Defining the Incremental Utility of Prostate Multiparametric Magnetic Resonance Imaging at Standard and Specialized Read in Predicting Extracapsular Extension of Prostate Cancer

Amide proton transfer imaging has added value for predicting extraprostatic extension in prostate cancer patients

Background

Prostate cancer invades the capsule is a key factor in selecting appropriate treatment methods. Accurate preoperative prediction of extraprostatic extension (EPE) can help achieve precise selection of treatment plans.

Purpose

The aim of this study is to verify the diagnostic efficacy of tumor size, length of capsular contact (LCC), apparent diffusion coefficient (ADC), and Amide proton transfer (APT) value in predicting EPE. Additionally, the study aims to investigate the potential additional value of APT for predicting EPE.

Method

This study include 47 tumor organ confined patients (age, 64.16 ± 9.18) and 50 EPE patients (age, 61.51 ± 8.82). The difference of tumor size, LCC, ADC and APT value between groups were compared. Binary logistic regression was used to screen the EPE predictors. The receiver operator characteristic curve analysis was performed to assess the diagnostic performance of variables for predicting EPE. The diagnostic efficacy of combined models (model I: ADC+LCC+tumor size; model II: APT+LCC+tumor size; and model III: APT +ADC+LCC+tumor size) were also analyzed.

Results

APT, ADC, tumor size and the LCC were independent predictors of EPE. The area under the curve (AUC) of APT, ADC, tumor size and the LCC were 0.752, 0.665, 0.700 and 0.756, respectively. The AUC of model I, model II, and model III were 0.803, 0.845 and 0.869, respectively. The cutoff value of APT, ADC, tumor size and the LCC were 3.65%, 0.97×10-3mm2/s, 17.30mm and 10.78mm, respectively. The sensitivity/specificity of APT, ADC, tumor size and the LCC were 76%/89.4.0%, 80%/59.6%, 54%/78.9%, 72%/66%, respectively. The sensitivity/specificity of model I, Model II and Model III were 74%/72.3%, 82%/72.5% and 84%/80.9%, respectively.

Data conclusion

Amide proton transfer imaging has added value for predicting EPE. The combination model of APT balanced the sensitivity and specificity.

Prostate Cancer Local Staging with Magnetic Resonance Imaging

Accurate determination of the local stage of prostate cancer is crucial for treatment planning and prognosis. The primary objective of local staging is to distinguish between organ-confined and locally advanced disease, with the latter carrying a worse clinical prognosis. The presence of locally advanced disease features of prostate cancer, such as extra-prostatic extension, seminal vesicle invasion, and positive surgical margin, can impact the choice of treatment. Over the past decade, multiparametric MRI (mpMRI) has become the preferred imaging modality for the local staging of prostate cancer and has been shown to provide accurate information on the location and extent of disease. It has demonstrated superior performance compared to staging based on traditional clinical nomograms. Despite being a relatively new technique, mpMRI has garnered considerable attention and ongoing investigations. Therefore, in this review, we will discuss the current use of mpMRI on prostate cancer local staging.

Comparison of Four Validated Nomograms (Memorial Sloan Kettering Cancer Center, Briganti 2012, 2017, and 2019) Predicting Lymph Node Invasion in Patients with High-Risk Prostate Cancer Candidates for Radical Prostatectomy and Extended Pelvic Lymph Node Dissection: Clinical Experience and Review of the Literature

Background: The indication for extended pelvic lymph node dissection (ePLND) at the time of radical prostatectomy (RP) is based on nomograms predicting the risk of lymph node invasion (LNI). However, limited data are available on the comparison of these predictive models in high-risk prostate cancer (PC) patients. Therefore, we compared the accuracy of the most used nomograms (MSKCC, Briganti 2012, 2017, and 2019) in the setting of high-risk PC patients submitted to ePLND. Methods: 150 patients with high-risk PC disease treated from 2019 to 2022 were included. Before RP + ePLND, we assessed the MSKCC, Briganti 2012, 2017, and 2019 nomograms for each patient, and we compared the prediction of LNI with the final histopathological analysis of the ePLND using pathologic results as a reference. Results: LNI was found in 39 patients (26%), and 71.3% were cT2. The percentage of patients with estimated LNI risk above the cut-off was significantly higher in pN+ cases than in pN0 for all Briganti nomograms. The percentage of patients at risk of LNI, according to Briganti Nomogram (2012, 2017, and 2019), was significantly higher in pN+ cases than in pN0 (p < 0.04), while MSKCC prediction didn’t vary significantly between pN0 and pN+ groups (p = 0.2). All nomograms showed high sensitivity (Se > 0.90), low specificity (Sp < 0.20), and similar AUC (range: 0.526–0.573) in predicting pN+. Particularly, 74% of cases patients with MSKCC estimated risk > 7% showed pN0 compared to 71% with Briganti 2012 > 5%, 69% with Briganti 2017 > 7%, and 70% with Briganti 2019 > 7%. Conclusions: Despite the high-risk disease, in our patients treated with ePLND emerges a still high number of pN0 cases and a similar low specificity of nomograms in predicting LNI.

External Validation of Models for Prediction of Side-specific Extracapsular Extension in Prostate Cancer Patients Undergoing Radical Prostatectomy

BACKGROUND

Predicting the risk of side-specific extracapsular extension (ECE) is essential for planning nerve-sparing radical prostatectomy (RP) in patients with prostate cancer (PCa).

OBJECTIVE

To externally validate available models for prediction of ECE.

DESIGN, SETTING, AND PARTICIPANTS

Sixteen models were assessed in a cohort of 737 consecutive PCa patients diagnosed via multiparametric magnetic resonance imaging (MRI)-targeted and systematic biopsies and treated with RP between January 2016 and November 2021 at eight referral centers.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Model performance was evaluated in terms of discrimination using area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA).

RESULTS AND LIMITATIONS

Overall, ECE was identified in 308/1474 (21%) prostatic lobes. Prostatic lobes with ECE had higher side-specific clinical stage on digital rectal examination and MRI, number of positive biopsy cores, and International Society of Urological Pathology grade group in comparison to those without ECE (all p < 0.0001). Less optimistic performance was observed in comparison to previous published studies, although the models described by Pak, Patel, Martini, and Soeterik achieved the highest accuracy (AUC ranging from 0.73 to 0.77), adequate calibration for a probability threshold <40%, and the highest net benefit for a probability threshold >8% on DCA. Inclusion of MRI-targeted biopsy data and MRI information in models improved patient selection and clinical usefulness. Using model-derived cutoffs suggested by their authors, approximately 15% of positive surgical margins could have been avoided. Some available models were not included because of missing data, which constitutes a limitation of the study.

CONCLUSIONS

We report an external validation of models predicting ECE and identified the four with the best performance. These models should be applied for preoperative planning and patient counseling.

PATIENT SUMMARY

We validated several tools for predicting extension of prostate cancer outside the prostate gland. These tools can improve patient selection for surgery that spares nerves affecting recovery of sexual potency after removal of the prostate. They could potentially reduce the risk of finding cancer cells at the edge of specimens taken for pathology, a finding that suggests that not all of the cancer has been removed.

Multiparametric MRI for Staging of Prostate Cancer: A Multicentric Analysis of Predictive Factors to Improve Identification of Extracapsular Extension before Radical Prostatectomy

Simple Summary

In this multicentric study, we tested the accuracy of multiparametric magnetic resonance imaging (mpMRI) in detecting extracapsular extension (ECE) out of the prostate in order to plan surgical sparing of neurovascular bundles in radical prostatectomy. Univariate and multivariate logistic regression analyses were performed to identify other risk factors for ECE. We found that it has a good ability to exclude extracapsular extension but a poor ability to identify it correctly. Risk factors other than mpMRI that predicted ECE were as follows: prostatic specific antigen, digital rectal examination, ratio of positive cores, and biopsy grade group. We suggest that using mpMRI exclusively should not be recommended to decide on surgical approaches.

Abstract

The correct identification of extracapsular extension (ECE) of prostate cancer (PCa) on multiparametric magnetic resonance imaging (mpMRI) is crucial for surgeons in order to plan the nerve-sparing approach in radical prostatectomy. Nerve-sparing strategies allow for better outcomes in preserving erectile function and urinary continence, notwithstanding this can be penalized with worse oncologic results. The aim of this study was to assess the ability of preoperative mpMRI to predict ECE in the final prostatic specimen (PS) and identify other possible preoperative predictive factors of ECE as a secondary end-point. We investigated a database of two high-volume hospitals to identify men who underwent a prostate biopsy with a pre-biopsy mpMRI and a subsequent RP. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of mpMRI in predicting ECE were calculated. A univariate analysis was performed to find the association between image staging and pathological staging. A multivariate logistic regression was performed to investigate other preoperative predictive factors. A total of 1147 patients were selected, and 203 out of the 1147 (17.7%) patients were classified as ECE according to the mpMRI. ECE was reported by pathologists in 279 out of the 1147 PS (24.3%). The PPV was 0.58, the NPV was 0.72, the sensitivity was 0.32, and the specificity was 0.88. The multivariate analysis found that PSA (OR 1.057, C.I. 95%, 1.016–1.100, p = 0.006), digital rectal examination (OR 0.567, C.I. 95%, 0.417–0.770, p = 0.0001), ratio of positive cores (OR 9.687, C.I. 95%, 3.744–25.006, p = 0.0001), and biopsy grade in prostate biopsy (OR 1.394, C.I. 95%, 1.025–1.612, p = 0.0001) were independent factors of ECE. The mpMRI has a great ability to exclude ECE, notwithstanding that low sensitivity is still an important limitation of the technique.

Structured approach to resolving discordance between PI-RADS v2.1 score and targeted prostate biopsy results: an opportunity for quality improvement

BACKGROUND

Prostate multiparametric magnetic resonance imaging (mpMRI) can identify lesions within the prostate with characteristics identified in Prostate Imaging Reporting and Data System (PI-RADS) v2.1 associated with clinically significant prostate cancer (csPCa) or Gleason grade group (GGG) ≥ 2 at biopsy.

OBJECTIVE

To assess concordance (PI-RADS 5 lesions with csPCa) of PI-RADS v2/2.1 with targeted, fusion biopsy results and to examine causes of discordance (PI-RADS 5 lesions without csPCa) with aim to provide a structured approach to resolving discordances and develop quality improvement (QI) protocols.

METHODS

A retrospective study of 392 patients who underwent mpMRI at 3 Tesla followed by fusion biopsy. PI-RADS v2/2.1 scores were assigned to lesions identified on mpMRI and compared to biopsy results expressed as GGG. Positive predictive value (PPV) of PI-RADS v2/2.1 was calculated for all prostate cancer and csPCa. Discordant cases were re-reviewed by a radiologist with expertise in prostate mpMRI to determine reason for discordance.

RESULTS

A total of 521 lesions were identified on mpMRI. 121/521 (23.2%), 310/524 (59.5%), and 90/521 (17.3%) were PI-RADS 5, 4, and 3, respectively. PPV of PI-RADS 5, 4, and 3 for all PCa and csPCa was 0.80, 0.55, 0.24 and 0.63, 0.33, and 0.09, respectively. 45 cases of discordant biopsy results for PI-RADS 5 lesions were found with 27 deemed "true" discordances or "unresolved" discordances where imaging re-review confirmed PI-RADS appropriateness, while 18 were deemed "false" or resolved discordances due to downgrading of PI-RADS scores based on imaging re-review. Adjusting for resolved discordances on re-review, the PPV of PI-RADS 5 lesions for csPCa was deemed to be 0.74 and upon adjusting for presence of csPCa found in cases of unresolved discordance, PPV rose to 0.83 for PI-RADS 5 lesions.

CONCLUSION

Although PIRADS 5 lesions are considered high risk for csPCa, the PPV is not 100% and a diagnostic dilemma occurs when targeted biopsy returns discordant. While PI-RADS score is downgraded in some cases upon imaging re-review, a number of "false" or "unresolved" discordances were identified in which MRI re-review confirmed initial PI-RADS score and subsequent pathology confirmed presence of csPCa in these lesions.

CLINICAL IMPACT

We propose a structured approach to resolving discordant biopsy results using multi-disciplinary re-review of imaging and archived biopsy strikes as a quality improvement pathway. Further work is needed to determine the value of re-biopsy in cases of unresolved discordance and to develop robust QI systems for prostate MRI.

Reconciling Discordance Between Prostate Biopsy Histology and Magnetic Resonance Imaging Suspicion - Implementation of a Quality Improvement Protocol of Imaging Re-review and Reverse-fusion Target Analysis

There is uncertainty with how to proceed when targeted prostate biopsy of suspicious multiparametric magnetic resonance imaging (mpMRI) lesions return without clinically significant prostate cancer (csPCa). While possible, there are error sources that could contribute to such discordance including the mpMRI read, mpMRI-ultrasound fusion, biopsy technique, and histologic classification. Consequences are potentially significant; mistakenly missing csPCa can lead to delays in curative treatment. Conversely, in cases of incorrect mpMRI interpretation, the patient may be subjected to unnecessary workup/burden. At our institution, we implemented a quality improvement (QI) initiative triggered after a discordant case occurs. This multidisciplinary review process incorporates mpMRI re-review and assessment of accurate lesion-sampling, termed "reverse-fusion." Herein, we describe the protocol, present sample cases, and discuss clinical implications.

Second-opinion reads in prostate MRI: added value of subspecialty interpretation and review at multidisciplinary rounds

Purpose

This study evaluates the impact of second-opinion review of multiparametric prostate MRI for cancer detection by a multidisciplinary review board at a tertiary care center when compared with the initial community radiologist interpretation.

Methods

Cases were collected retrospectively from multidisciplinary prostate MRI rounds from 2017 to 2020 at a single tertiary care center. Patients with suspected prostate cancer or on active surveillance were referred for consideration of TRUS/MRI-fusion biopsy based on community-read prostate MRIs. All MRIs were re-read by subspecialized abdominal radiologists and a PI-RADS score assigned. Targeted fusion and 8–12 core systematic biopsy was performed in patients with PIRADS ≥ 3 lesions. Cohen kappa values were used to quantify interobserver agreement. Positive predictive value (PPV) was used to determine accuracy of PI-RADS score for detection of clinically significant prostate cancer (csPCa) (ISUP Grade Group ≥ 2).

Results

Three hundred and thirty-two lesions in 303 patients were reviewed and 252 lesions in 198 patients biopsied. The PI-RADS score was concordant in 60.5% of lesions, downgraded in 17.8%, and upgraded in 7.8%. Agreement between community and tertiary center interpretation was fair (κ = 0.354), with greater agreement for PI-RADS ≥ 4 (κ = 0.523) than PI-RADS ≥ 3 (κ = 0.456), and peripheral zone (κ = 0.419) than transition zone lesions (κ = 0.251). Prevalence of csPCa in biopsied lesions was 40.9%.

Conclusion

There is variability in community and tertiary care center interpretation of prostate MRI in cancer detection, with higher concordance rates for higher grade and peripheral zone lesions. These differences demonstrate the added value of multidisciplinary round review and highlight the need for ongoing education and feedback.

Graphical abstract

Tumor contact length of prostate cancer determined by a three-dimensional method on multiparametric magnetic resonance imaging predicts extraprostatic extension and biochemical recurrence

OBJECTIVE

To evaluate the clinical benefit of tumor contact length as a predictor of pathological extraprostatic extension and biochemical recurrence in patients undergoing prostatectomy.

METHODS

A total of 91 patients who underwent 3T multiparametric magnetic resonance imaging before prostatectomy from April 2014 to July 2019 were included. A total of 94 prostate cancer foci were analyzed retrospectively. We evaluated maximum tumor contact length, which was determined to be the maximum value in the three-dimensional directions, as a predictor of pathological extraprostatic extension and biochemical recurrence.

RESULTS

A total of 19 lesions (20.2%) had positive pathological extraprostatic extension. Areas under the curves showed maximum tumor contact length to be a significantly better parameter to predict pathological extraprostatic extension than the Prostate Imaging Reporting and Data System (P = 0.002), tumor maximal diameter (P = 0.001), prostate-specific antigen (P = 0.020), Gleason score (P < 0.001), and clinical T stage (P < 0.001). Multivariate analysis showed maximum tumor contact length (P = 0.003) to be an independent risk factor for predicting biochemical recurrence. We classified the patients using preoperative factors (prostate-specific antigen >10, Gleason score >3 + 4 and maximum tumor contact length >10 mm) into three groups: (i) high-risk group (patients having all factors); (ii) intermediate-risk group (patients having two of three factors); and (iii) low-risk group (patients having only one or none of the factors). Kaplan-Meier curves showed that the high-risk group had significantly worse biochemical recurrence than the intermediate-risk group (P = 0.042) and low-risk group (P < 0.001).

CONCLUSIONS

Our findings suggest that maximum tumor contact length is an independent predictor of pathological extraprostatic extension and biochemical recurrence. A risk stratification system using prostate-specific antigen, Gleason score and maximum tumor contact length might be useful for preoperative assessment of prostate cancer patients.

External Validation of the Extraprostatic Extension Grade on MRI and Its Incremental Value to Clinical Models for Assessing Extraprostatic Cancer

Objectives

To externally validate the extraprostatic extension (EPE) grade criteria on MRI and analyze the incremental value of EPE grade to clinical models of prostate cancer.

Methods

A consecutive 130 patients who underwent preoperative prostate MRI followed by radical prostatectomy between January 2015 to January 2020 in our institution were retrospectively enrolled. The EPE grade, Cancer of the Prostate Risk Assessment (CAPRA), and Memorial Sloan Kettering Cancer Center nomogram (MSKCCn) score for each patient were assigned. Significant clinicopathological factors in univariate and multivariate analyses were combined with EPE grade to build the Clinical + EPE grade model, and the CAPRA and MSKCCn score were also combined with EPE grade to build the CAPRA + EPE grade and MSKCCn + EPE grade model, respectively. The area under the curve (AUC), sensitivity and specificity of these models were calculated to evaluate their diagnostic performance. Calibration and decision curve analyses were used to analyze their calibration performance and clinical utility.

Results

The AUC for predicting EPE was 0.767–0.778 for EPE grade, 0.704 for CAPRA, and 0.723 for MSKCCn. After combination with EPE grade, the AUCs of these clinical models increased significantly than using clinical models along (P < 0.05), but was comparable with using EPE grade alone (P > 0.05). The calibration curves of EPE grade, clinical models and combined models showed that these models are well-calibrated for EPE. In the decision curve analysis, EPE grade showed slightly higher net benefit than MSKCCn and CAPRA.

Conclusion

The EPE grade showed good performance for evaluating EPE in our cohort and possessed well clinical utility. Further combinations with the EPE grade could improve the diagnostic performance of clinical models.

Defining prostate cancer size and treatment margin for focal therapy: does intralesional heterogeneity impact the performance of multiparametric MRI?

OBJECTIVES

To evaluate the impact of intralesional heterogeneity on the performance of multiparametric magnetic resonance imaging (mpMRI) in determining cancer extent and treatment margins for focal therapy (FT) of prostate cancer.

PATIENTS AND METHODS

We identified men who underwent primary radical prostatectomy for organ- confined prostate cancer over a 3-year period. Cancer foci on whole-mount histology were marked out, coding low-grade (LG; Gleason 3) and high-grade (HG; Gleason 4-5) components separately. Measurements of entire tumours were grouped according to intralesional proportion of HG cancer: 0%, <50% and ≥50%; the readings were corrected for specimen shrinkage and correlated with matching lesions on mpMRI. Separate measurements were also taken of HG cancer components only, and correlated against entire lesions on mpMRI. Size discrepancies were used to derive the optimal tumour size and treatment margins for FT.

RESULTS

There were 122 MRI-detected cancer lesions in 70 men. The mean linear specimen shrinkage was 8.4%. The overall correlation between histology and MRI dimensions was r = 0.79 (P < 0.001). Size correlation was superior for tumours with high burden (≥50%) compared to low burden (<50%) of HG cancer (r = 0.84 vs r = 0.63; P = 0.007). Size underestimation by mpMRI was more likely for larger tumours (51% for >12 mm vs 26% for ≤12 mm) and those containing HG cancer (44%, vs 20% for LG only). Size discrepancy analysis suggests an optimal tumour size of ≤12 mm and treatment margins of 5-6 mm for FT. For tumours ≤12 mm in diameter, applying 5- and 6-mm treatment margins would achieve 98.6% and 100% complete tumour ablation, respectively. For tumours of all sizes, using the same margins would ablate >95% of the HG cancer components.

CONCLUSIONS

Multiparametric MRI performance in estimating prostate cancer size, and consequently the treatment margin for FT, is impacted by tumour size and the intralesional heterogeneity of cancer grades.

Stratifying patients with intermediate-risk prostate cancer: Validation of a new model based on MRI parameters and targeted biopsy and comparison with NCCN and AUA subclassifications

OBJECTIVE

Intermediate-risk prostate cancer regroups heterogeneous patients with different oncologic outcomes. Aim of the study is to validate a novel intermediate-risk subclassification ("magnetic resonance imaging [MRI] subclassification") that defines favorable and unfavorable diseases based on multiparametric MRI parameters and compare it to NCCN and AUA intermediate-risk subclassifications.

METHODS

A total of 429 patients treated with radical prostatectomy for NCCN intermediate-risk prostate cancer were identified. Using MRI subclassification, a favorable disease was defined as an organ-confined disease on MRI and international society of urological pathology Grade Group 1 to 2 on targeted biopsy. Remaining was classified as unfavorable. Univariable and multivariable analysis tested MRI subclassification in predicting overall unfavorable disease (OUD: pT3-4 and/or pN1 and/or International Society of Urological Pathology Grade Group ≥ 3), the need for adjuvant therapy and early biochemical recurrence (eBCR). Performance of NCCN, AUA, and MRI models was compared in term of OUD proportion and eBCR prediction using Harrell's c-index, calibrations plots, and decision curve analysis.

RESULTS

Median (interquartile range) follow-up was 12 months (4-28). In multivariable analysis, MRI subclassification was an independent factor for OUD (odds ratio [OR]: 4.54 [2.85-7.22], P < 0.001), the need for adjuvant therapy (OR: 3.42 [1.36-8.57], P = 0.009), and eBCR (HR: 2.62 [1.18-5.83], P = 0.018). Using this model, the proportion of unfavorable disease decreased from 73.7% and 63.9% to 35.9% (P < 0.001) associated to an increasing proportion of OUD when compared to NCCN and AUA models (63.9% and 67.1%-77.9% respectively, P < 0.001). Performance of the 3 models for eBCR prediction tended to be similar with a poor accuracy ranged from 58.7% to 66.7% (P > 0.05), permanent miscalibration and a net benefit at decision curve analysis.

CONCLUSIONS

We validated an intermediate-risk subclassification based on MRI and targeted biopsy that potentially improves patient selection by reducing the number of patients considered at unfavorable risk while increasing proportion of patients harboring poor oncologic outcomes. Its performance for eBCR detection was comparable to NCCN and AUA models.

External Validation of a Multiparametric Magnetic Resonance Imaging-based Nomogram for the Prediction of Extracapsular Extension and Seminal Vesicle Invasion in Prostate Cancer Patients Undergoing Radical Prostatectomy

The nomogram reported by Gandaglia et al (The key combined value of multiparametric magnetic resonance imaging, and magnetic resonance imaging-targeted and concomitant systematic biopsies for the prediction of adverse pathological features in prostate cancer patients undergoing radical prostatectomy. Eur Urol 2020;77:733-41) predicting extracapsular extension (ECE) or seminal vesicle invasion (SVI) has been developed using multiparametric magnetic resonance imaging (MRI) parameters and MRI-targeted biopsy. We aimed to validate this nomogram externally by analyzing 566 patients harboring prostate cancer diagnosed on MRI-targeted biopsy followed by radical prostatectomy. At final pathology, 37% and 12% patients had ECE and SVI, respectively. Performance of the nomogram, in comparison with the Memorial Sloan Kettering Cancer Center (MSKCC) model and Partin tables, was evaluated using discrimination, calibration, and decision curve analysis. Regarding ECE prediction, the nomogram showed higher discrimination (71.8% vs 69.8%, p = 0.3 and 71.8% vs 61.3%, p < 0.001), and similar miscalibration and net benefit for probability threshold above 30% when compared with MSKCC model and Partin tables, respectively. Performance of the nomogram with regard to SVI was comparable in terms of discrimination (68.5% vs 70.4% vs 67.8%, p ≥ 0.6), presenting a slight overestimation on calibration plots and a net benefit for probability threshold above 7.5%. This is the first multicentric study that externally validates a nomogram predicting ECE and SVI in patients diagnosed with MRI-targeted biopsy. Its performance was less optimistic than expected, and implementation of MRI in this setting was not associated with a clear improvement in patient selection and clinical usefulness when compared with available models. We proposed an updated version of the nomogram predicting ECE using the recalibration method, which leads to an improvement in its performance and needs to be validated in another external set. PATIENT SUMMARY: We validate a prediction tool based on multiparametric magnetic resonance imaging (MRI) parameters and MRI-targeted biopsy predicting extracapsular extension and seminal vesicle invasion at radical prostatectomy. An improvement of patient selection was not clearly demonstrated when compared with available models based on clinical parameters, and implementation of MRI in this setting still needs to be clarified.

Indications for and complications of pelvic lymph node dissection in prostate cancer: accuracy of available nomograms for the prediction of lymph node invasion

OBJECTIVES

To externally validate the currently available nomograms for predicting lymph node invasion (LNI) in patients with prostate cancer (PCa) and to assess the potential risk of complications of extended pelvic lymph node dissection (ePLND) when using the recommended threshold.

METHODS

A total of 14 921 patients, who underwent radical prostatectomy with ePLND at eight European tertiary referral centres, were retrospectively identified. After exclusion of patients with incomplete biopsy or pathological data, 12 009 were included. Of these, 609 had undergone multiparametic magnetic resonance imaging-targeted biopsies. Among ePLND-related complications we included lymphocele, lymphoedema, haemorrhage, infection and sepsis. The performances of the Memorial Sloan Kettering Cancer Centre (MSKCC), Briganti 2012, Briganti 2017, Briganti 2019, Partin 2016 and Yale models were evaluated using receiver-operating characteristic curve analysis (area under the curve [AUC]), calibration plots, and decision-curve analysis.

RESULTS

Overall, 1158 patients (9.6%) had LNI, with a mean of 17.7 and 3.2 resected and positive nodes, respectively. No significant differences in AUCs were observed between the MSKCC (0.79), Briganti 2012 (0.79), Partin 2016 (0.78), Yale (0.80), Briganti 2017 (0.81) and Briganti 2019 (0.76) models. A direct comparison of older models showed that better discrimination was achieved with the MSKCC and Briganti 2012 nomograms. A tendency for underestimation was seen for all the older models, whereas the Briganti 2017 and 2019 nomograms tended to overestimate LNI risk. Decision-curve analysis showed a net benefit for all models, with a lower net benefit for the Partin 2016 and Briganti 2019 models. ePLND-related complications were experienced by 1027 patients (8.9%), and 12.6% of patients with pN1 disease.

CONCLUSIONS

The currently available nomograms have similar performances and limitations in the prediction of LNI. Miscalibration was present, however, for all nomograms showing a net benefit. In patients with only systematic biopsy, the MSKCC and Briganti 2012 nomograms were superior in the prediction of LNI.

Added Value of Biparametric MRI and TRUS-Guided Systematic Biopsies to Clinical Parameters in Predicting Adverse Pathology in Prostate Cancer

Objective

To develop novel models for predicting extracapsular extension (EPE), seminal vesicle invasion (SVI), or upgrading in prostate cancer (PCa) patients using clinical parameters, biparametric magnetic resonance imaging (bp-MRI), and transrectal ultrasonography (TRUS)-guided systematic biopsies.

Patients and Methods

We retrospectively collected data from PCa patients who underwent standard (12-core) systematic biopsy and radical prostatectomy. To develop predictive models, the following variables were included in multivariable logistic regression analyses: total prostate-specific antigen (TPSA), central transition zone volume (CTZV), prostate-specific antigen (PSAD), maximum diameter of the index lesion at bp-MRI, EPE at bp-MRI, SVI at bp-MRI, biopsy Gleason grade group, and number of positive biopsy cores. Three risk calculators were built based on the coefficients of the logit function. The area under the curve (AUC) was applied to determine the models with the highest discrimination. Decision curve analyses (DCAs) were performed to evaluate the net benefit of each risk calculator.

Results

A total of 222 patients were included in this study. Overall, 83 (37.4%), 75 (33.8%), and 107 (48.2%) patients had EPE, SVI, and upgrading at final pathology, respectively. The addition of bp-MRI data improved the discrimination of models for predicting SVI (0.807 vs 0.816) and upgrading (0.548 vs 0.625) but not EPE (0.766 vs 0.763). Similarly, models including clinical parameters, bp-MRI data, and information on systematic biopsies achieved the highest AUC in the prediction of EPE (0.842), SVI (0.913), and upgrading (0.794), and the three corresponding risk calculators yielded the highest net benefit.

Conclusion

We developed three easy-to-use risk calculators for the prediction of adverse pathological features based on patient clinical parameters, bp-MRI data, and information on systematic biopsies. This may be greatly beneficial to urologists in the decision-making process for PCa patients.

Timing and delay of radical prostatectomy do not lead to adverse oncologic outcomes: results from a large European cohort at the times of COVID-19 pandemic

PURPOSE

The current COVID-19 pandemic is transforming our urologic practice and most urologic societies recommend to defer any surgical treatment for prostate cancer (PCa) patients. It is unclear whether a delay between diagnosis and surgical management (i.e., surgical delay) may have a detrimental effect on oncologic outcomes of PCa patients. The aim of the study was to assess the impact of surgical delay on oncologic outcomes.

METHODS

Data of 926 men undergoing radical prostatectomy across Europe for intermediate and high-risk PCa according to EAU classification were identified. Multivariable analysis using binary logistic regression and Cox proportional hazard model tested association between surgical delay and upgrading on final pathology, lymph-node invasion (LNI), pathological locally advanced disease (pT3-4 and/or pN1), need for adjuvant therapy, and biochemical recurrence. Kaplan-Meier analysis was used to estimate BCR-free survival after surgery as a function of surgical delay using a 3 month cut-off.

RESULTS

Median follow-up and surgical delay were 26 months (IQR 10-40) and 3 months (IQR 2-5), respectively. We did not find any significant association between surgical delay and oncologic outcomes when adjusted to pre- and post-operative variables. The lack of such association was observed across EAU risk categories.

CONCLUSION

Delay of several months did not appear to adversely impact oncologic results for intermediate and high-risk PCa, and support an attitude of deferring surgery in line with the current recommendation of urologic societies.

Prostate MRI with PI-RADS v2.1: initial detection and active surveillance

The role of prostate MRI in clinical practice has continued to broaden over time. Multiple iterations of PI-RADS reporting have aided in improving detection and reporting of prostate cancer. In addition, recent recommendations from the PI-RADS Steering Committee promote an MRI-first approach with an MRI-directed prostate cancer diagnostic pathway. It is imperative for radiologists to be knowledgeable and familiar with prostate MRI and PI-RADS recommendations, as there is an increasing demand for prostate imaging by clinicians and patients alike.

Radiomics Based on Multiparametric Magnetic Resonance Imaging to Predict Extraprostatic Extension of Prostate Cancer

Background: To develop a radiomics model based on multiparametric MRI (mpMRI) for preoperative prediction of extraprostatic extension (EPE) in patients with prostate cancer (PCa). Methods: Ninety-five pathology-confirmed PCa patients with 115 lesions (49 positive and 66 negative) were retrospectively enrolled. A 3.0T MR scanner was used to perform T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced imaging (DCE). Radiomics features extracted from T2WI, DWI, apparent diffusion coefficient (ADC), and DCE were used to build a radiomics model. Patients' clinical and pathological variables were also obtained to build a clinical model. The radiomics model and clinical model were further integrated to build a combined nomogram. All lesions were randomly divided into the training group (82 lesions) and the validation group (33 lesions). A least absolute shrinkage and selection operator (LASSO) regression algorithm was applied to build the radiomics model. The diagnostic performance of different models was assessed by calculating the area under the curve (AUC) and compared using the Delong test. The calibration curve and decision curve analyses were used to assess the calibration and clinical usefulness of the radiomics model. Results: The AUC values for the radiomics model in the training and validation group were 0.919 and 0.865, respectively, with a good calibration performance. The decision curve analysis confirmed the clinical utility of the radiomics model. The accuracy, sensitivity, and specificity were 81.8, 71.4, and 89.5% in the validation group. In the validation group, the radiomics model outperformed the clinical model (AUC = 0.658, P = 0.020), and was comparable with the combined nomogram (AUC = 0.857, P = 0.644). Conclusion: The radiomics model based on mpMRI could different EPE and non-EPE lesions with satisfactory diagnostic performance, and this model might assist in predicting EPE before prostatectomy.

Independent external validation of nomogram to predict extracapsular extension in patients with prostate cancer

INTRODUCTION

The objective of this study was to perform an independent external validation of the Giganti-Coppola nomogram (GCN), which uses clinical and radiological parameters to predict prostate extracapsular extension (ECE) on the final pathology of patients undergoing radical prostatectomy (RP).

MATERIAL AND METHODS

Seventy-two patients diagnosed with prostate cancer (PCa), who were RP candidates from two institutions, were prospectively included. All patients underwent preoperative multi-parametric magnetic resonance imaging (mpMRI) at 1.5 T, without the use of an endorectal coil, with multiplanar images in T1WI, T2WI, DWI, and DCE. The AUC and a calibration graph were used to validate the nomogram, using the regression coefficients of the Giganti-Coppola study.

RESULTS

The original nomogram had an AUC of 0.90 (p = 0.001), with a sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 100%, 5.1%, 47.1%, 100%, and 48%, respectively. The calibration graph showed an overestimation of the nomogram for ECE.

CONCLUSION

The GCN has an adequate ability in predicting ECE; however, in our sample, it showed limited accuracy and overestimated likelihood of ECE in the final pathology of patients with PCa submitted to RP.

KEY POINTS

• Knowledge of preoperative local staging of prostate cancer is essential for surgical treatment. Extracapsular extension increases the chance of positive surgical margins. • Imaging modalities such as mpMRI alone does not have suitable accuracy in local staging. • Giganti-Coppola's nomogram achieved an adequate ability in predicting ECE.

Imaging and Management of Prostate Cancer

Prostate cancer (PCa) is the most common noncutaneous malignancy in men and the second leading cause of cancer related death in the United States. Men with clinical suspicion of PCa undergo tissue sampling and based on features including the Gleason score, Prostate Specific antigen (PSA) levels and clinical tumor (T) stage, patients are risk stratified into 6 major groups based on National Comprehensive Cancer Network (NCCN) guidelines. This forms the basis for deciding imaging and management. Active surveillance is the preferred approach for less aggressive tumors. Surgery or radiation +/- androgen deprivation therapy continue to be the primary treatment options for localized disease. Imaging plays a critical role in the diagnosis, staging and management of PCa. Multiparametric magnetic resonance imaging (mpMRI) is currently the imaging modality of choice for locoregional staging. MRI, computed tomography and bone scan remain the preferred modalities for evaluation of nodal, soft tissue, and bone metastases, respectively. Advanced positron emission tomography imaging using novel radiotracers are being developed but are not yet integrated in the diagnostic guidelines for initial staging. In this review, we will discuss the imaging and treatment algorithms based on the NCCN risk groups, describe the utility of individual modalities, review Prosate Imaging and Reporting and Data System (PIRADS) version 2.1 for the reporting of mpMRI of the prostate.

The Key Combined Value of Multiparametric Magnetic Resonance Imaging, and Magnetic Resonance Imaging-targeted and Concomitant Systematic Biopsies for the Prediction of Adverse Pathological Features in Prostate Cancer Patients Undergoing Radical Prostatectomy

BACKGROUND

The combined role of multiparametric magnetic resonance imaging (mp-MRI), and magnetic resonance imaging (MRI)-targeted and concomitant systematic biopsies in the identification of prostate cancer (PCa) patients at a higher risk of adverse pathology at radical prostatectomy (RP) is still unclear.

OBJECTIVE

To develop novel models to predict extracapsular extension (ECE), seminal vesicle invasion (SVI), or upgrading in patients diagnosed with MRI-targeted and concomitant systematic biopsies.

DESIGN, SETTING, AND PARTICIPANTS

We included 614 men with clinical stage≤T2 at digital rectal examination who underwent MRI-targeted biopsy with concomitant systematic biopsy.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSES

Logistic regression analyses predicting ECE, SVI, and upgrading (ie, a shift from biopsy International Society of Urological Pathology grade group to any higher grade at RP) based on clinical variables with or without mp-MRI features and systematic biopsy information (the percentage of cores with grade group ≥2 PCa) were developed and internally validated. The area under the curve (AUC) was used to identify the models with the highest discrimination. Decision-curve analyses (DCAs) determined the net benefit associated with their use.

RESULTS AND LIMITATIONS

Overall, 333 (54%), 88 (14%), and 169 (27%) patients had ECE, SVI, and upgrading at RP, respectively. The inclusion of mp-MRI data improved the discrimination of clinical models for ECE (67% vs 70%) and SVI (74% vs 76%). Models including mp-MRI, and MRI-targeted and concomitant systematic biopsy information achieved the highest AUC at internal validation for ECE (73%), SVI (81%), and upgrading (73%) and represented the basis for three risk calculators that yield the highest net benefit at DCA.

CONCLUSIONS

Not only mp-MRI and MRI-targeted sampling, but also concomitant systematic biopsies provide significant information to identify patients at a higher risk of adverse pathology. Although omitting systematic prostate sampling at the time of MRI-targeted biopsy might be associated with a reduced risk of detecting insignificant PCa and lower patient discomfort, it reduces the ability to accurately predict pathological features.

PATIENT SUMMARY

The combination of multiparametric magnetic resonance imaging (mp-MRI) with accurate biopsy information on MRI-targeted and systematic biopsies improves the accuracy of multivariable models based on clinical and mp-MRI data alone. Correct mp-MRI interpretation and proper extensive prostate sampling are both needed to predict adverse pathology accurately at radical prostatectomy.

Prostate focal therapy: the rule or exception?

PURPOSE OF REVIEW

Prostate focal therapy has the potential to preserve urinary and sexual function while eliminating clinically significant cancer in a subset of men with low-volume, organ-confined prostate cancer. This systematic review aims to examine current evidence to determine the efficacy and safety of focal therapy for standard clinical application.

RECENT FINDINGS

Focal therapy reduces the rate of cancer progression and conversion to radical therapy in men on active surveillance for prostate cancer. As a strategy, success in focal therapy is heavily dependent on the use of imaging and targeted biopsies. Despite advances in these areas, there remains a small but significant risk of under-detecting clinically significant cancer. Similarly, under-estimation of tumor volume may contribute to infield recurrences and close attention must be paid to the ablation margin. Although long-term oncological outcomes remain lacking, focal therapy has a low complication rate, minimal impact on urinary continence and a moderate impact on erectile function.

SUMMARY

With the appropriate expertise in imaging, targeted biopsy and targeted ablation, focal therapy is a good option in men with low-intermediate risk cancer who are willing to maximize their urinary and sexual function. However, close posttreatment surveillance and the possibility of conversion to whole gland therapy must be accepted.

Preoperative PI-RADS Version 2 scores helps improve accuracy of clinical nomograms for predicting pelvic lymph node metastasis at radical prostatectomy

BACKGROUND

Lymph node invasion (LNI) is a strong adverse prognostic factor in prostate cancer (PCa). The purpose of this study was to evaluate the role of Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) scores for estimating the risk of LN metastasis. The study also aimed to investigate the additional value of PI-RADSv2 scores when used in combination with clinical nomograms for the prediction of LNI in patients with PCa.

METHODS

We retrospectively identified 308 patients who underwent multiparametric magnetic resonance imaging (mpMRI) and RP with pelvic lymph node dissection (PLND). Clinicopathological parameters and PI-RADSv2 scores were assessed. Univariate and multivariate logistic analyses were performed. The area under the receiver operating characteristic curves (AUCs) and decision curve analysis (DCA) were generated for assessing the incremental value of PI-RADSv2 scores combined with the Briganti and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms.

RESULTS

Overall, 20 (6.5%) patients had LNI. At univariate analysis, all clinicopathological characteristics and PI-RADSv2 scores were significantly associated to LNI (p < 0.04). However, multivariate analysis revealed that only PI-RADSv2 scores and percentage of positive cores were independently significant (p ≤ 0.006). The PI-RADSv2 score was the most accurate predictor (AUC, 80.2%). The threshold of PI-RADSv2 score was 5, which provided high sensitivity (18/20, 90.0%) and negative predictive value (203/205, 99.0%). When PI-RADSv2 scores were combined with Briganti and MSKCC nomograms, the AUC value increased from 75.1 to 86.3% and from 79.2 to 87.9%, respectively (p ≤ 0.001). The DCA also demonstrated that the two nomograms plus PI-RADSv2 scores improved clinical risk prediction of LNI.

CONCLUSIONS

The patients with a PI-RADSv2 score <5 were associated with a very low risk of LNI in PCa. Preoperative PI-RADSv2 scores could help improve the accuracy of clinical nomograms for predicting pelvic LN metastasis at radical prostatectomy.

Predicting side-specific prostate cancer extracapsular extension: a simple decision rule of PSA, biopsy, and MRI parameters

Objective

To develop an easy-to-use side-specific tool for the prediction of prostate cancer extracapsular extension (ECE) using clinical, biopsy, and MRI parameters.

Materials and methods

Retrospective analysis of patients who underwent radical prostatectomy preceded by staging multiparametric MRI of the prostate was performed. Multivariate logistic regression analysis was used to choose independent predictors of ECE. Continuous variables were transformed to categorical ones by choosing threshold values using spline knots or testing thresholds used in previously described models. Internal validation of the rule was carried out as well as validation of other algorithms on our group was performed.

Results

In the analyzed period of time, 88 out of 164 patients who underwent radical prostatectomy met inclusion criteria. ECE was evidenced at radical prostatectomy in 41 patients (46.6%) and in 53 lobes (30.1%). In the multivariate analysis PSA, total percentage of cancerous tissue in cores (%PCa) and maximum tumour diameter (MTD) of Likert 3–5 lesions on MRI were independent predictors of ECE. The following rule for predicting side-specific ECE was proposed: %PCa ≥ 15% OR MTD ≥ 15 mm OR PSA ≥ 20 ng/mL. Internal validation of the algorithm revealed safe lower confidence limits for sensitivity and NPV, proving that model offers accurate risk grouping that can be safely used in decision-making.

Conclusion

The rule developed in this study makes ECE prediction fast, intuitive, and side-specific. However, until validated externally it should be used with caution.

The Role of Tumor Oxygenation Tested by Magnetic Resonance Imaging (MRI) in Prostate Cancer Grading

Background

Prostate cancer is a common malignant tumor in males. Prostate cancer grading is an important basis for evaluation of invasion. The purpose of this article was to use dynamic enhanced scan magnetic resonance imaging (MRI) to quantitatively investigate the relationship between tumor oxygenation value and prostate cancer pathological Gleason score.

Material/Methods

A total of 312 prostate cancer patients diagnosed by needle biopsy who received MRI dynamic enhanced scan were enrolled in this study. Multiparameter oxygen concentration image based on MRI was applied to test pO2 in tumors. Multiple spin resonance image relaxation time edit sequence and weak field diffusion model were used to estimate oxygen saturation level and pO2. hematoxylin and eosin staining and Gleason score were used to determine biological behavior and prognosis.

Results

According to the Gleason score system, there were 28 cases with a score of 10, 112 cases with a score of 9, 56 cases with a score of 8, and 116 cases with a score lower than 7. The enrolled patients were divided into groups: 116 cases into the middle-to-well differentiation group (Gleason score ≤7) and 196 cases into the poorly differentiation group (Gleason score at 8 to 10). Prostate cancer tumor oxygenation value was positively correlated with Gleason score (r=0.349, P<0.05) or PSA (r=0.432, P<0.05). Tumor oxygenation value in Gleason ≤7 group was obviously different from that in the group with Gleason score between 9 and 10 (P<0.05).

Conclusions

Tumor oxygenation value in prostate cancer was positively correlated with Gleason score. Tumor oxygenation value might be useful in clinics to evaluate prostate cancer grading and prognosis.

A Grading System for the Assessment of Risk of Extraprostatic Extension of Prostate Cancer at Multiparametric MRI

Purpose To evaluate MRI features associated with pathologically defined extraprostatic extension (EPE) of prostate cancer and to propose an MRI grading system for pathologic EPE. Materials and Methods In this prospective study, consecutive male study participants underwent preoperative 3.0-T MRI from June 2007 to March 2017 followed by robotic-assisted laparoscopic radical prostatectomy. An MRI-based EPE grading system was defined as follows: curvilinear contact length of 1.5 cm or capsular bulge and irregularity were grade 1, both features were grade 2, and frank capsular breach were grade 3. Multivariable logistic regression and decision curve analyses were performed to compare the MRI grade model and clinical parameters (prostate-specific antigen, Gleason score) for pathologic EPE prediction by using the area under the receiver operating characteristic curve (AUC) value. Results Among 553 study participants, the mean age was 60 years ± 8 (standard deviation); the median prostate-specific antigen value was 6.3 ng/mL. A total of 125 of 553 (22%) participants had pathologic EPE at radical prostatectomy. Detection of pathologic EPE, defined as number of pathologic EPEs divided by number of participants with individual MRI features, was as follows: curvilinear contact length, 88 of 208 (42%); capsular bulge and irregularity, 78 of 175 (45%); and EPE visible at MRI, 37 of 56 (66%). For MRI, grades 1, 2, and 3 for detection of pathologic EPE were 18 of 74 (24%), 39 of 102 (38%), and 37 of 56 (66%), respectively. Clinical features plus the MRI-based EPE grading system (prostate-specific antigen, International Society of Urological Pathology stage, MRI grade) predicted pathologic EPE better than did MRI grade alone (AUC, 0.81 vs 0.77, respectively; P < .001). Conclusion Higher MRI-based extraprostatic extension (EPE) grading categories were associated with a greater risk of pathologic EPE. Clinical features plus MRI grading had the highest diagnostic performance for prediction of pathologic EPE. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Eberhardt in this issue.

Clinical utility of MRI in the decision-making process before radical prostatectomy: Systematic review and meta-analysis

Context

Magnetic resonance imaging (MRI) is currently the most accurate imaging modality to assess local prostate cancer stage. Despite a growing body of evidence, incorporation of MRI images into decision-making process concerning surgical template of radical prostatectomy, is complex and still poorly understood.

Objective

We sought to determine the value of MRI in preoperative planning before radical prostatectomy.

Materials and methods

Systematic search through electronic PubMed, EMBASE, and Cochrane databases from 2000 up to April 2018 was performed. Only studies that used preoperative MRI in decision-making process regarding extension of resection in patients with prostate cancer, in whom radical prostatectomy was an initial form of treatment were included into analysis. Their quality was scored by Risk Of Bias In Non-Randomized Studies of Interventions system. Meta-analysis was performed to calculate the weighted summary proportion under the fixed or random effects model as appropriate and pooled effects were depicted on forest plots.

Results

The results showed that the preoperative MRI led to the modification of initial surgical template in one third of cases (35%). This occurred increasingly with the rising prostate cancer-risk category: 28%, 33%, 52% in low-, intermediate- and high-risk group, respectively. Modification of neurovascular bundle-sparing surgery based on MRI appeared to have no impact on the positive surgical margin rate. The decision based on MRI was correct on average in 77% of cases and differed across prostate cancer-risk categories: 63%, 75% and 91% in low-, intermediate- and high-risk group, accordingly.

Conclusions

In summary, MRI has a considerable impact on the decision-making process regarding the extent of resection during radical prostatectomy. Adaptation of MRI images by operating surgeons has at worst no significant impact on surgical margin status, however its ability to decrease the positive surgical margin rates remains unconfirmed.

Adding multiparametric MRI to the MSKCC and Partin nomograms for primary prostate cancer: Improving local tumor staging?

INTRODUCTION AND OBJECTIVES

As a single diagnostic modality, multiparametric MRI (mpMRI) has imperfect accuracy to detect locally advanced prostate cancer (T-stages 3-4). In this study we evaluate if combining mpMRI with preoperative nomograms (Memorial Sloan Kettering Cancer Center [MSKCC] and Partin) improves the prediction of locally advanced tumors.

MATERIALS AND METHODS

Preoperative mpMRI results of 430 robot-assisted radical prostatectomy patients were analyzed. MSKCC and Partin nomogram scores predicting extraprostatic growth were calculated. Logistic regression analysis was performed, combining the nomogram prediction scores with mpMRI results. The diagnostic value of the combined models was evaluated by creating receiver operator characteristics curves and comparing the area under the curve (AUC).

RESULTS

mpMRI was a significant predictor of locally advanced disease in addition to both the MSKCC and Partin nomogram, despite its low sensitivity (45.3%). However, overall predictive accuracy increased by only 1% when mpMRI was added to the MSKCC nomogram (AUC MSKCC 0.73 vs MSKCC + mpMRI 0.74). Predictive accuracy for the Partin Tables increased 4% (AUC Partin 0.62 vs Partin + mpMRI 0.66).

CONCLUSION

The addition of mpMRI to the preoperative MSKCC and Partin nomograms did not increase diagnostic accuracy for the prediction of locally advanced prostate cancer.

Combined Clinical Parameters and Multiparametric Magnetic Resonance Imaging for the Prediction of Extraprostatic Disease-A Risk Model for Patient-tailored Risk Stratification When Planning Radical Prostatectomy

BACKGROUND

Multiparametric magnetic resonance imaging (mpMRI) facilitates the detection of significant prostate cancer. Therefore, addition of mpMRI to clinical parameters might improve the prediction of extraprostatic extension (EPE) in radical prostatectomy (RP) specimens.

OBJECTIVE

To investigate the accuracy of a novel risk model (RM) combining clinical and mpMRI parameters to predict EPE in RP specimens.

DESIGN, SETTING, AND PARTICIPANTS

We added prebiopsy mpMRI to clinical parameters and developed an RM to predict individual side-specific EPE (EPE-RM). Clinical parameters of 264 consecutive men with mpMRI prior to MRI/transrectal ultrasound fusion biopsy and subsequent RP between 2012 and 2015 were retrospectively analysed.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Multivariate regression analyses were used to determine significant EPE predictors for RM development. The prediction performance of the novel EPE-RM was compared with clinical T stage (cT), MR-European Society of Urogenital Radiology (ESUR) classification for EPE, two established nomograms (by Steuber et al and Ohori et al) and a clinical nomogram based on the coefficients of the established nomograms, and was constructed based on the data of the present cohort, using receiver operating characteristics (ROCs). For comparison, models' likelihood ratio (LR) tests and Vuong tests were used. Discrimination and calibration of the EPE-RM were validated based on resampling methods using bootstrapping.

RESULTS AND LIMITATIONS

International society of Urogenital Pathology grade on biopsy, ESUR criteria, prostate-specific antigen, cT, prostate volume, and capsule contact length were included in the EPE-RM. Calibration of the EPE-RM was good (error 0.018). The ROC area under the curve for the EPE-RM was larger (0.87) compared with cT (0.66), Memorial Sloan Kettering Cancer Center nomogram (0.73), Steuber nomogram (0.70), novel clinical nomogram (0.79), and ESUR classification (0.81). Based on LR and Vuong tests, the EPE-RM's model fit was significantly better than that of cT, all clinical models, and ESUR classification alone (p<0.001). Limitations include monocentric design and expert reading of MRI.

CONCLUSIONS

This novel EPE-RM, incorporating clinical and MRI parameters, performed better than contemporary clinical RMs and MRI predictors, therefore providing an accurate patient-tailored preoperative risk stratification of side-specific EPE.

PATIENT SUMMARY

Extraprostatic extension of prostate cancer can be predicted accurately using a combination of magnetic resonance imaging and clinical parameters. This novel risk model outperforms magnetic resonance imaging and clinical predictors alone and can be useful when planning nerve-sparing radical prostatectomy.

RETRACTED: Recommandations françaises du Comité de Cancérologie de l’AFU – Actualisation 2018–2020 : cancer de la prostate French ccAFU guidelines – Update 2018–2020: Prostate cancer

This article has been retracted: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy). Cet article est retiré de la publication à la demande des auteurs car ils ont apporté des modifications significatives sur des points scientifiques après la publication de la première version des recommandations. Le nouvel article est disponible à cette adresse: DOI:10.1016/j.purol.2019.01.007. C’est cette nouvelle version qui doit être utilisée pour citer l’article. This article has been retracted at the request of the authors, as it is not based on the definitive version of the text because some scientific data has been corrected since the first issue was published. The replacement has been published at the DOI:10.1016/j.purol.2019.01.007. That newer version of the text should be used when citing the article.

Clinical study of prenatal ultrasonography combined with T‑box transcription factor 1 as a biomarker for the diagnosis of congenital heart disease

Congenital heart disease (CHD) seriously threatens fetal health. Therefore, prenatal examination to detect deformity is extremely important. The present study aimed to investigate the clinical application value of prenatal ultrasonography combined with molecular biology methods in the diagnosis of fetal CHD. A total of 1,000 pregnant women who had received fetal ultrasonography to examine fetal CHD were enrolled. Ultrasounds were performed for fetal heart examination and diagnosis, mainly on fetal heart position, size, structure and function, and heart valve morphology and function. These indexes were tested again 2 weeks after birth. Blood samples were collected from pregnant women with fetal CHD. Polymerase chain reaction (PCR) and western blotting were performed to detect the association between heart development and T‑box transcription factor 1 (TBX1) expression. The results revealed that 10 fetuses had CHD (1%), of which ultrasound detected 9 cases. The specificity and sensitivity of ultrasounds were 100 and 90%, respectively. Of the 9 cases were identified by prenatal ultrasound screening, including 2 cases had endocardial cushion defect, 1 case had pulmonary stenosis combined with right ventricular dysplasia, 1 case had tetralogy of Fallot combined with a cleft lip and palate, 2 cases had ventricular septal defect, 1 case had a single ventricle defect, 1 case had Ebstein and 1 case had a triatrial heart. One case of ventricular septal defect was missed prior to delivery. PCR and western blotting demonstrated that TBX1 expression may be associated with CHD. Therefore, ultrasonography combined with laboratory examinations represent efficient, economic and safe methods for fetal CHD detection. These methods may be significant to improve the rate of CHD diagnosis, and require further investigation.

New prostate cancer prognostic grade group (PGG): Can multiparametric MRI (mpMRI) accurately separate patients with low-, intermediate-, and high-grade cancer?

PURPOSE

Our objective is to determine the accuracy of multiparametric MRI (mpMRI) in predicting pathologic grade of prostate cancer (PCa) after radical prostatectomy (RP) using simple apparent diffusion coefficient metrics and, specifically, whether mpMRI can accurately separate disease into one of two risk categories (low vs. higher grade) or one of three risk categories (low, intermediate, or high grade) corresponding to the new prognostic grade group (PGG) criteria.

METHODS

This retrospective, HIPAA-compliant, IRB-approved study included 140 patients with PCa who underwent 3 T mpMRI with endorectal coil and transrectal ultrasound-guided (TRUS-G) biopsy before RP. MpMRI was used to classify lesions using a two-tier (low-grade/PGG 1 vs. high-grade/PGG 2-5) or a three-tier system (low-grade/PGG 1 vs. intermediate-grade/PGG 2 vs. high-grade/PGG 3-5). Accuracy of mpMRI was compared against RP for each system.

RESULTS

The predictive accuracy of mpMRI using the two-tier system is higher than when using three-tier system (0.77 and 0.45, respectively). There were similar rates of undergrading between mpMRI and TRUS-G biopsy compared to RP (16% & 21%; respectively); rate of overgrading was higher for mpMRI vs. TRUS-G biopsy compared to RP (42% & 17%, respectively). When mpMRI and TRUS-G biopsy are combined, rate of undergrading is 1.4% and overgrading is 11%.

CONCLUSIONS

MpMRI predictive accuracy is higher when using a two-tier vs. a three-tier system, suggesting that advanced metrics may be necessary to delineate intermediate- from high-grade disease. Rates of under- and overgrading decreased when mpMRI and TRUS-G biopsy are combined, suggesting that these techniques may be complementary in predicting tumor grade.

Seminal vesicle invasion on multi-parametric magnetic resonance imaging: Correlation with histopathology

OBJECTIVES

The pre-treatment risk of seminal vesicle (SV) invasion (SVI) from prostate cancer is currently based on nomograms which include clinical stage (cT), Gleason score (GS) and prostate-specific antigen (PSA). The aim of our study was to evaluate the staging accuracy of 3T (3T) multi-parametric (mp) Magnetic Resonance Imaging (MRI) by comparing the imaging report of SVI with the tissue histopathology. The additional value in the existing prediction models and the role of radiologists' experience were also examined.

METHODS

After obtaining institutional review board approval, we retrospectively reviewed clinico-pathological data from 527 patients who underwent a robot-assisted radical prostatectomy (RARP) between January 2012 and March 2015. Preoperative prostate imaging with an endorectal 3T-mp-MRI was performed in all patients. Sequences consisted of an axial pre-contrast T1 sequence, three orthogonally-oriented T2 sequences, axial diffusion weighted and dynamic contrast-enhanced sequences. We considered SVI in case of low-signal intensity in the SV on T2-weighted sequences or apparent mass while diffusion-weighted and DCE sequences were used to confirm findings on T2. Whole-mount section pathology was performed in all patients. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of MRI (index test) for the prediction of histological SVI (reference standard) were calculated. We developed logistic multivariable regression models including: clinical variables (PSA, cT, percentage of involved cores/total cores, primary GS 4-5) and Partin table estimates. MRI results (negative/positive exam) were then added in the models and the multivariate modeling was reassessed. In order to assess the extent of SVI and the reason for mismatch with pathology an MRI-review from an expert genitourinary radiologist was performed in a subgroup of 379 patients.

RESULTS

A total of 54 patients (10%) were found to have SVI on RARP-histopathology. In the overall cohort sensitivity, specificity, PPV and NPV for SVI detection on MRI were 75.9%, 94.7%, 62% and 97% respectively. Based on our sub-analysis, the radiologist's expertise improved the accuracy demonstrating a sensitivity, specificity, PPV and NPV of 85.4%, 95.6%, 70.0% and 98.2%, respectively. In the multivariate analysis PSA (odds ratio [OR] 1.07, p=0.008), primary GS 4 or 5 (OR 3.671, p=0.007) and Partin estimates (OR 1.07, p=0.023) were significant predictors of SVI. When MRI results were added to the analysis, a highly significant prediction of SVI was observed (OR 45.9, p<0.0001). Comparing Partin, MRI and Partin with MRI predictive models, the areas under the curve were 0.837, 0.884 and 0.929, respectively.

CONCLUSIONS

MRI had high diagnostic accuracy for SVI on histopathology. It provided added diagnostic value to clinical/Partin based SVI-prediction models alone. A key factor is radiologist's experience, though no inter-observer variability could be examined due to the availability of a single expert radiologist.

3D T2-weighted imaging to shorten multiparametric prostate MRI protocols

Objectives

To determine whether 3D acquisitions provide equivalent image quality, lesion delineation quality and PI-RADS v2 performance compared to 2D acquisitions in T2-weighted imaging of the prostate at 3 T.

Methods

This IRB-approved, prospective study included 150 consecutive patients (mean age 63.7 years, 35–84 years; mean PSA 7.2 ng/ml, 0.4–31.1 ng/ml). Two uroradiologists (R1, R2) independently rated image quality and lesion delineation quality using a five-point ordinal scale and assigned a PI-RADS score for 2D and 3D T2-weighted image data sets. Data were compared using visual grading characteristics (VGC) and receiver operating characteristics (ROC)/area under the curve (AUC) analysis.

Results

Image quality was similarly good to excellent for 2D T2w (mean score R1, 4.3 ± 0.81; R2, 4.7 ± 0.83) and 3D T2w (mean score R1, 4.3 ± 0.82; R2, 4.7 ± 0.69), p = 0.269. Lesion delineation was rated good to excellent for 2D (mean score R1, 4.16 ± 0.81; R2, 4.19 ± 0.92) and 3D T2w (R1, 4.19 ± 0.94; R2, 4.27 ± 0.94) without significant differences (p = 0.785). ROC analysis showed an equivalent performance for 2D (AUC 0.580–0.623) and 3D (AUC 0.576–0.629) T2w (p > 0.05, respectively).

Conclusions

Three-dimensional acquisitions demonstrated equivalent image and lesion delineation quality, and PI-RADS v2 performance, compared to 2D in T2-weighted imaging of the prostate. Three-dimensional T2-weighted imaging could be used to considerably shorten prostate MRI protocols in clinical practice.

Key points

• 3D shows equivalent image quality and lesion delineation compared to 2D T2w.

• 3D T2w and 2D T2w image acquisition demonstrated comparable diagnostic performance.

• Using a single 3D T2w acquisition may shorten the protocol by 40%.

• Combined with short DCE, multiparametric protocols of 10 min are feasible.

Variability in Outcomes for Patients with Intermediate-risk Prostate Cancer (Gleason Score 7, International Society of Urological Pathology Gleason Group 2-3) and Implications for Risk Stratification: A Systematic Review

CONTEXT

Optimal management for patients with intermediate-risk (IR) prostate cancer (PCa) remains controversial. Clinical metrics provide guidance on appropriate management options.

OBJECTIVE

To report estimates for clinically relevant outcomes in men with IR PCa based on clinical and pathological features.

EVIDENCE ACQUISITION

PubMed and programs from key 2015 uro-oncology congresses were searched using the terms "intermediate", "Gleason 3 + 4", "Gleason 4 + 3", "active surveillance", "treatment", "adverse pathology", AND "prostate cancer." Articles meeting prespecified criteria were retrieved. Bibliographies were scanned for additional relevant references.

EVIDENCE SYNTHESIS

Men with IR PCa have a wide range of predicted clinically relevant outcomes. Within the IR category, estimate ranges for adverse surgical pathology and 5-yr disease progression are 15-64% and 21-91%, respectively. Clinical parameters and predictive nomograms refine these estimates, but do not uniformly differentiate favorable and unfavorable IR PCa. Variations in study design and data quality in source manuscripts mandate caution in interpreting results.

CONCLUSIONS

Outcomes in IR PCa are heterogeneous. Refinements in personalized risk assessment are needed to better select IR PCa patients for surveillance.

PATIENT SUMMARY

Current and future risk stratification tools may provide additional information to identify men with intermediate-risk prostate cancer who may consider active surveillance.

[Indications and limits of ablative therapies in prostate cancer]

OBJECTIVE

To perform a state of the art about indications and limits of ablative therapies for localized prostate cancer.

METHODS

A review of the scientific literature was performed in Medline database (http://www.ncbi.nlm.nih.gov) and Embase (http://www.embase.com) using different associations of keywords. Publications obtained were selected based on methodology, language and relevance. After selection, 107 articles were analysed.

RESULTS

The objective to combine reduction of side effects and oncological control has induced recent development of several ablative therapies. Beyond this heterogeneity, some preferential indications appear: unilateral cancer of low risk (but with significant volume, excluding active surveillance) or intermediate risk (excluding majority of grade 4); treatment targeted the index lesion, by quarter or hemi-ablation, based on biopsy and mpMRI. In addition, indications must considered specific limits of each energy, such as gland volume and tumor localization.

CONCLUSION

Based on new imaging and biopsy, ablative therapies will probably increased its role in the future in management of localize prostate cancer. The multiple ongoing trials will certainly be helpful to better define their indications and limits.

New advances in focal therapy for early stage prostate cancer

INTRODUCTION

Prostate focal therapy offers men the opportunity to achieve oncological control while preserving sexual and urinary function. The prerequisites for successful focal therapy are to accurately identify, localize and completely ablate the clinically significant cancer(s) within the prostate. We aim to evaluate the evidence for current and upcoming technologies that could shape the future of prostate cancer focal therapy in the next five years. Areas covered: Current literature on advances in patient selection using imaging, biopsy and biomarkers, ablation techniques and adjuvant treatments for focal therapy are summarized. A literature search of major databases was performed using the search terms 'focal therapy', 'focal ablation', 'partial ablation', 'targeted ablation', 'image guided therapy' and 'prostate cancer'. Expert commentary: Advanced radiological tools such as multiparametric magnetic resonance imaging (mpMRI), multiparametric ultrasound (mpUS), prostate-specific-membrane-antigen positron emission tomography (PSMA-PET) represent a revolution in the ability to understand cancer function and biology. Advances in ablative technologies now provide a menu of modalities that can be rationalized based on lesion location, size and perhaps in the near future, pre-determined resistance to therapy. However, these need to be carefully studied to establish their safety and efficacy parameters. Adjuvant strategies to enhance focal ablation are under development.

[CCAFU french national guidelines 2016-2018 on prostate cancer]

OBJECTIVES

The purpose of the guidelines national committee CCAFU was to propose updated french guidelines for localized and metastatic prostate cancer (PCa).

METHODS

A Medline search was achieved between 2013 and 2016, as regards diagnosis, options of treatment and follow-up of PCa, to evaluate different references with levels of evidence.

RESULTS

Epidemiology, classification, staging systems, diagnostic evaluation are reported. Disease management options are detailed. Recommandations are reported according to the different clinical situations. Active surveillance is a major option in low risk PCa. Radical prostatectomy remains a standard of care of localized PCa. The three-dimensional conformal radiotherapy is the technical standard. A dose of > 74Gy is recommended. Moderate hypofractionation provides short-term biochemical control comparable to conventional fractionation. In case of intermediate risk PCa, radiotherapy can be combined with short-term androgen deprivation therapy (ADT). In case of high risk disease, long-term ADT remains the standard of care. ADT is the backbone therapy of metastatic disease. In men with metastases at first presentation, upfront chemotherapy combined with ADT should be considered as a new standard. In case of metastatic castration-resistant PCa (mCRPC), new hormonal treatments and chemotherapy provide a better control of tumor progression and increase survival.

CONCLUSIONS

These updated french guidelines will contribute to increase the level of urological care for the diagnosis and treatment for prostate cancer. © 2016 Elsevier Masson SAS. All rights reserved.

Multi-parametric magnetic resonance imaging as a management decision tool

The ability to image the prostate accurately and better characterize cancerous lesions makes multiparametric magnetic resonance imaging (mpMRI) an invaluable tool to improve management of localized prostate cancer (PCa). Improved risk stratification is warranted given the evidence of significant overtreatment of indolent PCa. mpMRI can more accurately rule out clinically significant PCa in men deciding between surveillance and definitive treatment to reduce overtreatment. mpMRI improves detection of clinically significant PCa, which helps minimize sampling error, a major limitation of the traditional diagnostic paradigm. Aside from helping determine candidacy for initial surveillance vs. treatment, mpMRI is a useful tool for following men on active surveillance (AS) with the potential to reduce the need for serial biopsies. When definitive treatment is warranted, mpMRI can be used to determine the local extent of disease. This provides information that is useful in the treatment decision, counseling about outcomes, and surgical planning. While mpMRI is a significant step forward in PCa management, it is necessary to understand its limitations. mpMRI and MRI-guided fusion biopsy techniques still do not detect all clinically significant tumors. The utility of current mpMRI techniques is limited by the multifocal nature of PCa with poor detection of non-index lesions, inaccurate estimation of tumor size and geometry, and the need for interpretation by specialized radiologists. The role of mpMRI will continue to expand as improvements in technology and experience help overcome these limitations.