Validation of Prostate Imaging Reporting and Data System Version 2 for the Detection of Prostate Cancer

Accuracy of MRI-ultrasound fusion-guided and systematic biopsy of the prostate

OBJECTIVES

Prostate multiparametric MRI (mpMRI) with subsequent targeted biopsy of suspicious lesions has a critical role in the diagnostic workup of prostate cancer. The objective was to evaluate the diagnostic accuracy of systematic biopsies, targeted biopsies, and the combination of both in prostate cancer detection.

METHODS

From January 1, 2013 to June 1, 2022, biopsy-naïve and prior biopsy-negative patients who underwent both systematic and targeted biopsies were included. MRIs were evaluated according to PI-RADS with biopsy threshold set at PI-RADS ≥3. Systematic biopsies consisted of 8-12 cores, based on prostate volume. Overall prostate cancer and clinically significant cancer (Gleason Score ≥3 + 4) detection rates were stratified based on PI-RADS and location within the prostate, and compared between biopsy types using McNemar test.

RESULTS

Among 867 patients, 615 had prostate cancer, with 434 clinically significant cases. Overall detection rates were: PI-RADS 3 48%, PI-RADS 4 72%, and PI-RADS 5 90%. Detection rates for clinically significant cancer were 21%, 53%, and 72%, respectively. The combination of biopsy methods was most accurate in detecting clinically significant prostate cancer (P < .001). Targeted biopsies alone detected more clinically significant prostate cancer than systematic biopsies alone (43.1% vs 40.3%, P = .046). For posterior PI-RADS 5 lesions, no statistically significant difference was found between all biopsy methods.

CONCLUSIONS

In the detection of clinically significant prostate cancer, the combination of systematic and targeted biopsies proves most effective. Targeted biopsies rarely missed significant cancer for posterior PI-RADS 5 lesions, suggesting systematic biopsies could be reserved for instances where targeted biopsy results are negative.

ADVANCES IN KNOWLEDGE

This study emphasizes on the efficacy of mpMRI and targeted biopsies in suspected prostate cancer in real-world clinical context. For PI-RADS 5 lesions, systematic biopsies provide limited clinical benefit and may only be necessary when targeted biopsy results are negative.

Reduction of false positives using zone-specific prostate-specific antigen density for prostate MRI-based biopsy decision strategies

OBJECTIVES

To develop and test zone-specific prostate-specific antigen density (sPSAD) combined with PI-RADS to guide prostate biopsy decision strategies (BDS).

METHODS

This retrospective study included consecutive patients, who underwent prostate MRI and biopsy (01/2012-10/2018). The whole gland and transition zone (TZ) were segmented at MRI using a retrained deep learning system (DLS; nnU-Net) to calculate PSAD and sPSAD, respectively. Additionally, sPSAD and PI-RADS were combined in a BDS, and diagnostic performances to detect Grade Group ≥ 2 (GG ≥ 2) prostate cancer were compared. Patient-based cancer detection using sPSAD was assessed by bootstrapping with 1000 repetitions and reported as area under the curve (AUC). Clinical utility of the BDS was tested in the hold-out test set using decision curve analysis. Statistics included nonparametric DeLong test for AUCs and Fisher-Yates test for remaining performance metrics.

RESULTS

A total of 1604 patients aged 67 (interquartile range, 61-73) with 48% GG ≥ 2 prevalence (774/1604) were evaluated. By employing DLS-based prostate and TZ volumes (DICE coefficients of 0.89 (95% confidence interval, 0.80-0.97) and 0.84 (0.70-0.99)), GG ≥ 2 detection using PSAD was inferior to sPSAD (AUC, 0.71 (0.68-0.74)/0.73 (0.70-0.76); p < 0.001). Combining PI-RADS with sPSAD, GG ≥ 2 detection specificity doubled from 18% (10-20%) to 43% (30-44%; p < 0.001) with similar sensitivity (93% (89-96%)/97% (94-99%); p = 0.052), when biopsies were taken in PI-RADS 4-5 and 3 only if sPSAD was ≥ 0.42 ng/mL/cc as compared to all PI-RADS 3-5 cases. Additionally, using the sPSAD-based BDS, false positives were reduced by 25% (123 (104-142)/165 (146-185); p < 0.001).

CONCLUSION

Using sPSAD to guide biopsy decisions in PI-RADS 3 lesions can reduce false positives at MRI while maintaining high sensitivity for GG ≥ 2 cancers.

CLINICAL RELEVANCE STATEMENT

Transition zone-specific prostate-specific antigen density can improve the accuracy of prostate cancer detection compared to MRI assessments alone, by lowering false-positive cases without significantly missing men with ISUP GG ≥ 2 cancers.

KEY POINTS

• Prostate biopsy decision strategies using PI-RADS at MRI are limited by a substantial proportion of false positives, not yielding grade group ≥ 2 prostate cancer. • PI-RADS combined with transition zone (TZ)-specific prostate-specific antigen density (PSAD) decreased the number of unproductive biopsies by 25% compared to PI-RADS only. • TZ-specific PSAD also improved the specificity of MRI-directed biopsies by 9% compared to the whole gland PSAD, while showing identical sensitivity.

Multiparametric Magnetic Resonance Imaging- Guided Dose-Escalated Radiation Therapy for Localized Prostate Cancer: A Prospective Phase 2 Trial

PURPOSE

This trial's purpose was to determine the late toxicity associated with dose escalation to Prostate Imaging Reporting and Data System (PI-RADS) III-V lesions on multiparametric magnetic resonance imaging (MRI) with an image guided combined IMRT-stereotactic body radiation therapy (SBRT) approach in men with localized prostate cancer.

METHODS AND MATERIALS

In this phase 2 trial patients with localized prostate cancer with clinical tumor stage T1-T3bN0 and at least one PIRADS III-V lesion were recruited to receive 45 Gy in 25 fractions to the prostate and seminal vesicles followed by a boost of 18 Gy in 3 fractions to the prostate with a simultaneous integrated boost 21 Gy in 3 fractions to the PI-RADS lesion(s). The primary endpoint was the cumulative incidence of late grade ≥3 genitourinary and gastrointestinal toxicity by 18 months (National Cancer Institute Common Terminology Criteria for Adverse Events, version 4.0).

RESULTS

Overall, 50 patients were enrolled in this study, and 43 patients completed at least 18 months of follow-up. The cumulative incidence of grade 1, 2, and 3 late genitourinary toxicity at 18 months was 18%, 53%, and 2%. One patient was noted to have grade 3 hematuria and needed cystoscopy-guided cauterization. No acute grade 3 gastrointestinal or genitourinary toxicities were observed. The cumulative incidence of grade 1, 2, and 3 late gastrointestinal toxicity at 18 months was 31%, 4%, and 0%, respectively. At a median follow-up of 43.5 months, 3 patients developed biochemical recurrence, each with distant bone metastases without local or nodal recurrence. At 3 years, freedom from biochemical failure rate was 95.3% (95% CI, 89.2%-100%).

CONCLUSIONS

Multiparametric MRI-guided dose escalation to PI-RADS III-V lesions using a combined image guided IMRT-SBRT approach is associated with an acceptable risk of late gastrointestinal and genitourinary toxicity. The results should be interpreted with caution considering their single institutional nature, small sample size, and short follow-up and should be validated in a larger study.

MRI-targeted biopsy cores from prostate index lesions: assessment and prediction of the number needed

BACKGROUND

Magnetic resonance imaging (MRI) is used to detect the prostate index lesion before targeted biopsy. However, the number of biopsy cores that should be obtained from the index lesion is unclear. The aim of this study is to analyze how many MRI-targeted biopsy cores are needed to establish the most relevant histopathologic diagnosis of the index lesion and to build a prediction model.

METHODS

We retrospectively included 451 patients who underwent 10-core systematic prostate biopsy and MRI-targeted biopsy with sampling of at least three cores from the index lesion. A total of 1587 biopsy cores were analyzed. The core sampling sequence was recorded, and the first biopsy core detecting the most relevant histopathologic diagnosis was identified. In a subgroup of 261 patients in whom exactly three MRI-targeted biopsy cores were obtained from the index lesion, we generated a prediction model. A nonparametric Bayes classifier was trained using the PI-RADS score, prostate-specific antigen (PSA) density, lesion size, zone, and location as covariates.

RESULTS

The most relevant histopathologic diagnosis of the index lesion was detected by the first biopsy core in 331 cases (73%), by the second in 66 cases (15%), and by the third in 39 cases (9%), by the fourth in 13 cases (3%), and by the fifth in two cases (<1%). The Bayes classifier correctly predicted which biopsy core yielded the most relevant histopathologic diagnosis in 79% of the subjects. PI-RADS score, PSA density, lesion size, zone, and location did not independently influence the prediction model.

CONCLUSION

The most relevant histopathologic diagnosis of the index lesion was made on the basis of three MRI-targeted biopsy cores in 97% of patients. Our classifier can help in predicting the first MRI-targeted biopsy core revealing the most relevant histopathologic diagnosis; however, at least three MRI-targeted biopsy cores should be obtained regardless of the preinterventionally assessed covariates.

Prostate imaging-reporting and data system version 2 in combination with clinical parameters for prostate cancer detection: a single center experience

PURPOSE

The diagnostic performance of the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) has been challenged due to its lower diagnostic accuracy and higher false-positive rates for prostate cancer detection. This study aimed to analyze the diagnostic performance of PI-RADS v2 in combination with clinical parameters in patients with suspected prostate cancer.

MATERIAL AND METHODS

A total of 424 men with suspicion of prostate cancer were retrospectively analyzed. Logistic regression analyses were performed to identify predictors of clinically significant prostate cancer defined as a Gleason score of 3 + 4 or greater. The prediction performance was compared with prostate specific antigen (PSA), free/total PSA ratio (f/t PSA), PSA density (PSAD), PI-RADS v2 alone, and PI-RADS v2 plus PSAD using receiver operating characteristics (ROCs).

RESULTS

In total, 231 out of 424 cases (54.48%) were pathologically diagnosed as prostate cancer. The percentage of clinically significant prostate cancer was higher in patients with PI-RADS v2 score of 4 or greater compared to PI-RADS v2 score of less than 4 (90.86% vs. 55.88%, P < 0.001). Age, PSA level, f/t PSA, PSAD, and PI-RADS v2 were significant independent predictors of clinically significant prostate cancer. The ROC area under the curve of PI-RADS v2 plus PSAD (0.952) was larger compared with PSA (0.845), f/t PSA (0.719), PSAD (0.920), and PI-RADS v2 alone (0.885).

CONCLUSION

PI-RADS v2 in combination with PSAD may help detect clinically significant prostate cancer and provide benefit in making the decision to biopsy men at suspicion of prostate cancer.

A dynamic-static combination model based on radiomics features for prostate cancer using multiparametric MRI

Objective. To propose a new dynamic multiparametric magnetic resonance imaging (mpMRI) radiomics method for the detection of prostate cancer (PCa), and establish a combined model using dynamic and static radiomics features based on this method.Approach. A total of 166 patients (82 PCa patients and 84 non-PCa patients) were enrolled in the study, and 31 872 mpMRI images were performed in a radiomics workflow. The whole prostate segmentation and traditional static radiomics features extraction were performed on intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI,bvalue of 10, 50, 100, 150, 200, 400, 600, 800, 1000, 1500 s mm^-2respectively), apparent diffusion coefficient (ADC), and T2-weighted imaging (T2WI) sequences respectively. Through the building of eachb-value DWI model and the analysis of the static key radiomics features, three types of dynamic features called standard discrete (SD), parameter (P) and relative change rate (RCR) were constructed. And the b-value parameters used to construct dynamic features were divided into three groups ('Df_', 'Db_' and 'Da_'): the front part (10-200 s mm^-2), the back part (400-1500 s mm^-2), and all (10-1500 s mm^-2) of theb-values set, respectively. Afterwards, the dynamic mpMRI model and combined model construction were constructed, and the PCa discrimination performance of each model was evaluated.Main results.The models based on dynamic features showed good potential for PCa identification. Where, the results of Db_SD, Da_P and Db_P models were encouraging (test cohort AUCs: 90.78%, 87.60%, 86.3%), which was better than the commonly used ADC model (AUC of ADC was 75.48%). Among the combined models, the models using static features of T2WI and dynamic features performed the best. The AUC of Db_SD + T2WI, Db_P + T2WI and Db_RCR + T2WI model was 92.90%, 91.29% and 81.46%.Significance.The dynamic-static combination model based on dynamic mpMRI radiomics method has a good effect on the identification of PCa. This method has broad application prospects in PCa individual diagnosis management.

Predictors of Unfavorable Pathology in Patients with Incidental (pT1a-T1b) Prostate Cancer

BACKGROUND

Incidental prostate cancer (IPCa) is encountered in 10% of surgical procedures for benign prostatic obstruction (BPO). Identification of patients with underlying detrimental prostate cancer is paramount for tailored treatment decision-making, but guideline recommendations for this setting are lacking.

OBJECTIVE

To highlight clinical and histological characteristics related to BPO surgery that may predict IPCa with unfavorable pathology.

DESIGN, SETTING, AND PARTICIPANTS

We included men with IPCa who underwent radical prostatectomy (RP) in the short term after IPCa diagnosis. Two cohorts were built according to final pathology for the RP specimen: unfavorable pathology (International Society of Urological Pathology [ISUP] grade group [GG] ≥3 and/or ≥pT3a and/or pN1) versus favorable pathology.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

We performed multivariate regression analysis for the endpoint, which was unfavorable pathology for the RP specimen. Using the model estimates for prostate-specific antigen (PSA), ISUP GG, age, and prostate volume, we established a model for estimating the risk of unfavorable histopathology.

RESULTS AND LIMITATIONS

Overall, 112 patients were included in the final assessment. On multivariate analysis, PSA (odds ratio [OR] 1.083, 95% confidence interval [CI] 1.003-1.170; p = 0.042), ISUP GG for the specimen from BPO surgery (OR 3.090; 95% CI 1.129-8.457; p = 0.028), and age (OR 1.121, 95% CI 1.026-1.225; p = 0.012) were independent predictors for unfavorable histopathology. On receiver operating characteristic analysis, the area under the curve was 0.751. A novel calculator was developed to predict adverse pathology for men with IPCa. The study is limited by its retrospective design.

CONCLUSIONS

For men with IPCa, PSA before surgery for BPO, ISUP GG, and age are independent predictors of unfavorable disease. Our results might improve preoperative risk assessment for patient counseling.

PATIENT SUMMARY

We developed a novel calculator to estimate the risk of underlying detrimental disease in men diagnosed with prostate cancer at surgery for benign prostatic obstruction.

Follow-up of men with a PI-RADS 4/5 lesion after negative MRI/Ultrasound fusion biopsy

Magnetic resonance imaging/Ultrasound (MRI/US) fusion targeted biopsy (TB) in combination with a systematic biopsy (SB) improves cancer detection but limited data is available how to manage patients with a Prostate Imaging-Reporting and Data System (PI-RADS) ≥ 4 lesion and a negative biopsy. We evaluate the real-world management and the rate of clinically significant Prostate Cancer (csPCa) during follow-up. 1546 patients with a multi-parametric MRI (mpMRI) and a PI-RADS ≥ 3 who underwent SB and TB between January 2012 and May 2017 were retrospectively analyzed. 222 men with a PI-RADS ≥ 4 and a negative biopsy were included until 2019. For 177/222 (80%) complete follow-up data was obtained. 66/84 (78%) had an initial PI-RADS 4 and 18 (22%) a PI-RADS 5 lesion. 48% (84/177) received a repeat mpMRI; in the follow-up mpMRI, 39/84 (46%) lesions were downgraded to PI-RADS 2 and 11 (13%) to PI-RADS 3; three cases were upgraded and 28 lesions remained consistent. 18% (32/177) men underwent repeated TB and csPCa was detected in 44% (14/32). Our study presents real world data on the management of men with a negative TB biopsy. Men with a positive mpMRI and lesions with high suspicion (PI-RADS4/5) and a negative targeted biopsy should be critically reviewed and considered for repeat biopsy or strict surveillance. The optimal clinical risk assessment remains to be further evaluated.

Prostate MRI percentage tumor involvement or "PI-RADS percent" as a predictor of adverse surgical pathology

BACKGROUND

This study assesses magnetic resonance imaging (MRI) prostate % tumor involvement or "PI-RADs percent" as a predictor of adverse pathology (AP) after surgery for localized prostate cancer (PCa). Two separate variables, "All PI-RADS percent" (APP) and "Highest PI-RADS percent" (HPP), are defined as the volume of All PI-RADS 3-5 score lesions on MRI and the volume of the Highest PI-RADS 3-5 score lesion each divided by TPV, respectively.

METHOD

An analysis was done of an IRB approved prospective cohort of 557 patients with localized PCa who had targeted biopsy of MRI PIRADs 3-5 lesions followed by RARP from April 2015 to May 2020 performed by a single surgeon at a single center. AP was defined as ISUP GGG ≥3, pT stage ≥T3 and/or LNI. Univariate and multivariable analyses were used to evaluate APP and HPP at predicting AP with other clinical variables such as Age, PSA at surgery, Race, Biopsy GGG, mpMRI ECE and mpMRI SVI. Internal and External Validation demonstrated predicted probabilities versus observed probabilities.

RESULTS

AP was reported in 44.5% (n = 248) of patients. Multivariable regression showed both APP (odds ratio [OR]: 1.10, 95% confidence interval [CI]: 1.04-1.14, p = 0.0007) and HPP (OR: 1.10; 95% CI: 1.04-1.16; p = 0.0007) were significantly associated with AP with individual area under the operating curves (AUCs) of 0.6142 and 0.6229, respectively, and AUCs of 0.8129 and 0.8124 when incorporated in models including preoperative PSA and highest biopsy GGG.

CONCLUSIONS

Increasing PI-RADS Percent was associated with a higher risk of AP, and both APP and HPP may have clinical utility as predictors of AP in GGG 1 and 2 patients being considered for AS.

PATIENT SUMMARY

Using PIRADs percent to predict AP for presurgical patients may help risk stratification, and for low and low volume intermediate risk patients, may influence treatment decisions.

Transrectal ultrasound features and biopsy outcomes of transition PI-RADS 5

BACKGROUND

Transition Prostate Imaging and Reporting and Data System (PI-RADS) 5 is easily detected owing to typical magnetic resonance imaging features. However, it is unclear as to how transition PI-RADS 5 appears on transrectal ultrasound (TRUS).

PURPOSE

To assess TRUS features of transition PI-RADS 5 and outcomes of TRUS-guided target biopsy.

MATERIAL AND METHODS

Between March 2014 and November 2018, 186 male patients underwent TRUS-guided biopsy of PI-RADS 5. Of them, 82 and 104were transition and peripheral PI-RADS 5, respectively. Transition and peripheral PI-RADS 5 were compared according to echogenicity (hyperechoic or hypoechoic) and hypoechoic rim (present or absent). Each tumor was targeted with TRUS based on TRUS features. Significant (Gleason score ≥7) and insignificant (Gleason score 6) cancer detection rates (CDRs) were compared between transition and peripheral PI-RADS 5. Standard reference was biopsy examination. Fisher's exact test was used for statistical analysis.

RESULTS

Transition PI-RADS 5 was hyperechoic in 89.0% (73/82) and had a hypoechoic rim in 97.6% (80/82), whereas peripheral PI-RADS 5 was hypoechoic in 99.0% (103/104) and had a hypoechoic rim in 26.9% (28/104) (both, P<0.0001). The significant CDRs of transition and peripheral PI-RADS 5 were 56.1% (46/82) and 65.4% (68/104), respectively (P=0.2263). However, the insignificant CDRs of these categories were 22.0% (18/82) and 8.7% (9/104), respectively (P=0.0123).

CONCLUSION

Transition PI-RADS 5 tends to have hyperechoic echogenicity and a hypoechoic rim. These findings help to target the transition PI-RADS 5 using TRUS. However, transition PI-RADS 5 is confirmed more frequently as insignificant cancer than peripheral PI-RADS 5.

PI-RADS and Likert scales for structured reporting in multiparametric MR imaging of the prostate

Multiparametric MRI (mpMRI) plays a critical role in the detection, staging and risk stratification of prostate cancer (PCa). There are two widely accepted structured reporting systems used for interpretation of mpMRI of the prostate - PI-RADS v2.1 and Likert. Both these systems demonstrate good diagnostic performance with high cancer detection rates however have key conceptual differences. In this commentary, the authors highlight the individual strengths and areas of potential improvement as well as emphasize the need for continued clinical validation for these interpreting and reporting systems.

MRI as a screening tool for prostate cancer: current evidence and future challenges

Purpose

Prostate cancer (PCa) screening, which relies on prostate-specific antigen (PSA) testing, is a contentious topic that received negative attention due to the low sensitivity and specificity of PSA to detect clinically significant PCa. In this context, due to the higher sensitivity and specificity of magnetic resonance imaging (MRI), several trials investigate the feasibility of “MRI-only” screening approaches, and question if PSA testing may be replaced within prostate cancer screening programs.

Methods

This narrative review discusses the current literature and the outlook on the potential of MRI-based PCa screening.

Results

Several prospective randomized population-based trials are ongoing. Preliminary study results appear to favor the “MRI-only” approach. However, MRI-based PCa screening programs face a variety of obstacles that have yet to be fully addressed. These include the increased cost of MRI, lack of broad availability, differences in MRI acquisition and interpretation protocols, and lack of long-term impact on cancer-specific mortality. Partly, these issues are being addressed by shorter and simpler MRI approaches (5–20 min bi-parametric MRI), novel quality indicators (PI-QUAL) and the implementation of radiomics (deep learning, machine learning).

Conclusion

Although promising preliminary results were reported, MRI-based PCa screening still lack long-term data on crucial endpoints such as the impact of MRI screening on mortality. Furthermore, the issues of availability, cost-effectiveness, and differences in MRI acquisition and interpretation still need to be addressed.

Stratification of prostate cancer patients into low- and high-grade groups using multiparametric magnetic resonance radiomics with dynamic contrast-enhanced image joint histograms

PURPOSE

This study aimed to investigate the potential of stratification of prostate cancer patients into low- and high-grade groups (GGs) using multiparametric magnetic resonance (mpMR) radiomics in conjunction with two-dimensional (2D) joint histograms computed with dynamic contrast-enhanced (DCE) images.

METHODS

A total of 101 prostate cancer regions extracted from the MR images of 44 patients were identified and divided into training (n = 31 with 72 cancer regions) and test datasets (n = 13 with 29 cancer regions). Each dataset included low-grade tumors (International Society of Urological Pathology [ISUP] GG ≤ 2) and high-grade tumors (ISUP GG ≥ 3). A total of 137,970 features consisted of mpMR image (16 types of images in four sequences)-based and joint histogram (DCE images at 10 phases)-based features for each cancer region. Joint histogram features can visualize temporally changing perfusion patterns in prostate cancer based on the joint histograms between different phases or subtraction phases of DCE images. Nine signatures (a set of significant features related to GGs) were determined using the best combinations of features selected using the least absolute shrinkage and selection operator. Further, support vector machine models with the nine signatures were built based on a leave-one-out cross-validation for the training dataset and evaluated with receiver operating characteristic (ROC) curve analysis.

RESULTS

The signature showing the best performance was constructed using six features derived from the joint histograms, DCE original images, and apparent diffusion coefficient maps. The areas under the ROC curves for the training and test datasets were 1.00 and 0.985, respectively.

CONCLUSION

This study suggests that the proposed approach with mpMR radiomics in conjunction with 2D joint histogram computed with DCE images could have the potential to stratify prostate cancer patients into low- and high-GGs.

Single-center versus multi-center biparametric MRI radiomics approach for clinically significant peripheral zone prostate cancer

Objectives

To investigate a previously developed radiomics-based biparametric magnetic resonance imaging (bpMRI) approach for discrimination of clinically significant peripheral zone prostate cancer (PZ csPCa) using multi-center, multi-vendor (McMv) and single-center, single-vendor (ScSv) datasets.

Methods

This study’s starting point was a previously developed ScSv algorithm for PZ csPCa whose performance was demonstrated in a single-center dataset. A McMv dataset was collected, and 262 PZ PCa lesions (9 centers, 2 vendors) were selected to identically develop a multi-center algorithm. The single-center algorithm was then applied to the multi-center dataset (single–multi-validation), and the McMv algorithm was applied to both the multi-center dataset (multi–multi-validation) and the previously used single-center dataset (multi–single-validation). The areas under the curve (AUCs) of the validations were compared using bootstrapping.

Results

Previously the single–single validation achieved an AUC of 0.82 (95% CI 0.71–0.92), a significant performance reduction of 27.2% compared to the single–multi-validation AUC of 0.59 (95% CI 0.51–0.68). The new multi-center model achieved a multi–multi-validation AUC of 0.75 (95% CI 0.64–0.84). Compared to the multi–single-validation AUC of 0.66 (95% CI 0.56–0.75), the performance did not decrease significantly (p value: 0.114). Bootstrapped comparison showed similar single-center performances and a significantly different multi-center performance (p values: 0.03, 0.012).

Conclusions

A single-center trained radiomics-based bpMRI model does not generalize to multi-center data. Multi-center trained radiomics-based bpMRI models do generalize, have equal single-center performance and perform better on multi-center data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-021-01099-y.

Is transrectal ultrasound-guided systematic biopsy necessary after PI-RADS 4 is targeted?

Purpose: Target biopsy is usually performed in Prostate Imaging Reporting and Data System (PI-RADS) 4. Still, it is unclear if adding systematic biopsy to target biopsy influences cancer detection. The aim was to assess the role of systematic biopsy for detecting significant cancer after PI-RADS 4 is targeted.Methods: Between March 2014 and November 2018, 182 men with PI-RADS 4 underwent transrectal ultrasound (TRUS)-guided biopsy. Systematic biopsy was added to target biopsy in 128 men (Group I) by May 2018 because PI-RADS 4 was not completely visible on TRUS, while it was done in 54 men (Group II) from June 2018 regardless of lesion visibility. Significant cancer detection rates (CDRs) were compared between the groups regarding target and systematic biopsies. Major complication rate was also compared. Significant cancer was defined as a Gleason score ≥7 tumor. Standard reference was biopsy examination. Fisher’s exact were used for statistical analysis.Results: The significant CDRs were 21.9% (28/128) in the Group I and 38.9% (21/54) in the Group II (P= 0.0273). The significant cancers of Group I and II were missed in two (1.6%) and in one (1.9%) by target biopsy, respectively. Major complication rates of these groups were 0.8% (1/128) and 0% (0/54), respectively (P= 0.999).Conclusion: Systematic biopsy should be added to target biopsy even though PI-RADS 4 is clearly visible on ultrasound. A significant number of significant cancers are detected with systematic biopsy.

Managing Discordant Findings Between Multiparametric Magnetic Resonance Imaging and Transrectal Magnetic Resonance Imaging-directed Prostate Biopsy-The Key Role of Magnetic Resonance Imaging-directed Transperineal Biopsy

BACKGROUND

Discordant findings between multiparametric magnetic resonance imaging (mpMRI) and transrectal image-guided biopsies of the prostate (TRUS-P) may result in inadequate risk stratification of localized prostate cancer.

OBJECTIVE

To assess transperineal image-guided biopsies of the index target (TPER-IT) in terms of disease reclassification and treatment recommendations.

DESIGN, SETTING, AND PARTICIPANTS

Cases referred for suspicion or treatment of localized prostate cancer were reviewed in a multidisciplinary setting, and discordance was characterized into three scenarios: type I-negative biopsies or International Society of Urological Pathology (ISUP) grade 1 cancer in Prostate Imaging Reporting and Data System (PI-RADS) ≥4 index target (IT); type II-negative biopsies or ISUP grade 1 cancer in anterior IT; and type III-<3 mm stretch of cancer in PI-RADS ≥3 IT. Discordant findings were characterized in 132/558 (23.7%) patients after TRUS-P. Of these patients, 102 received reassessment TPER-IT.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The primary objective was to report changes in treatment recommendations after TPER-IT. Therefore, cores obtained by primary TRUS-P and TPER-IT were analyzed in terms of cancer detection, ISUP grade, and Cambridge Prognostic Group classification using descriptive statistics.

RESULTS AND LIMITATIONS

TPER-IT biopsies that consisted of fewer cores than the initial TRUS-P (seven vs 14, p < 0.0001) resulted in more cancer tissue materials for analysis (56 vs 42.5 mm, p = 0.0003). As a result, 40% of patients initially considered for follow-up (12/30) and 49% for active surveillance (30/61) were reassigned after TPER-IT to surgery or intensity-modulated radiotherapy.

CONCLUSIONS

Nonconcordance between pathology and imaging was observed in a significant proportion of patients receiving TRUS-P. TPER-IT better informed the presence and grade of cancer, resulting in a significant impact on treatment recommendations. A multidisciplinary review of mpMRI and TRUS-P findings and reassessment TPER-IT in type I-II discordances is recommended.

PATIENT SUMMARY

In this report, patients with suspicious imaging of the prostate, but no or well-differentiated cancer on transrectal image-guided -biopsies, were offered transperineal image-guided biopsies for reassessment. We found that a large share of these had a more aggressive cancer than initially suspected. We conclude that discordant results warrant reassessment transperineal image-guided biopsies as these may impact disease risk classification and treatment recommendations.

New TRUS Techniques and Imaging Features of PI-RADS 4 or 5: Influence on Tumor Targeting

Purpose

To determine if the new transrectal ultrasound (TRUS) techniques and imaging features contribute to targeting Prostate Imaging and Reporting and Data System (PI-RADS) 4 or 5.

Materials and Methods

Between December 2018 and February 2020, 115 men underwent cognitive biopsy by radiologist A, who was familiar with the new TRUS findings and biopsy techniques. During the same period, 179 men underwent magnetic resonance imaging–TRUS image fusion or cognitive biopsy by radiologist B, who was unfamiliar with the new biopsy techniques. Prior to biopsy, both radiologists knew MRI findings such as the location, size, and shape of PI-RADS 4 or 5. We recorded how many target biopsies were performed without systematic biopsy and how many of these detected higher Gleason score (GS) than those detected by systematic biopsy. The numbers of biopsy cores were also obtained. Fisher Exact or Mann–Whitney test was used for statistical analysis.

Results

For PI-RADS 4, target biopsy alone was performed in 0% (0/84) by radiologist A and 0.8% (1/127) by radiologist B (p>0.9999). Target biopsy yielded higher GSs in 57.7% (30/52) by radiologist A and 29.5% (23/78) by radiologist B (p = 0.0019). For PI-RADS 5, target biopsy alone was performed in 29.0% (9/31) by radiologist A and 1.9% (1/52) by radiologist B (p = 0.0004). Target biopsy yielded higher GSs in 50.0% (14/28) by radiologist A and 18.2% (8/44) by radiologist B (p = 0.0079). Radiologist A sampled fewer biopsy cores than radiologist B (p = 0.0008 and 0.0023 for PI-RADS 4 and 5), respectively.

Conclusions

PI-RADS 4 or 5 can be more precisely targeted if the new TRUS biopsy techniques are applied.

How does PI-RADS v2.1 impact patient classification? A head-to-head comparison between PI-RADS v2.0 and v2.1

BACKGROUND

PI-RADS classification has recently been updated, with the magnitude of changes implemented currently unknown.

PURPOSE

To quantify the categorization shifts between PI-RADS v2.0 and v2.1.

MATERIAL AND METHODS

Retrospective review of 535 consecutive diagnostic magnetic resonance imaging (MRI) studies performed over 18 months, assigning to each case a PI-RADS category in the peripheral zone (PZ), the transition zone (TZ), and the whole gland using both PI-RADS v2.0 and v2.1. Significance of changes in category assignments and of differences in the number of positive or negative MRIs were evaluated using the McNemar test.

RESULTS

Comparing v2.0 to v2.1 for the whole gland, 11.2% of PI-RADS 2 categories shifted to PI-RADS 1 (6.9% in the PZ, 56.8% in the TZ), 16.1% of PI-RADS 3 categories shifted to PI-RADS 2 (15.0% in the PZ, 20.0% in the TZ), and 2.1% of PI-RADS 2 categories shifted to PI-RADS 3 (0.3% in the PZ, 1.9% in the TZ). The proportion of PI-RADS 1 significantly increased from 0.6% to 7.3%, PI-RADS 2 significantly decreased from 60.0% to 53.8%, and PI-RADS 3 non-significantly decreased from 11.6% to 11.0%. The total number of positive exams (PI-RADS 3-5) did not change significantly (39.4% versus 38.8%).

CONCLUSION

The most prominent change between v2.0 and v2.1 was observed in the TZ with the downgrading of typical benign prostatic hyperplasia nodules from category 2 into category 1. Overall, there were no significant changes in the number of positive and negative MRI results, with an expected low influence in clinical management.

The role of mpMRI in qualification of patients with ISUP 1 prostate cancer on biopsy to radical prostatectomy

BACKGROUND

To investigate the role of mpMRI and high PIRADS score as independent triggers in the qualification of patients with ISUP 1 prostate cancer on biopsy to radical prostatectomy.

METHODS

Between January 2017 and June 2019, 494 laparoscopic radical prostatectomies were performed in our institution, including 203 patients (41.1%) with ISUP 1 cT1c-2c PCa on biopsy. Data regarding biopsy results, digital rectal examination, PSA, mpMRI and postoperative pathological report have been retrospectively analysed.

RESULTS

In 183 cases (90.1%) mpMRI has been performed at least 6 weeks after biopsy. Final pathology revealed ISUP Gleason Grade Group upgrade in 62.6% of cases. PIRADS 5, PIRADS 4 and PIRADS 3 were associated with Gleason Grade Group upgrade in 70.5%, 62.8%, 48.3% of patients on final pathology, respectively. Within PIRADS 5 group, the number of upgraded cases was statistically significant.

CONCLUSIONS

PIRADS score correlates with an upgrade on final pathology and may justify shared decision of radical treatment in patients unwilling to repeated biopsies. However, the use of PIRADS 5 score as a sole indicator for prostatectomy may result in nonnegligible overtreatment rate.

MRI-targeted prostate biopsy: the next step forward!

Aim

For decades, the gold standard technique for diagnosing prostate cancer was the 10 to 12 core systematic transrectal or transperineal biopsy, under ultrasound guidance. Over the past years, an increased rate of false negative results and detection of clinically insignificant prostate cancer has been noted, resulting into overdiagnosis and overtreatment. The purpose of the current study was to evaluate the changes in diagnosis and management of prostate cancer brought by MRI-targeted prostate biopsy.

Methods

A critical review of literature was carried out using the Medline database through a PubMed search, 37 studies meeting the inclusion criteria: prospective studies published in the past 8 years with at least 100 patients per study, which used multiparametric magnetic resonance imaging as guidance for targeted biopsies.

Results

In-Bore MRI targeted biopsy and Fusion targeted biopsy outperform standard systematic biopsy both in terms of overall and clinically significant prostate cancer detection, and ensure a lower detection rate of insignificant prostate cancer, with fewer cores needed. In-Bore MRI targeted biopsy performs better than Fusion biopsy especially in cases of apical lesions.

Conclusion

Targeted biopsy is an emerging and developing technique which offers the needed improvements in diagnosing clinically significant prostate cancer and lowers the incidence of insignificant ones, providing a more accurate selection of the patients for active surveillance and focal therapies.

Prostate Imaging-Reporting and Data System: Comparison of the Diagnostic Performance between Version 2.0 and 2.1 for Prostatic Peripheral Zone

Objective

To compare the diagnostic performance between Prostate Imaging-Reporting and Data System version 2.0 (PI-RADSv2.0) and version 2.1 (PI-RADSv2.1) for clinically significant prostate cancer (csPCa) in the peripheral zone (PZ).

Materials and Methods

This retrospective study included 317 patients who underwent multiparametric magnetic resonance imaging and targeted biopsy for PZ lesions. Definition of csPCa was International Society of Urologic Pathology grade ≥ 2 cancer. Area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy for csPCa were analyzed by two readers. The cancer detection rate (CDR) for csPCa was investigated according to the PI-RADS categories.

Results

AUC of PI-RADSv2.1 (0.856 and 0.858 for reader 1 and 2 respectively) was higher than that of PI-RADSv2.0 (0.795 and 0.747 for reader 1 and 2 respectively) (both p < 0.001). Sensitivity, specificity, PPV, NPV, and accuracy for PI-RADSv2.0 vs. PI-RADSv2.1 were 93.2% vs. 88.3% (p = 0.023), 52.8% vs. 76.6% (p < 0.001), 48.7% vs. 64.5% (p < 0.001), 94.2% vs. 93.2% (p = 0.504), and 65.9% vs. 80.4% (p < 0.001) for reader 1, and 96.1% vs. 92.2% (p = 0.046), 34.1% vs. 72.4% (p < 0.001), 41.3% vs. 61.7% (p < 0.001), 94.8% vs. 95.1% (p = 0.869), and 54.3% vs. 78.9% (p < 0.001) for reader 2, respectively. CDRs of PI-RADS categories 1–2, 3, 4, and 5 for PI-RADSv2.0 vs. PI-RADSv2.1 were 5.9% vs. 5.9%, 5.8% vs. 12.5%, 39.8% vs. 56.2%, and 88.9% vs. 88.9% for reader 1; and 4.5% vs. 4.1%, 6.1% vs. 11.1%, 32.5% vs. 53.4%, and 85.0% vs. 86.8% for reader 2, respectively.

Conclusion

Our data demonstrated improved AUC, specificity, PPV, accuracy, and CDRs of category 3 or 4 of PI-RADSv2.1, but decreased sensitivity, compared with PI-RADSv2.0, for csPCa in PZ.

Advances in the selection of patients with prostate cancer for active surveillance

Early identification and management of prostate cancer completely changed with the discovery of prostate-specific antigen. However, improved detection has also led to overdiagnosis and consequently overtreatment of patients with low-risk disease. Strategies for the management of patients using active surveillance - the monitoring of clinically insignificant disease until intervention is warranted - were developed in response to this issue. The success of this approach is critically dependent on the accurate selection of patients who are predicted to be at the lowest risk of prostate cancer mortality. The Epstein criteria for clinically insignificant prostate cancer were first published in 1994 and have been repeatedly validated for risk-stratification and selection for active surveillance over the past few decades. Current active surveillance programmes use modified criteria with 30-50% of patients receiving treatment at 10 years. Nonetheless, tools for prostate cancer diagnosis have continued to evolve with improvements in biopsy format and targeting, advances in imaging technologies such as multiparametric MRI, and the identification of serum-, tissue- and urine-based biomarkers. These advances have the potential to further improve the identification of men with low-risk disease who can be appropriately managed using active surveillance.

Magnetic resonance imaging-guided prostate biopsy-A review of literature

Objective

Multiparametric magnetic resonance imaging (MP-MRI) helps to identify lesion of prostate with reasonable accuracy. We aim to describe the various uses of MP-MRI for prostate biopsy comparing different techniques of MP-MRI guided biopsy.

Materials and methods

A literature search was performed for "multiparametric MRI", "MRI fusion biopsy", "MRI guided biopsy", "prostate biopsy", "MRI cognitive biopsy", "MRI fusion biopsy systems", "prostate biopsy" and "cost analysis". The search operation was performed using the operator "OR" and "AND" with the above key words. All relevant systematic reviews, original articles, case series, and case reports were selected for this review.

Results

The sensitivity of MRI targeted biopsy (MRI-TB) is between 91%-93%, and the specificity is between 36%-41% in various studies. It also has a high negative predictive value (NPV) of 89%-92% and a positive predictive value (PPV) of 51%-52%. The yield of MRI fusion biopsy (MRI-FB) is similar, if not superior to MR cognitive biopsy. In-bore MRI-TB had better detection rates compared to MR cognitive biopsy, but were similar to MR fusion biopsy.

Conclusions

The use of MRI guidance in prostate biopsy is inevitable, subject to availability, cost, and experience. Any one of the three modalities (i.e. MRI cognitive, MRI fusion and MRI in-bore approach) can be used. MRI-FB has a fine balance with regards to accuracy, practicality and affordability.

Study protocol for a single-centre non-inferior randomised controlled trial on a novel three-dimensional matrix positioning-based cognitive fusion-targeted biopsy and software-based fusion-targeted biopsy for the detection rate of clinically significant prostate cancer in men without a prior biopsy

INTRODUCTION

The classical pathway for diagnosing prostate cancer is systematic 12-core biopsy under the guidance of transrectal ultrasound, which tends to underdiagnose the clinically significant tumour and overdiagnose the insignificant disease. Another pathway named targeted biopsy is using multiparametric MRI to localise the tumour precisely and then obtain the samples from the suspicious lesions. Targeted biopsy, which is mainly divided into cognitive fusion method and software-based fusion method, is getting prevalent for its good performance in detecting significant cancer. However, the preferred targeted biopsy technique in detecting clinically significant prostate cancer between cognitive fusion and software-based fusion is still beyond consensus.

METHODS AND ANALYSIS

This trial is a prospective, single-centre, randomised controlled and non-inferiority study in which all men suspicious to have clinically significant prostate cancer are included. This study aims to determine whether a novel three-dimensional matrix positioning cognitive fusion-targeted biopsy is non-inferior to software-based fusion-targeted biopsy in the detection rate of clinically significant cancer in men without a prior biopsy. The main inclusion criteria are men with elevated serum prostate-specific antigen above 4-20 ng/mL or with an abnormal digital rectal examination and have never had a biopsy before. A sample size of 602 participants allowing for a 10% loss will be recruited. All patients will undergo a multiparametric MRI examination, and those who fail to be found with a suspicious lesion, with the anticipation of half of the total number, will be dropped. The remaining participants will be randomly allocated to cognitive fusion-targeted biopsy (n=137) and software-based fusion-targeted biopsy (n=137). The primary outcome is the detection rate of clinically significant prostate cancer for cognitive fusion-targeted biopsy and software-based fusion-targeted biopsy in men without a prior biopsy. The clinically significant prostate cancer will be defined as the International Society of Urological Pathology grade group 2 or higher.

ETHICS AND DISSEMINATION

Ethical approval was obtained from the ethics committee of Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China. The results of the study will be disseminated and published in international peer-reviewed journals.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Registry (NCT04271527).

Interobserver agreement of Prostate Imaging–Reporting and Data System (PI-RADS–v2)

Background

A retrospective study was conducted on 71 consecutive patients with suspected prostate cancer (PCa) with a mean age of 56 years and underwent mp-MRI of the prostate at 3 Tesla MRI. Two readers recognized all prostatic lesions, and each lesion had a score according to Prostate Imaging–Reporting and Data System version 2 (PI-RADS-v2).

Purpose of the study

To evaluate the interobserver agreement of PI-RADS-v2 in characterization of prostatic lesions using multiparametric MRI (mp-MRI) at 3 Tesla MRI.

Results

The overall interobserver agreement of PI-RADS-v2 for both zones was excellent (k = 0.81, percent agreement = 94.9%). In the peripheral zone (PZ) lesions are the interobserver agreement for PI-RADS II (k = 0.78, percent agreement = 83.9%), PI-RADS III (k = 0.66, percent agreement = 91.3 %), PI-RADS IV (k = 0.69, percent agreement = 93.5%), and PI-RADS V (k = 0.91, percent agreement = 95.7 %). In the transitional zone (TZ) lesions are the interobserver agreement for PI-RADS I (k = 0.98, percent of agreement = 96%), PI-RADS II (k = 0.65, percent agreement = 96%), PI-RADS III (k = 0.65, percent agreement = 88%), PI-RADS IV (k = 0.83, percent agreement = 96%), and PI-RADS V (k = 0.82, percent agreement = 92%).

Conclusion

We concluded that PI-RADS-v2 is a reliable and a reproducible imaging modality for the characterization of prostatic lesions and detection of PCa.

Prospective PI-RADS v2.1 Atypical Benign Prostatic Hyperplasia Nodules With Marked Restricted Diffusion: Detection of Clinically Significant Prostate Cancer on Multiparametric MRI

BACKGROUND. On the basis of expert consensus, PI-RADS version 2.1 (v2.1) introduced the transition zone (TZ) atypical benign prostatic hyperplasia (BPH) nodule, defined as a TZ lesion with an incomplete or absent capsule (T2 score, 2). PI-RADS v2.1 also included a revised scoring pathway whereby such nodules, if exhibiting marked restricted diffusion (DWI score, 4-5), are upgraded from overall PI-RADS category 2 to category 3 (2 + 1 TZ lesions). OBJECTIVE. The purpose of this study was to compare the rates of detection of clinically significant prostate cancer (csPCa) in prospectively reported 2 + 1 TZ lesions, as defined by PI-RADS v2.1, and conventional 3 + 0 TZ lesions with targeted biopsy as the reference standard. METHODS. This retrospective study included men with no known PCa or with treatment-naïve grade group (GG) 1 PCa who underwent 3-T multiparametric MRI of the prostate with prospective reporting by means of PI-RADS v2.1. Patients with at least one PI-RADS category 3 TZ lesion who underwent targeted biopsy formed the final sample. Biopsy results were summarized descriptively for 2 + 1 and 3 + 0 lesions. Generalized estimating equations were used to compare csPCa detection rates between groups. Associations between csPCa in 2 + 1 lesions and patient age, PSA level, prostate volume, PSA density, biopsy history, lesion size, and lesion ADC were tested with Kruskal-Wallis and Fisher exact tests. RESULTS. Among 1238 eligible patients who underwent MRI reported with PI-RADS v2.1, 2 + 1 lesions were reported in 6% (n = 69) and 3 + 0 TZ lesions in 7% (n = 87) of patients. No PCa, GG1 PCa, or csPCa was found in 84% (n = 41), 10% (n = 5), and 6% (n = 3) of 49 patients with 2 + 1 lesions who underwent targeted biopsy. Nor were they found in 74% (n = 45), 15% (n = 9), and 11% (n = 7) of 61 patients with 3 + 0 lesions who underwent targeted biopsy. The csPCa detection rate was not significantly different between 2 + 1 and 3 + 0 lesions (p = .31). All cases of csPCa were GG2, except for one 3 + 0 lesion with a GG3 tumor. No clinical or imaging variable was associated with csPCa in 2 + 1 lesions. CONCLUSION. The rate of csPCa in atypical BPH nodules with marked restricted diffusion was low (6%) and not significantly different from that of conventional 3 + 0 TZ lesions (11%). CLINICAL IMPACT. The results provide prospective clinical data about the revised TZ scoring criterion and pathway in PI-RADS v2.1 for atypical BPH nodules with marked restricted diffusion.

The role of MRI/TRUS fusion biopsy in the diagnosis of clinically significant prostate cancer

Background

The aim of this work is to evaluate the detection rate of magnetic resonance imaging/transrectal ultrasound (MRI/TRUS) fusion-guided biopsy for clinically significant prostate cancers (Cs PCas), with particular interest in biopsy-naive patients and patients in active surveillance. MRI-targeted biopsy improves cancer detection rate (DR) in patients with prior negative biopsies; the current literature focuses on biopsy naive patients. We also evaluated the pathologic concordance between biopsies and surgical specimens.

Methods

MRI/TRUS fusion-guided biopsies were performed between February 2016 and February 2019. Patients with previous negative biopsies, biopsy-naive or in active surveillance (AS) were included. Cs PCas were defined through Epstein's criteria.

Results

A total of 416 men were enrolled. The overall DRs and Cs PCa DRs were 49% and 34.3%, respectively. Cs PCas were 17.2%, 44.9% and 73.4%, respectively for PI-RADS 3, 4 or 5. Among biopsy-naive patients, 34.8% were found to have a Cs PCa, while a 43.6% tumour upgrading was achieved in men with a low risk of PCa. In patients who underwent radical prostatectomy (RP), the concordance between biopsy Gleason score (GS) (bGS) and pathological GS (pGS) was 90.8%.

Conclusion

Our study highlights the role of MRI/TRUS fusion prostate biopsy in the detection of PCa in patients with previous negative biopsies focusing on Cs PCa diagnosis. The MRI/TRUS fusion biopsy is also emerging as a diagnostic tool in biopsy-naïve patients and deserves a fundamental role in AS protocols. A greater concordance between bGS and pGS can be achieved with targeted biopsies.

Predicting clinically significant prostate cancer from quantitative image features including compressed sensing radial MRI of prostate perfusion using machine learning: comparison with PI-RADS v2 assessment scores

Background

To investigate if supervised machine learning (ML) classifiers would be able to predict clinically significant cancer (sPC) from a set of quantitative image-features and to compare these results with established PI-RADS v2 assessment scores.

Methods

We retrospectively included 201, histopathologically-proven, peripheral zone (PZ) prostate cancer lesions. Gleason scores ≤3+3 were considered as clinically insignificant (inPC) and Gleason scores ≥3+4 as sPC and were encoded in a binary fashion, serving as ground-truth. MRI was performed at 3T with high spatiotemporal resolution DCE using Golden-angle RAdial SParse (GRASP) MRI. Perfusion maps (Ktrans, Kep, Ve), apparent diffusion coefficient (ADC), and absolute T2-signal intensities (SI) were determined in all lesions and served as input parameters for four supervised ML models: Gradient Boosting Machines (GBM), Neural Networks (NNet), Random Forest (RF) and Support Vector Machines (SVM). ML results and PI-RADS scores were compared with the ground-truth. Next ROC-curves and AUC values were calculated.

Results

All ML models outperformed PI-RADS v2 assessment scores in the prediction of sPC (RF, GBM, NNet and SVM vs. PI-RADS: AUC 0.899, 0.864, 0.884 and 0.874 vs. 0.595, all P<0.001).

Conclusions

Using quantitative imaging parameters as input, supervised ML models outperformed PI-RADS v2 assessment scores in the prediction of sPC. These results indicate that quantitative imagining parameters contain relevant information for the prediction of sPC from image features.

Comparing Prostate Imaging-Reporting and Data System Version 2 (PI-RADSv2) Category 1 and 2 Groups: Clinical Implication of Negative Multiparametric Magnetic Resonance Imaging

Objectives

To evaluate the clinicopathological differences between Prostate Imaging-Reporting and Data System (PI-RADS) version 2 (v2) category 1 and 2 groups. Materials and Methods. We retrospectively reviewed our two institutional clinical databases: (1) transrectal ultrasound (TRUS)/magnetic resonance imaging (MRI) fusion biopsy cohort (n = 706) and (2) radical prostatectomy (RP) cohort (n = 1403). Subsequently, we performed comparative analyses between PI-RADSv2 category 1 and 2 groups. Clinically significant prostate cancer (csPCa) was defined as the presence of Gleason score (GS) ≥ 3 + 4 in a single biopsy core, and adverse pathology (AP) was defined as high-grade (primary Gleason pattern 4 or any pattern 5) and/or non-organ-confined disease (pT3/N1). We also performed multivariate logistic regression analyses for AP.

Results

In the TRUS/MRI fusion biopsy cohort, no significant differences in detection rates of all cancer (18.2% vs. 29.0%, respectively, P = 0.730) or csPCa (9.1% vs. 9.9%, respectively, P = 0.692) were observed between PI-RADSv2 category 1 and 2 groups. There were no significant differences in pathologic outcomes including Gleason score (≥4 + 3, 21.2% vs. 29.9%, respectively, P = 0.420) or detection rate of AP (27.3% vs. 33.8%, respectively, P = 0.561) between the two groups in the RP cohort either. PI-RADSv2 category 1 or 2 had no significant association with AP, even in univariate analysis (P = 0.299).

Conclusions

PI-RADSv2 categories 1 and 2 had similar performance to predict clinicopathological outcomes. Consequently, these two categories may be unified into a single category. Negative mpMRI does not guarantee the absence of AP, as with csPCa.

New Biopsy Techniques and Imaging Features of Transrectal Ultrasound for Targeting PI-RADS 4 and 5 Lesions

PURPOSE

To introduce new biopsy techniques and imaging features of transrectal ultrasound (TRUS) for targeting Prostate Imaging Reporting and Data System (PI-RADS) 4 and 5 lesions Methods: TRUS-guided targeted and/or systematic biopsies were performed in 432 men with PI-RADS 4 and 5 lesions following magnetic resonance imaging examination. A TRUS operator who was familiar with the new techniques and imaging features performed lesion detection. Overall and significant cancer detection rates (CDRs) were compared among the men with PI-RADS 4 and 5 lesions. The CDRs in the peripheral and transition zones were compared. Additionally, we assessed whether targeted or systematic biopsies contributed to cancer detection. The standard reference was a biopsy examination.

RESULTS

The overall CDRs in the men with PI-RADS 4 and 5 lesions were 49.5% (139/281) and 74.8% (113/151) (p < 0.0001); significant CDRs were 33.1% (93/281) and 58.3% (88/151) (p < 0.0001); and CDRs in the peripheral and transition zones were 53.6% (187/349) and 78.3% (65/83) (p < 0.0001), respectively. Of the 139 men with clinically significant cancer PI-RADS 4 lesions, 107 (77.0%) were diagnosed by targeted biopsy, 5 (3.6%) by systematic biopsy, and 27 (19.4%) by both. Of the 113 men with clinically significant cancer PI-RADS 5 lesions, 97 (85.8%) were diagnosed by targeted biopsy, 3 (2.7%) by systematic biopsy, and 13 (11.5%) by both.

CONCLUSIONS

Most PI-RADS 4 and 5 lesions can be targeted with TRUS if the new techniques and imaging features are applied.

PI-RADS score is associated with biochemical control and distant metastasis in men with intermediate-risk and high-risk prostate cancer treated with radiation therapy

BACKGROUND

Novel methods of risk stratification are needed for men with prostate cancer. The Prostate Imaging Reporting and Data System (PI-RADS) uses multiparametric MRI (mpMRI) to assign a score indicating the likelihood of clinically significant prostate cancer. We evaluated pretreatment mpMRI findings, including PI-RADS score, as a marker for outcome in patients treated with primary radiation therapy (RT).

METHODS

One hundred and twenty-three men, 64% and 36% of whom had National Comprehensive Cancer Network (NCCN) intermediate-risk and high-risk disease, respectively, underwent mpMRI prior to RT. PI-RADS score and size of the largest nodule were analyzed with respect to freedom from biochemical failure (FFBF) and freedom from distant metastasis.

RESULTS

A PI-RADS score of ≤3, 4, or 5 was defined in 7%, 49%, and 44%; with a median nodule size of 0, 8, and 18 mm, respectively (P < 0.001). Median follow-up was 67 months. Men with PI-RADS ≤ 3, 4, or 5 disease had 7-year FFBF of 100%, 92%, and 65% (P = 0.002), and a 7-year freedom from distant metastasis of 100%, 100%, and 82%, respectively (P = 0.014). PI-RADS (Hazard Ratio 5.4 for PI-RADS 5 vs. 4, P = 0.006) remained associated with FFBF when controlling for NCCN risk category (P = 0.063) and receipt of androgen deprivation therapy (P = 0.535). Nodule size was also associated with FFBF (Hazard Ratio 1.08 per mm, P < 0.001) after controlling for NCCN risk category (P = 0.156) and receipt of androgen deprivation therapy (P = 0.776).

CONCLUSION

mpMRI findings, including PI-RADS score and nodule size, may improve risk stratification in men treated with primary RT.

A Novel Prediction Tool Based on Multiparametric Magnetic Resonance Imaging to Determine the Biopsy Strategy for Clinically Significant Prostate Cancer in Patients with PSA Levels Less than 50 ng/ml

PURPOSE

To develop and internally validate nomograms to help choose the optimal biopsy strategy among no biopsy, targeted biopsy (TB) only, or TB plus systematic biopsy (SB).

PATIENTS AND METHODS

This retrospective study included a total of 385 patients who underwent magnetic resonance imaging (MRI)-guided TB and/or SB at our institute after undergoing multiparametric MRI (mpMRI) between 2015 and 2018. We developed models to predict clinically significant prostate cancer (csPCa) based on suspicious lesions from a TB result and based on the whole prostate gland from the results of TB plus SB or SB only. Nomograms were generated using logistic regression and evaluated using receiver-operating characteristic (ROC) curve analysis, calibration curves and decision analysis. The results were validated using ROC curve and calibration on 177 patients from 2018 to 2019 at the same institute.

RESULTS

In the multivariate analyses, prostate-specific antigen level, prostate volume, and the Prostate Imaging Reporting and Data System score were predictors of csPCa in both nomograms. Age was also included in the model for suspicious lesions, while obesity was included in the model for the whole gland. The area under the curve (AUC) in the ROC analyses of the prediction models was 0.755 for suspicious lesions and 0.887 for the whole gland. Both models performed well in the calibration and decision analyses. In the validation cohort, the ROC curve described the AUCs of 0.723 and 0.917 for the nomogram of suspicious lesions and nomogram of the whole gland, respectively. Also, the calibration curve detected low error rates for both models.

CONCLUSION

Nomograms with excellent discriminative ability were developed and validated. These nomograms can be used to select the optimal biopsy strategy for individual patients in the future.

Multiparametric MRI and auto-fixed volume of interest-based radiomics signature for clinically significant peripheral zone prostate cancer

Objectives

To create a radiomics approach based on multiparametric magnetic resonance imaging (mpMRI) features extracted from an auto-fixed volume of interest (VOI) that quantifies the phenotype of clinically significant (CS) peripheral zone (PZ) prostate cancer (PCa).

Methods

This study included 206 patients with 262 prospectively called mpMRI prostate imaging reporting and data system 3–5 PZ lesions. Gleason scores > 6 were defined as CS PCa. Features were extracted with an auto-fixed 12-mm spherical VOI placed around a pin point in each lesion. The value of dynamic contrast-enhanced imaging(DCE), multivariate feature selection and extreme gradient boosting (XGB) vs. univariate feature selection and random forest (RF), expert-based feature pre-selection, and the addition of image filters was investigated using the training (171 lesions) and test (91 lesions) datasets.

Results

The best model with features from T2-weighted (T2-w) + diffusion-weighted imaging (DWI) + DCE had an area under the curve (AUC) of 0.870 (95% CI 0.980–0.754). Removal of DCE features decreased AUC to 0.816 (95% CI 0.920–0.710), although not significantly (p = 0.119). Multivariate and XGB outperformed univariate and RF (p = 0.028). Expert-based feature pre-selection and image filters had no significant contribution.

Conclusions

The phenotype of CS PZ PCa lesions can be quantified using a radiomics approach based on features extracted from T2-w + DWI using an auto-fixed VOI. Although DCE features improve diagnostic performance, this is not statistically significant. Multivariate feature selection and XGB should be preferred over univariate feature selection and RF. The developed model may be a valuable addition to traditional visual assessment in diagnosing CS PZ PCa.

Key Points

• T2-weighted and diffusion-weighted imaging features are essential components of a radiomics model for clinically significant prostate cancer; addition of dynamic contrast-enhanced imaging does not significantly improve diagnostic performance.

• Multivariate feature selection and extreme gradient outperform univariate feature selection and random forest.

• The developed radiomics model that extracts multiparametric MRI features with an auto-fixed volume of interest may be a valuable addition to visual assessment in diagnosing clinically significant prostate cancer.

Electronic supplementary material

The online version of this article (10.1007/s00330-019-06488-y) contains supplementary material, which is available to authorized users.

Similarities and differences between Likert and PIRADS v2.1 scores of prostate multiparametric MRI: a pictorial review of histology-validated cases

The UK National Institute for Health and Care Excellence (NICE) 2019 "Prostate cancer: diagnosis and management" guidelines have recommended that all patients suspected of prostate cancer undergo multiparametric magnetic resonance imaging (mpMRI) prior to biopsy. The Likert scoring system is advocated for mpMRI reporting based on multicentre studies that have demonstrated its effectiveness within the National Health Service (NHS). In recent years, there has been considerable drive towards standardised prostate reporting, which led to the development of "Prostate Imaging-Reporting And Data System" (PI-RADS). The PI-RADS system has been adopted by the majority of European countries and within the US. This paper reviews these systems indicating the similarities and specific differences that exist between PI-RADS and Likert assessment through a series of histologically proven clinical cases.

Necessity of differentiating small (< 10 mm) and large (≥ 10 mm) PI-RADS 4

PURPOSE

Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) provides reasonable performance in detecting significant cancers. Still, it is unclear about whether all PI-RADS 4 lesions show the same cancer detection rate (CDR) regardless of tumor size. The aim was to compare the CDRs of small (< 10 mm) and large (≥ 10 mm) PI-RADS 4.

METHODS

After magnetic resonance imaging (MRI) was performed in 684 men, a radiologist interpreted the MR images and detected 281 index lesions categorized as PI-RADS 4 in 281 men. PI-RADS 4 lesions were divided into small and large groups on size of 10 mm. Overall and significant CDRs were compared between the groups. A significant cancer was defined as one with Gleason score (GS) ≥ 7 or tumor volume ≥ 0.5 ml. Tumor volumes were roughly calculated as πr³4/3 (π = 3.14 and r = a half of tumor size) and were compared between the groups. Standard reference was a biopsy examination. Fisher's exact and Mann-Whitney tests were used for statistical analysis.

RESULTS

The overall CDRs of small and large groups were 39.0% (53/136) and 59.3% (86/145), respectively, (p = 0.0008). The median tumor volumes of cancer-proven small and large groups were 0.18 ml (0.01-0.38 ml) and 0.70 ml (0.52-1.44 ml), respectively (p < 0.0001). Using GS or tumor volume, the significant CDRs of these groups were 26.5% (36/136) and 59.3% (86/145), respectively (p < 0.0001), and using GS alone, 26.5% (36/136) and 39.3% (57/145), respectively (p = 0.0232).

CONCLUSIONS

PI-RADS 4 lesions should be sub-divided on size of 10 mm because of different significant CDRs.

Prostate Imaging Reporting and Data System 3 Category Cases at Multiparametric Magnetic Resonance for Prostate Cancer: A Systematic Review and Meta-analysis

CONTEXT

The Prostate Imaging Reporting and Data System (PI-RADS) 3 score represents a "grey zone" that need to be further investigated to solve the issue of whether to biopsy these equivocal cases or not.

OBJECTIVE

To critically analyze the current evidence on PI-RADS 3 cases. We evaluated the prevalence of PI-RADS 3 cases in the literature and detection rate of prostate cancer (PC) and clinically significant PC (csPC) at biopsy with regard to factors determining these rates.

EVIDENCE ACQUISITION

We searched in the Medline and Cochrane Library database from the literature from January 2009 to January 2019, following the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines.

EVIDENCE SYNTHESIS

A total of 28 studies were included in our analysis (total number of PI-RADS 3 cases: 1759, range 20-187). The prevalence of PI-RADS 3 cases reported in available studies was 17.3% (range 6.4-45.7%). The PC detection rate was 36% (95% confidence interval [CI] 33.8-37.4; range 10.3-55.8%), whereas that of csPC was 18.5% (95% CI 16.6-20.3; range 3.4-46.5%). Detection rates of PC and csPC were found to be similar in men who underwent a target biopsy versus those with a systematic biopsy (23.5% vs 23.9% and 11.4% vs 12.3%, respectively) and lower than the rates achieved with the combined strategy (36.9% and 19.6%, respectively). A prostate-specific antigen density (PSAD) of ≥0.15ng/ml/ml may represent an index to decide whether to submit a PI-RADS 3 case to biopsy.

CONCLUSIONS

In most investigations, PI-RADS 3 cases were not evaluated separately. A PI-RADS 3 lesion remains an equivocal lesion. Evaluation of clinical predictive factors in terms of csPC risk is a main aspect of helping clinicians in the biopsy decision process.

PATIENT SUMMARY

Management of Prostate Imaging Reporting and Data System 3 cases remains an unmet need, and the detection rate of clinically significant prostate cancer (csPC) among this population varies widely. Performing a combined target plus a systematic biopsy yields the highest detection of csPC. A prostate-specific antigen density of lower than 0.15ng/ml/ml may select patients for a follow-up strategy.

PI-RADS Steering Committee: The PI-RADS Multiparametric MRI and MRI-directed Biopsy Pathway

High-quality evidence shows that MRI in biopsy-naive men can reduce the number of men who need prostate biopsy and can reduce the number of diagnoses of clinically insignificant cancers that are unlikely to cause harm. In men with prior negative biopsy results who remain under persistent suspicion, MRI improves the detection and localization of life-threatening prostate cancer with greater clinical utility than the current standard of care, systematic transrectal US-guided biopsy. Systematic analyses show that MRI-directed biopsy increases the effectiveness of the prostate cancer diagnosis pathway. The incorporation of MRI-directed pathways into clinical care guidelines in prostate cancer detection has begun. The widespread adoption of the Prostate Imaging Reporting and Data System (PI-RADS) for multiparametric MRI data acquisition, interpretation, and reporting has promoted these changes in practice. The PI-RADS MRI-directed biopsy pathway enables the delivery of key diagnostic benefits to men suspected of having cancer based on clinical suspicion. Herein, the PI-RADS Steering Committee discusses how the MRI pathway should be incorporated into routine clinical practice and the challenges in delivering the positive health impacts needed by men suspected of having clinically significant prostate cancer.

Dynamic Contrast-Enhanced MRI-Upgraded Prostate Imaging Reporting and Data System Version 2 Category 3 Peripheral Zone Observations Stratified by a Size Threshold of 15 mm

OBJECTIVE. The purpose of this study is to evaluate dynamic contrast-enhanced (DCE) MRI (DCE-MRI)-upgraded Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) peripheral zone (PZ) observations stratified by a size threshold of 15 mm. MATERIALS AND METHODS. Two blinded radiologists independently assessed 301 patients with 326 clinically significant tumors (Gleason score [GS] ≥ 7) using multiparametric MRI performed before radical prostatectomy (RP) between 2012 and 2017 and then assigned PI-RADSv2 scores for the tumors. PI-RADSv2 category 3 PZ observations upgraded on the basis of abnormal DCE-MRI findings were tabulated, agreement was calculated, and discrepancies were resolved by consensus. The rate of detection of clinically significant cancer among upgraded observations was calculated. Size was measured at consensus review and was compared with pathologic outcomes on the basis of the PI-RADSv2 size threshold of 15 mm or more, with the use of chi-square tests. RESULTS. Reader 1 identified 5.2% (17/326) of DCE-MRI-upgraded PZ observations, and reader 2 identified 8.3% (27/326) of such observations. Interobserver agreement for PI-RADSv2 scoring was moderate (κ = 0.42) overall, but it was fair (κ = 0.23) when only DCE-MRI-upgraded observations were considered. Of the upgraded observations, which had a mean (± SD) size of 14 ± 6 mm (range, 6-29 mm), 10.4% (34/326) were agreed on after consensus review. Size smaller than 15 mm was noted for 61.8% (21/34) of observations. Among DCE-MRI-upgraded PZ observations, true- and false-positive detection rates for significant cancer were 91.2% (31/34) and 8.8% (3/34), respectively. Observations 15 mm or larger had no false-positive diagnoses and higher rates of extraprostatic extension (84.6% [11/13] vs 38.1% [8/21]; p = 0.016); however, there was no difference in GS (p = 0.354) compared with observations less than 15 mm in size. CONCLUSION. PZ observations upgraded on the basis of abnormal DCE-MRI findings have a high likelihood of being clinically significant cancer; however, agreement between readers was low. DCE-MRI-upgraded tumors of 15 mm or larger had no false-positive diagnoses and higher rates of extraprostatic extension, suggesting that they could be assigned to PI-RADSv2 assessment category 5.

Analysis of PI-RADS 4 cases: Management recommendations for negatively biopsied patients

PURPOSE

To evaluate if subgroups of patients assigned to MRI category PI-RADS 4 regarding clinical and MRI imaging aspects have distinct risks of prostate cancer (PCa) to facilitate adequate clinical management of this population, especially after negative targeted biopsy.

METHODS

This prospective, IRB approved single center cross-sectional study includes 931 consecutive patients after mp-MRI at 3 T for PCa detection. 193 patients with PI-RADS assessment category 4 received subsequent combined targeted MRI/US fusion-guided and systematic 12-core TRUS-guided biopsy as reference standard and were finally analyzed. The primary endpoint was PCa detection of PI-RADS 4 with MRI subgroup analyses. Secondary endpoints were analyses of clinical data, location of PCa, and detection of targeted biopsy cores.

RESULTS

PCa was detected in 119 of 193 patients (62%) including clinically significant PCa (csPCa; Gleason score ≥3 + 4 = 7) in 92 patients (48%). MRI subgroup analysis revealed 95% PCa (73% csPCa) in unambiguous PI-RADS 4 index lesions without additional, interfering signs of prostatitis in the peripheral zone or overlaying signs of severe stromal hyperplasia in the transition zone according to PI-RADS v2. Transition zone confined PI-RADS-4-lesions with overlaying signs of stromal hyperplasia showed PCa only in 11% (4% csPCa). Targeted biopsy cores missed the csPCa index lesion in 7% of the patients. PSA density (PSAD) was significantly higher in PCa patients.

CONCLUSIONS

Small csPCa can reliably be detected with mp-MRI by experienced readers, but can be missed by targeted MR/US fusion biopsy alone. Targeted re-biopsy of unambiguous (peripheral) PI-RADS-4-lesions is recommended; whereas transition zone confined PI-RADS-4-lesions with overlaying signs of stromal hyperplasia might be followed-up by re-MRI primarily.

Prostate Imaging Reporting and Data System Version 2 for MRI of Prostate Cancer: Can We Do Better?

OBJECTIVE. Although the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) has been widely adopted and is generally considered a success, it has clear limitations. The purpose of this article is to highlight the strengths and weaknesses of PI-RADSv2 and discuss ways that it can be improved. CONCLUSION. PI-RADSv2 has improved standardization of acquisition and interpretation of prostate MR images. Although it improves the detection of clinically significant cancers, its subjectivity and intrareader variability limit its accuracy and reproducibility, causing concerns regarding its reliability.