clinically significant prostate cancer in men with PI-RADS 3 lesions.

Most Prostate Imaging-Reporting and Data System (PI-RADS) 3 lesions do not contain clinically significant prostate cancer (CSPCa; grade group ≥2). This study was aimed at identifying clinical and magnetic resonance imaging (MRI)-derived risk fac- tors that predict CSPCa in men with PI-RADS 3 lesions. This study analyzed the detection of CSPCa in men who underwent MRI-targeted biopsy for PI-RADS 3 lesions. Multivariable logistic regression models with goodness-of-fit testing were used to identify variables associated with CSPCa. Receiver operating curves and decision curve analyses were used to estimate the clinical utility of a predictive model. Of the 1784 men reviewed, 1537 were included in the training cohort, and 247 were included in the validation cohort. The 309 men with CSPCa (17.3%) were older, had a higher prostate-specific antigen (PSA) density, and had a greater likelihood of an anteriorly located lesion than men without CSPCa (p < .01). Multivariable analysis revealed that PSA density (odds ratio [OR], 1.36; 95% confidence interval [CI], 1.05-1.85; p < .01), age (OR, 1.05; 95% CI, 1.02-1.07; p < .01), and a biopsy-naive status (OR, 1.83; 95% CI, 1.38-2.44) were independently associated with CSPCa. A prior negative biopsy was negatively associated (OR, 0.35; 95% CI, 0.24-0.50; p < .01). The application of the model to the validation cohort resulted in an area under the curve of 0.78. A predicted risk threshold of 12% could have prevented 25% of biopsies while detecting almost 95% of CSPCas with a sensitivity of 94% and a specificity of 34%. For PI-RADS 3 lesions, an elevated PSA density, older age, and a biopsy-naive status were associated with CSPCa, whereas a prior negative biopsy was negatively associated. A predictive model could prevent PI-RADS 3 biopsies while missing few CSPCas. Among men with an equivocal lesion (Prostate Imaging-Reporting and Data System 3) on multiparametric magnetic resonance imaging (mpMRI), those who are older, those who have a higher prostate-specific antigen density, and those who have never had a biopsy before are at higher risk for having clinically significant prostate cancer (CSPCa) on subsequent biopsy. However, men with at least one negative biopsy have a lower risk of CSPCa. A new predictive model can greatly reduce the need to biopsy equivocal lesions noted on mpMRI while missing only a few cases of CSPCa.

Diagnostic value of combining PI-RADS v2.1 with PSAD in clinically significant prostate cancer.

To investigate the diagnostic value of the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) for clinically significant prostate cancer (CsPCa). We also aimed to combine PI-RADS v2.1 with prostate-specific antigen (PSA) derivatives to improve the predictive value of CsPCa. We retrospectively collected relevant data who underwent standard MRI examinations of the prostate and subjected to a prostate biopsy at Shenzhen People's hospital from November 2014 to November 2019. Included 125 cases of CsPCa and 383 cases of non-CsPCa. All cases were scored using the PI-RADS v2.1. The clinical data collected included age, PSA, free PSA/total PSA, prostate volume and PSA density (PSAD). A univariate analysis was performed to identify statistically significant indicators. Logistic regression was used to analyze the predictive value of the multi-parameter combination on CsPCa. Except age, the difference in all of indicators between the CsPCa group and non-CsPCa group was statistically significant. The PI-RADS score and PSAD value had the highest diagnostic value. Logistic regression analysis revealed that the PI-RADS score and PSAD value were independent predictors of CsPCa, with a regression model AUC of 0.935. CsPCa detection rates were low when the PI-RADS score ≤ 2 or the PI-RADS score = 3 and the PSAD value ≤ 0.33ng/ml/ml. Combining the PI-RADS score and PSAD value improved the predictive performance of CsPCa. Patients with a PI-RADS score ≤ 2 or a PI-RADS score = 3 and a PSAD value ≤ 0.33ng/ml/ml can avoid an unnecessary biopsy.

MP53-05 CLINICALLY SIGNIFICANT PROSTATE CANCER DETECTION RATE OF PROSTATE IMAGING REPORTING AND DATA SYSTEM SCORE 4 IN THE PERIPHERAL ZONE

You have accessJournal of UrologyCME1 May 2022MP53-05 CLINICALLY SIGNIFICANT PROSTATE CANCER DETECTION RATE OF PROSTATE IMAGING REPORTING AND DATA SYSTEM SCORE 4 IN THE PERIPHERAL ZONE Gang Song, and Zhoujie Sun Gang SongGang Song More articles by this author , and Zhoujie SunZhoujie Sun More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002628.05AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 recommends that lesions in the peripheral zone (PZ) are mainly assessed by diffusion-weighted imaging (DWI) and adjusted by dynamic contrast-enhanced (DCE). There are two possible images for PI-RADS 4 lesions in PZ. One is DWI 4, the other is DWI 3 with positive DCE (hereinafter called ‘DWI 3/DCE+’). Our objectives are to compare the clinically significant prostate cancer (csPCa) detection rate between DWI 4 and DWI 3/DCE+ in PZ and to explore the diagnostic performances of targeted biopsy (TB) alone or systematic biopsy (SB) alone for patients with DWI 3/DCE+. METHODS: We retrospectively enrolled 206 patients who underwent multiparametric magnetic resonance imaging and had at least one PI-RADS 4 lesion in the PZ. All patients subsequently underwent combined magnetic resonance imaging/ultrasound fusion-guided TB and ultrasound-guided SB. The chi-square test was used to compare the csPCa detection rates between DWI 4 and DWI 3/DCE+ lesions. Based on the TB+SB results as a standard reference, we analyzed the sensitivity, negative predictive values, and diagnostic accuracies of TB alone or SB alone. RESULTS: Patients with DWI 4 lesions had higher csPCa detection rates than those with DWI 3/DCE+ lesions when using TB+SB, TB, and SB, and the differences were significant for TB+SB or SB alone. For DWI 3/DCE+ patients whose prostate-specific antigen levels ranged from 4 to 10 ng/mL, TB alone showed the highest negative predictive value. CONCLUSIONS: Our finding suggested that DWI 4 tends to have worse results than DWI 3/DCE+. TB has an excellent ability to exclude negative csPCa in patients with DWI 3/DCE+ lesions and prostate-specific antigen levels from 4 to 10 ng/mL. Source of Funding: The Ministry of Science and Technology of China © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e897 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Gang Song More articles by this author Zhoujie Sun More articles by this author Expand All Advertisement PDF DownloadLoading ...

Reducing the number of systematic biopsy cores in the era of MRI targeted biopsy—implications on clinically-significant prostate cancer detection and relevance to focal therapy planning

BackgroundThe optimal number of systematic biopsy cores in the era of multi-parametric MRI targeted biopsy remains unclear, especially on its impact of focal therapy planning. Our objective is to investigate the impact of reducing the number of systematic cores on prostate cancer detection in the era of MRI-US fusion targeted biopsy and as well as its relevance in template planning for focal therapy.Materials and methodsA retrospective analysis of 398 consecutive men who underwent both systematic saturation (~24 cores) and MRI-US fusion targeted biopsy was performed. Four reduced-core systematic biopsy strategies (two-thirds, half, one-third and one-quarter systematic cores) were modelled and the detection rates of clinically-significant prostate cancer (csPCa defined as grade group ≥2) were compared to that of a full systematic biopsy using McNemar’s test. Focal therapy treatment plans were made based on positive cores on combined (targeted and systematic) biopsy and the various reduced-cores strategies to compare the proportion who had a change in treatment plan.ResultscsPCa was detected in 42% (168/398) of this patient cohort. Non-targeted systematic saturation biopsy had a 21% (83/398) csPCa detection rate. Our four strategies reduced the mean number of non-targeted systematic cores from 21.8 to 14.5, 10.9, 7.3 and 5.4 cores and their csPCa detection rates were significantly decreased to 16%, 13%, 9% and 8% respectively (all p < 0.05). Compared to the reduced-core strategies, a full systematic saturation biopsy resulted in change to the focal therapy treatment plan in 12% (2/3 cores), 19% (1/2 cores), 24% (1/3 cores) and 29% (1/4 cores) of the time (p = 0.0434).ConclusionsReducing the number of systematic biopsies when performing an MRI-targeted biopsy leads to reduced detection of csPCa and alter the treatment plans for focal therapy, possibly limiting its oncological efficacy.

Evaluation of clinically significant prostate cancer using biparametric magnetic resonance imaging: An evolving concept.

Multiparametric magnetic resonance imaging (mp-MRI) of prostate involves a combination of T2-weighted imaging, diffusion-weighted imaging, and dynamic contrast-enhanced (DCE) scans. However, controversy exists in the literature regarding the true value of DCE in the detection of clinically significant (CS) prostate cancer (PCa). The aim of this study is to compare the role of biparametric MRI (bp-MRI) and mp-MRI in the detection of CS PCa. Thirty-six patients with raised serum prostate-specific antigen levels were included. Bp-MRI was performed in all patients, whereas mp-MRI was performed in 30 cases only. The findings were characterized on the basis of prostate imaging reporting and data system (PI-RADS) v2 grading. PI-RADS v2 score of 3 or more was considered CS PCa. All patients underwent transrectal ultrasound-guided biopsy. Gleason score >6 was considered CS. Statistical analysis was done using the SPSS software and results interpreted. CS PCa was observed in 31 cases on histopathology. On bp-MRI, CS PCa was seen in 31 patients. Five cases of PI-RADS v2 score 3 were seen on bp-MRI and 3 of them were upgraded to PI-RADS 4 on DCE images. One case of PI-RADS 3 had low Gleason score on biopsy, whereas 1 case of PI-RADS 2 had CS PCa on biopsy. No significant difference was observed between bp-MRI and mp-MRI in the detection of CS PCa. Both bp-MRI and mp-MRI have high sensitivity, specificity, and diagnostic accuracy and were nearly identical in the detection of CS PCa with no significant advantage of DCE images.

Multiparametric ultrasound of prostate: role in prostate cancer diagnosis.

Recent advances in ultrasonography (US) technology established modalities, such as Doppler-US, HistoScanning, contrast-enhanced ultrasonography (CEUS), elastography, and micro-ultrasound. The early results of these US modalities have been promising, although there are limitations including the need for specialized equipment, inconsistent results, lack of standardizations, and external validation. In this review, we identified studies evaluating multiparametric ultrasonography (mpUS), the combination of multiple US modalities, for prostate cancer (PCa) diagnosis. In the past 5 years, a growing number of studies have shown that use of mpUS resulted in high PCa and clinically significant prostate cancer (CSPCa) detection performance using radical prostatectomy histology as the reference standard. Recent studies have demonstrated the role mpUS in improving detection of CSPCa and guidance for prostate biopsy and therapy. Furthermore, some aspects including lower costs, real-time imaging, applicability for some patients who have contraindication for magnetic resonance imaging (MRI) and availability in the office setting are clear advantages of mpUS. Interobserver agreement of mpUS was overall low; however, this limitation can be improved using standardized and objective evaluation systems such as the machine learning model. Whether mpUS outperforms MRI is unclear. Multicenter randomized controlled trials directly comparing mpUS and multiparametric MRI are warranted.

The stanford prostate cancer calculator: Development and external validation of online nomograms incorporating PIRADS scores to predict clinically significant prostate cancer.

While multiparametric MRI (mpMRI) has high sensitivity for detection of clinically significant prostate cancer (CSC), false positives and negatives remain common. Calculators that combine mpMRI with clinical variables can improve cancer risk assessment, while providing more accurate predictions for individual patients. We sought to create and externally validate nomograms incorporating Prostate Imaging Reporting and Data System (PIRADS) scores and clinical data to predict the presence of CSC in men of all biopsy backgrounds. Data from 2125 men undergoing mpMRI and MR fusion biopsy from 2014 to 2018 at Stanford, Yale, and UAB were prospectively collected. Clinical data included age, race, PSA, biopsy status, PIRADS scores, and prostate volume. A nomogram predicting detection of CSC on targeted or systematic biopsy was created. Biopsy history, Prostate Specific Antigen (PSA) density, PIRADS score of 4 or 5, Caucasian race, and age were significant independent predictors. Our nomogram-the Stanford Prostate Cancer Calculator (SPCC)-combined these factors in a logistic regression to provide stronger predictive accuracy than PSA density or PIRADS alone. Validation of the SPCC using data from Yale and UAB yielded robust AUC values. The SPCC combines pre-biopsy mpMRI with clinical data to more accurately predict the probability of CSC in men of all biopsy backgrounds. The SPCC demonstrates strong external generalizability with successful validation in two separate institutions. The calculator is available as a free web-based tool that can direct real-time clinical decision-making.

MP05-06 DIAGNOSTIC ACCURACY OF ADC VALUE ON BIPARAMETRIC MRI FOR DETECTING CLINICALLY SIGNIFICANT PROSTATE CANCER

You have accessJournal of UrologyProstate Cancer: Detection & Screening I (MP05)1 Sep 2021MP05-06 DIAGNOSTIC ACCURACY OF ADC VALUE ON BIPARAMETRIC MRI FOR DETECTING CLINICALLY SIGNIFICANT PROSTATE CANCER Jih Hoon Park, Ja Yoon Ku, and Hong Koo Ha Jih Hoon ParkJih Hoon Park More articles by this author , Ja Yoon KuJa Yoon Ku More articles by this author , and Hong Koo HaHong Koo Ha More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000001972.06AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: PI-RADS v2 is helpful for the detection of clinically significant prostate cancer (CS-PCa), but does not provide quantitative information. We conducted this study to evaluate the diagnostic accuracy of apparent diffusion coefficient (ADC) value for detecting CS-PCa with TRUS-MR fusion biopsy using 3T biparametric MRI (bpMRI). METHODS: We enrolled 310 patients with elevated PSA level over 4 ng/mL who underwent bpMRI followed by TRUS-MR fusion biopsy of prostate between June 2016 and June 2019. Patients underwent MRI examination on Achieva 3.0T TX MRI Scanner from Philips. The suspicious lesions were indicated by experienced radiologists according to PI-RADS v2, marked as a region-of-interest (ROI) and targeted by TRUS-MR fusion biopsy. ADC values were calculated for a pair of b values: 50 and 1400 s/mm2. ADC values of ROIs were recorded by averaging the values measured at least three times each by two urologists. The size of ROIs was chosen to be as large as possible and with minimal contamination from normal tissue. CS-PCa was defined as ISUP grade of 2 or greater. Lower grade (LG) PCa was defined as ISUP grade 1 or 2, and higher grade (HG) as ISUP grade over 2. RESULTS: Of the 502 lesions indicated and biopsied, 348 (69.3%) were on peripheral zone (PZ) and 154 (30.7%) on transitional zone (TZ). In PZ, 101 (29.0%) lesions were diagnosed with PCa, including 73 (21.0%) with CS-PCa, and in TZ, 39 (25.3%) and 21 (13.6%) were detected with PCa and CS-PCa, respectively. Receiver operating characteristic (ROC) curve analyses showed larger area under curve (AUC) for ADC value compared to PI-RADS (0.902 vs 0.827) for detecting CS-PCa in PZ, but not in TZ (0.797 vs 0.786). According to DeLong test there was a statistically significant better AUC for ADC value on ROC curve analysis compared to PI-RADS in PZ (p=0.0095), but not in TZ (p=0.8496). Mean ADC value (x10-3 mm2/s) of the lesions diagnosed with benign prostatic tissues was 0.929 (95% CI 0.906-0.953), and was different statistically significant with that of LG PCa tissues (mean=0.643, 95% CI 0.591-0.695, p<0.001) and that of HG PCa tissue (mean=0.576, 95% CI 0.540-0.610, p<0.001). The difference between LG and HG PCa tissues was statistically significant (p=0.034). CONCLUSIONS: Predictive role of ADC value on biparametric MRI before TRUS-MR fusion biopsy is better than PI-RADS v2 in detection of CS-PCa. Source of Funding: No source of funding © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e79-e80 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Jih Hoon Park More articles by this author Ja Yoon Ku More articles by this author Hong Koo Ha More articles by this author Expand All Advertisement Loading ...

Diagnostic accuracy of the Novel 29 MHz micro-ultrasound "ExactVuTM" for the detection of clinically significant prostate cancer: A prospective single institutional study. A step forward in the diagnosis of prostate cancer.

ExactVuTM is a real-time micro-ultrasound system which provides, according to the Prostate Risk Identification Using Micro-Ultrasound protocol (PRI-MUS), a 300% higher resolution compared to conventional transrectal ultrasound. To evaluate the performance of ExactVuTM in the detection of Clinically significant Prostate Cancer (CsPCa). Patients with Prostate Cancer diagnosed at fusion biopsy were imaged with ExactVuTM. CsPCa was defined as any Gleason Score ≥ 3+4. ExactVuTM examination was considered as positive when PRI-MUS score was ≥ 3. PRI-MUS scoring system was considered as correct when the fusion biopsy was positive for CsPCa. A transrectal fusion biopsy- proven CsPCa was considered as a gold standard. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under the receiver operator characteristic (ROC) curve (AUC) were calculated. 57 patients out of 68 (84%) had a csPCa. PRI-MUS score was correctly assessed in 68% of cases. Regarding the detection of CsPCa, ExactVuTM 's sensitivity, specificity, PPV, and NPV was 68%, 73%, 93%, and 31%, respectively and the AUC was 0.7 (95% CI 0.5-0-8). For detecting CsPCa in the transition/ anterior zone the sensitivity, specificity, PPV, and NPV was 45%, 66%, 83% and 25% respectively ant the AUC was 0.5 (95% CI 0.2-0.9). Accounting only the CsPCa located in the peripheral zone, sensitivity, specificity, PPV, and NPV raised up to 74%, 75%, 94%, 33%, respectively with AUC 0.75 (95% CI 0.5-0-9). ExactVuTM provides high resolution of the prostatic peripheral zone and could represent a step forward in the detection of CsPCa as a triage tool. Further studies are needed to confirm these promising results.

The diagnostic impact of UK regional variations in age-specific prostate-specific antigen guidelines.

The ideal prostate cancer diagnostic pathway would maximise detection of clinically-significant prostate cancer (csPCa) while avoiding unnecessary biopsies and other investigations. The introduction of pre-biopsy MRI has done much to aid this goal. However, referrals into the image-based diagnostic pathway still depends on prostate-specific antigen (PSA) testing performed in primary care and interpreted using referral guidelines. In the UK, the National Institute for Health and Care Excellence (NICE) only provides guidance on PSA thresholds for men aged 50-69 years (PSA ≥3.0 ng/mL) [1]. For other age groups, PSA thresholds are set by regional cancer networks without any unified consensus. Here we explored if different regional guidelines impacted csPCa detection in modern image-based pathways.

Analysis of risk factors for determining the need for prostate biopsy in patients with negative MRI

To analyze the clinical characteristics of patients with negative biparametric magnetic resonance imaging (bpMRI) who didn’t need prostate biopsies (PBs). A total of 1,012 male patients who underwent PBs in the First Affiliated Hospital of Nanjing Medical University from March 2018 to November 2019, of 225 had prebiopsy negative bpMRI (defined as Prostate Imaging Reporting and Data System (PI-RADS 2.1) score less than 3). The detection efficiency of clinically significant prostate cancer (CSPCa) was assessed according to age, digital rectal examination (DRE), prostate volume (PV) on bpMRI, prostate-specific antigen (PSA) and PSA density (PSAD). The definition of CSPCa for Gleason score > 6. Univariate and multivariable logistic regression analysis were used to identify predictive factors of absent CSPCa on PBs. Moreover, absent CSPCa contained clinically insignificant prostate cancer (CIPCa) and benign result. The detection rates of present prostate cancer (PCa) and CSPCa were 27.11% and 16.44%, respectively. Patients who were diagnosed as CSPCa had an older age (P < 0.001), suspicious DRE (P < 0.001), a smaller PV (P < 0.001), higher PSA value (P = 0.008) and higher PSAD (P < 0.001) compared to the CIPCa group and benign result group. PSAD < 0.15 ng/ml/cm3 (P = 0.004) and suspicious DRE (P < 0.001) were independent predictors of absent CSPCa on BPs. The negative forecast value of bpMRI for BP detection of CSPCa increased with decreasing PSAD, mainly in patients with naive PB (P < 0.001) but not in prior negative PB patients. 25.33% of the men had the combination of negative bpMRI, PSAD < 0.15 ng/ml/cm3 and PB naive, and none had CSPCa on repeat PBs. The incidence of PB was determined, CSPCa was 1.59%, 0% and 16.67% in patients with negative bpMRI and PSAD < 0.15 ng/ml/cm3, patients with negative bpMRI, PSAD < 0.15 ng/ml/cm3 and biopsy naive and patients with negative bpMRI, PSAD < 0.15 ng/ml/cm3 and prior negative PB, separately. We found that a part of patients with negative bpMRI, a younger age, no suspicious DRE and PSAD < 0.15 ng/ml/cm3 may securely avoid PBs. Conversely PB should be considered in patients regardless of negative bpMRI, especially who with a greater age, obviously suspicious DRE, significantly increased PSA value, a significantly small PV on MRI and PSAD > 0.15 ng/ml/cm3.

Interreader agreement in different PI-RADS systems in multiparametric prostate magnetic resonance imaging: A head-to-head comparison between PI-RADSv2 and v2.1

Aim The purpose of this study is to compare PI-RADSv2 with v2.1 in terms of interreader agreement and diagnostic performance in clinically significant prostate cancer (CSCa) detection. Materials and Methods Two hundred-two patients who had both multiparametric prostate magnetic resonance imaging (mpMRI) and 12 quadrant systematic biopsies were included in this retrospective study. Acquisition parameters were totally complied with proposal of PI-RADSv2 and 2.1 guidelines. mpMRIs were evaluated by two radiologists independently. Index lesion’s score was used to determine diagnostic performance of the systems. Gleason ≥ 3+4 tumors were considered CSCa. Kappa statistic was used to determine interreader agreement. Area under the curve (AUC) was calculated in detection of CSCa using receiver operating characteristic curve (ROC). Results The numbers of cases with PI-RADSv2 and v2.1 scores from 1 to 5 were 46, 21, 13, 41, 81 and 46, 26, 9, 43, 78, by reader 1 and 51, 10, 18, 43, 80 and 51, 15, 19, 37, 80 by reader 2, respectively. There was “substantial” agreement between two readers for both scoring systems. Kappa values were 0.600 in PI-RADSv2 and 0.624 in PI-RADSv2.1. Ninety-eight (48.5%) patients had CSCa. AUC values of PI-RADSv2 and v2.1 scoring systems were 0.861 and 0.851 for reader 1, 0.873 and 0.883 for reader 2, respectively. Conclusion Interreader agreement was “substantial” in mpMRI and slightly improved with PI-RADSv2.1. Diagnostic performance of the two systems were almost equal.