Multiparametric MRI Improves Accuracy of Clinical Nomograms for Predicting Extracapsular Extension of Prostate Cancer

Evaluation of MSKCC Preprostatectomy nomogram in men who undergo MRI-targeted prostate biopsy prior to radical prostatectomy

INTRODUCTION

The Memorial Sloan Kettering Cancer Center (MSKCC) Preprostatectomy nomogram is a widely used resource that integrates clinical factors to predict the likelihood of adverse pathology at radical prostatectomy. Adoption of magnetic resonance imaging targeted biopsy (TB) permits optimized detection of clinically-significant cancer over systematic biopsy (SB) alone. We aim to evaluate the prognostic utility of the MSKCC Preprostatectomy nomogram with TB pathology results.

METHODS

Men who underwent SB and magnetic resonance imaging TB who later underwent radical prostatectomy at our institution were included. Patient information was entered into the MSKCC Preprostatectomy nomogram using 5 biopsy reporting schemes with TB reported by both individual core (IC) and aggregate group (AG) methods. The likelihood of extraprostatic extension, seminal vesicle invasion, and lymph node involvement as predicted by the nomogram for each biopsy reporting schema were compared to radical prostatectomy pathology.

RESULTS

We identified 63 men from January 2014 to November 2017. On receiver operating characteristic analysis, IC-TB, AG-TB, SB plus IC-TB, and SB plus AG-TB exhibited similar, if not improved, area under the curve compared to SB alone in predicting extraprostatic extension (0.671, 0.674, 0.658, and 0.6613 vs. 0.6085). This was similarly observed for seminal vesicle invasion prediction using SB plus IC-TB compared to SB alone (0.727 vs. 0.733). For lymph node involvement, superior but nonsignificant area under the curve was observed for AG-TB (0.647) compared to IC-TB (0.571) and SB alone (0.524) CONCLUSIONS: Using TB pathology results either alone or combined with SB pathology results as input to the MSKCC Preprostatectomy nomogram appears comparable for prognosticating adverse pathology on radical prostatectomy compared to SB alone, but robust validation is warranted prior to adoption into clinical practice.

Accuracy of multiparametric magnetic resonance imaging for detecting extracapsular extension in prostate cancer: a systematic review and meta-analysis

OBJECTIVE

To evaluate the diagnostic accuracy of multiparametric MRI (mpMRI) for detecting extracapsular extension (ECE) in patients with prostate cancer (PCa).

METHODS AND MATERIALS

We searched MEDLINE, PubMed, Embase and the Cochrane library up to December 2018. We included studies that used mpMRI to differentiate ECE from organ-confined PCa with a combination of T₂ weighted imaging (T₂WI), diffusion-weighted imaging, and dynamic contrast-enhanced MRI. All studies included had pathological diagnosis with radical prostatectomy. Two reviewers independently assessed the methodological quality of included studies by using Quality Assessment of Diagnostic Accuracy Studies 2 tool. We calculated pooled sensitivity, specificity, positive and negative predictive values, diagnostic odds ratios and receiver operating characteristic curve for mpMRI from 2 × 2 tables.

RESULTS

A total of 17 studies that comprised 3374 participants were included. The pooled data showed a sensitivity of 0.55 (95% confidence interval 0.43, 0.66]) and specificity of 0.87 (95% confidence interval 0.82, 0.91) for extracapsular extension detection in PCa.

CONCLUSION

First, our meta-analysis shows moderate sensitivity and high specificity for mpMRI to differentiate ECE from organ-confined prostate cancer before surgery. Second, our meta-analysis shows that mpMRI had no significant differences in performance compared with the former meta-analysis with use of T₂WI alone or with additional functional MRI.

ADVANCES IN KNOWLEDGE

It is the first meta-analysis to evaluate the accuracy of mpMRI in combination of TWI, diffusion-weightedimaging and dynamiccontrast-enhanced-MRI for extracapsular extension detection.

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.

Role of MRI in planning radical prostatectomy: what is the added value?

INTRODUCTION

The goal of radical prostatectomy is to eradicate oncological disease while achieving the best possible functional outcomes. In this regard, nerve sparing offers a greater chance of recovering potency after surgery. Accurately locating prostate cancer foci is instrumental for identifying good candidates for this approach whilst maintaining safe oncological margins. In addition to this, the length of membranous urethra is an independent predictor of time to, and extent of, continence recovery. The introduction of Mp-MRI allows visualising malignant tissue within the prostate gland, which could lead to image-directed surgery planning as with other solid-organ cancers such as kidney, pancreas, breast or testes.

METHODS

A narrative review of the available literature was performed.

RESULTS

Mp-MRI demonstrated moderate sensitivity and high specificity to detect extra-capsular extension, seminal vesicle involvement or T3 stage. Measurements of membranous urethral length have shown to be useful in predicting probability of achieving continence after surgery. Furthermore, image-guided surgery has shown to be accurate to determine surgical planes to safely preserve neurovascular bundles.

CONCLUSION

The use of Mp-MRI for pre-surgical planning introduces a new scenario where the previously homogeneous radical prostatectomy can be tailored to suit patient and tumour features. This has the potential to improve functional outcomes whilst not compromising on surgical margins. Moreover, the introduction of Mp-MRI increases the ability to predict functional outcomes after surgery and allows for a more accurate local staging. This in turn provides more information to both patients and clinicians in the decision-making process regarding treatment.

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.

Apparent diffusion coefficient in extraprostatic extension of prostate cancer: a systematic review and diagnostic meta-analysis

Objective: To evaluate the diagnostic performance of apparent diffusion coefficient (ADC) for local staging of prostate cancer. Methods: Databases of Web of Science, MEDLINE (Ovid and PubMed), Cochrane Library, EMBASE, and Google Scholar were searched up to May 31, 2018, with language restricted to English. All studies concerning multiparametric magnet resonance imaging (mpMRI) with ADC for detection of extracapsular extension (ECE, T3a) and/or extraprostatic extension (EPE, overall stage of T3) were identified by two reviewers independently, and quality of included studies was evaluated using Quality Assessment of Diagnostic Accuracy Studies-2 tool. True positive, false positive, false negative and true negative of each study were extracted to reconstruct the 2×2 tables for evaluating diagnostic accuracy. Summary estimates of sensitivity, specificity, and corresponding 95% CIs were calculated with bivariate model and hierarchical summary receiver operating characteristic model, then presented in forest plots. Multiple subgroup analyses and meta-regression were performed, and publication bias was evaluated with Deeks funnel. Results: A total of 18 studies were included, with 6 involved ECE and 12 for EPE. Pooled sensitivity was 80.5% (95% CI 76.5-83.9%) with specificity of 69.1% (95% CI 62.3-75.2%). Multiple subgroup analyses showed that if ADC and length of capsular contact are regarded as independent predictors, pooled sensitivity was 85% (95% CI 77-90%) and 81.1% (95% CI 76.0-85.3%), with specificity of 70.8% (95% CI 56.3-82.0%) and 66.6% (95% CI 57.6-74.5%), respectively. Meta-regression demonstrated that there was no substantially significant difference in types of coil, magnet field strength (1.5T versus 3.0T), and analysis method (per-lesion versus per-patient). Conclusion: By introducing ADC to MRI, we could obtain favorable sensitivity for diagnostic performance of EPE, but with a little decreased specificity.

Head-to-head comparison between multiparametric MRI, the partin tables, memorial sloan kettering cancer center nomogram, and CAPRA score in predicting extraprostatic cancer in patients undergoing radical prostatectomy

BACKGROUND

It is unclear whether clinical models including the Partin tables (PT), the Memorial Sloan Kettering Cancer Center nomogram (MSKCCn), and the cancer of the prostate risk assessment (CAPRA) can benefit from incorporating multiparametric magnetic resonance imaging (mpMRI) when staging prostate cancer (PCa).

PURPOSE

To compare the accuracy of clinical models, mpMRI, and mpMRI plus clinical models in predicting stage ≥pT3 of PCa.

STUDY TYPE

Prospective monocentric cohort study.

POPULATION

Seventy-three patients who underwent radical prostatectomy between 2016-2018.

FIELD STRENGTH/SEQUENCE

3.0T using turbo spin echo (TSE) imaging, single-shot echoplanar diffusion-weighted imaging, and T₁ -weighted high-resolution-isotropic-volume-examination (THRIVE) contrast-enhanced imaging.

ASSESSMENT

We calculated the probability of extraprostatic extension (EPE) using the PT and MSKCC, as well as the CAPRA score. Three readers with 2-8 years of experience in mpMRI independently staged PCa on imaging.

STATISTICAL TESTS

Receiver operating characteristics analysis and logistic regression analysis to investigate the per-patient accuracy of mpMRI vs. clinical models vs. mpMRI plus clinical models in predicting stage ≥pT3. The alpha level was 0.05.

RESULTS

Median probability for EPE and MSKCCn was 27.3% and 47.0%, respectively. Median CAPRA score was 3. Stage ≥pT3 occurred in 32.9% of patients. Areas under the curve (AUCs) were 0.62 for PT, 0.62 for MSKCCn, 0.64 for CAPRA, and 0.73-0.75 for mpMRI (readers 1-3) (P > 0.05 for all comparisons). Compared with mpMRI, the combination of mpMRI with PT or MSKCCn provided lower AUCs (P > 0.05 for all the readers), while the combination with CAPRA provided significantly higher (P < 0.05) AUCs in the case of readers 1 and 3. On multivariable analysis, mpMRI by reader 1 was the only independent predictor of stage ≥pT3 (odds ratio 7.40). DATA CONCLUSION: mpMRI was more accurate than clinical models and mpMRI plus clinical models in predicting stage ≥pT3, except for the combination of mpMRI and CAPRA in two out of three readers.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1604-1613.

Predictive Factors and Oncologic Outcome of Downgrade to Pathologic Gleason Score 6⁻7 after Radical Prostatectomy in Patients with Biopsy Gleason Score 8⁻10

Gleason score (GS) 8⁻10 is associated with adverse outcomes in prostate cancer (PCa). However, biopsy GS (bGS) may be upgraded or downgraded post-radical prostatectomy (RP). We aimed to investigate predictive factors and oncologic outcomes of downgrade to pathologic GS (pGS) 6⁻7 after RP in PCa patients with bGSs 8⁻10. We retrospectively reviewed clinical data of patients with bGS ≥ 8 undergoing RP. pGS downgrade was defined as a pGS ≤ 7 from bGS ≥ 8 post-RP. Univariate and multivariate cox regression analysis, logistic regression analysis, and Kaplan⁻Meier curves were used to analyze pGS downgrade and biochemical recurrence (BCR). Of 860 patients, 623 and 237 had bGS 8 and bGS ≥ 9, respectively. Post-RP, 332 patients were downgraded to pGS ≤ 7; of these, 284 and 48 had bGS 8 and bGS ≥ 9, respectively. Prostate-specific antigen (PSA) levels; clinical stage; and adverse pathologic features such as extracapsular extension, seminal vesicle invasion and positive surgical margin were significantly different between patients with pGS ≤ 7 and pGS ≥ 8. Furthermore, bGS 8 (odds ratio (OR): 0.349, p < 0.001), PSA level < 10 ng/mL (OR: 0.634, p = 0.004), and ≤cT3a (OR: 0.400, p < 0.001) were identified as significant predictors of pGS downgrade. pGS downgrade was a significant positive predictor of BCR following RP in patients with high bGS (vs. pGS 8, hazard radio (HR): 1.699, p < 0.001; vs. pGS ≥ 9, HR: 1.765, p < 0.001). In addition, the 5-year BCR-free survival rate in patients with pGS downgrade significantly differed from that in patients with bGS 8 and ≥ 9 (52.9% vs. 40.7%, p < 0.001). Among patients with bGS ≥ 8, those with bGS 8, PSA level < 10 ng/mL, and ≤cT3a may achieve pGS downgrade after RP. These patients may have fewer adverse pathologic features and show a favorable prognosis; thus we suggest that active treatment is needed in these patients. In addition, patients with high-grade bGS should be managed aggressively, even if they show pGS downgrade.

Low PI-RADS assessment category excludes extraprostatic extension (≥pT3a) of prostate cancer: a histology-validated study including 301 operated patients

OBJECTIVES

To evaluate whether low PI-RADS v2 assessment categories are effective at excluding extraprostatic extension (EPE) of prostate cancer (≥pT3a PCa).

METHODS

The local institutional ethics committee approved this retrospective analysis of 301 consecutive PCa patients. Patients were classified as low- or intermediate/high-risk based on clinical parameters and underwent pre-surgical multiparametric magnetic resonance imaging. A PI-RADS v2 assessment category and ESUR EPE score were assigned for each lesion by two readers working in consensus. Histopathologic analysis of the whole-mount radical prostatectomy specimen was the reference standard. Univariate and multivariate analyses were performed to evaluate the association of PI-RADS v2 assessment category with final histology ≥pT3a PCa.

RESULTS

For a PI-RADS v2 assessment category threshold of 3, the overall performance for ruling out (sensitivity, negative predictive value, negative likelihood ratio) ≥pT3a PCa was 99%/98%/0.04 and was similar in both the low-risk (96%/97%/0.12; N = 137) and the intermediate/high-risk groups (100%/100%/0.0; N = 164). In univariate analysis, all clinical and tumor characteristics except age were significantly associated with ≥pT3a PCa. In multivariate analysis, PI-RADS v2 assessment categories ≤ 3 had a protective effect relative to categories 4 and 5. The inclusion of ESUR EPE score improved the AUC of ≥pT3a PCa prediction (from 0.73 to 0.86, p = 0.04 in the overall cohort). The impact of PI-RADS v2 assessment category is reflected in a nomogram derived on the basis of our cohort.

CONCLUSIONS

In our cohort, low PI-RADS v2 assessment categories of 3 or less confidently ruled out the presence of ≥pT3a PCa irrespective of clinical risk group.

KEY POINTS

• Our analysis of 301 mp-MRI and RARP specimens showed that the addition of PI-RADS v2 assessment categories to clinical parameters improves the exclusion of ≥pT3a (extraprostatic) prostate cancer. • PI-RADS v2 assessment categories of 1 to 3 are useful for excluding ≥pT3a prostate cancer with a NPV of 98%; such patients can be considered as candidates for less invasive approaches. • The ability to exclude ≥pT3a prostate cancer may improve confidence in choosing nerve-sparing surgery or in avoiding pelvic nodal dissections, and similarly for patients undergoing radiotherapy, in adopting short-course adjuvant hormonal therapy or foregoing prophylactic nodal irradiation.

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.

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.

The current role of prostate multiparametric magnetic resonance imaging

Prostate multi-parametric magnetic resonance imaging (mpMRI) has shown excellent sensitivity for Gleason ≥7 cancers, especially when their volume is ≥0.5 mL. As a result, performing an mpMRI before prostate biopsy could improve the detection of clinically significant prostate cancer (csPCa) by adding targeted biopsies to systematic biopsies. Currently, there is a consensus that targeted biopsies improve the detection of csPCa in the repeat biopsy setting and at confirmatory biopsy in patients considering active surveillance. Several prospective multicentric controlled trials recently showed that targeted biopsy also improved csPCa detection in biopsy-naïve patients. The role of mpMRI and targeted biopsy during the follow-up of active surveillance remains unclear. Whether systematic biopsy could be omitted in case of negative mpMRI is also a matter of controversy. mpMRI did show excellent negative predictive values (NPV) in the literature, however, since NPV depends on the prevalence of the disease, negative mpMRI findings should be interpreted in the light of a priori risk for csPCa of the patient. Nomograms combining mpMRI findings and classical risk predictors (age, prostate-specific antigen density, digital rectal examination, etc.) will probably be developed in the future to decide whether a prostate biopsy should be obtained. mpMRI has a good specificity for detecting T3 stage cancers, but its sensitivity is low. It should therefore not be used routinely for staging purposes in low-risk patients. Nomograms combining mpMRI findings and other clinical and biochemical data will also probably be used in the future to better assess the risk of T3 stage disease.

Multi-disciplinary and shared decision-making approach in the management of organ-confined prostate cancer

Decision-making in the management of organ-confined prostate cancer is complex as it is based on multi-factorial considerations. It is complicated by a multitude of issues, which are related to the patient, treatment, disease, availability of equipment(s), expertise, and physicians. Combination of all these factors play a major role in the decision-making process and provide for an interactive decision-making preferably in the multi-disciplinary team (MDT) meeting. MDT decisions are comprehensive and are often based on all factors including patients' biological status, disease and its aggressiveness, and physician and centres' expertise. However, one important and often under rated factor is patient-related factors. There is considerable evidence that patients and physicians have different goals for treatment and physicians' understanding of their own patients' preferences is not accurate. Several patient-related key factors have been identified such as age, religious beliefs, sexual health, educational background, and cognitive impairment. We have focused on these areas and highlight some key factors that need to be taken considered whilst counselling a patient and understanding his choice of treatment, which might not always be match with the clinicians' recommendation.

Imaging as a Personalized Biomarker for Prostate Cancer Risk Stratification

Biomarkers provide objective data to guide clinicians in disease management. Prostate-specific antigen serves as a biomarker for screening of prostate cancer but has come under scrutiny for detection of clinically indolent disease. Multiple imaging techniques demonstrate promising results for diagnosing, staging, and determining definitive management of prostate cancer. One such modality, multiparametric magnetic resonance imaging (mpMRI), detects more clinically significant disease while missing lower volume and clinically insignificant disease. It also provides valuable information regarding tumor characteristics such as location and extraprostatic extension to guide surgical planning. Information from mpMRI may also help patients avoid unnecessary biopsies in the future. It can also be incorporated into targeted biopsies as well as following patients on active surveillance. Other novel techniques have also been developed to detect metastatic disease with advantages over traditional computer tomography and magnetic resonance imaging, which primarily rely on defined size criteria. These new techniques take advantage of underlying biological changes in prostate cancer tissue to identify metastatic disease. The purpose of this review is to present literature on imaging as a personalized biomarker for prostate cancer risk stratification.

Prostate Magnetic Resonance Imaging Provides Limited Incremental Value Over the Memorial Sloan Kettering Cancer Center Preradical Prostatectomy Nomogram

OBJECTIVE

To examine the incremental value of prostate magnetic resonance imaging (MRI) when used in combination with the currently available preoperative risk stratification tool, the Memorial Sloan Kettering Cancer Center (MSKCC) preradical prostatectomy nomogram.

MATERIALS AND METHODS

We reviewed our institutional database of prostate MRI performed before radical prostatectomy between December 2014 and March 2016 (n = 236). We generated a logistic regression model based on observed final pathology results and the MSKCC nomogram predictions for organ-confined disease, extracapsular extension (ECE), seminal vesicle invasion, and lymph node involvement (LNI) ("MSKCC only"). We then generated a combined regression model incorporating both the MSKCC nomogram prediction with the degree of prostate MRI suspicion ("MSKCC + MRI"). Receiver operating characteristic curves were generated, and the area under the curves (AUCs) were compared.

RESULTS

When independently examining the MSKCC nomogram predicted risk and the degree of prostate MRI suspicion, MRI was a predictor for ECE (odds ratio 2.8, P <.01) and LNI (odds ratio 5.6, P = .01). When examining the "MSKCC + MRI" and "MSKCC only" models, the incremental benefit in risk discrimination from the combined model ("MSKCC + MRI") was not significant for organ-confined disease, ECE, seminal vesicle invasion, or LNI (ΔAUC +0.03, P = .10; ΔAUC +0.03, P = .08; ΔAUC 0.63, P = .63; ΔAUC +0.04, P = .42; respectively).

CONCLUSION

A combined model with prostate MRI and the MSKCC nomogram provides no additional risk discrimination over the MSKCC nomogram-based model alone. Evaluation of prostate MRI as a predictive tool should be performed in combination with, not independent of, these clinical risk stratification models.

The efficacy and utilisation of preoperative multiparametric magnetic resonance imaging in robot-assisted radical prostatectomy: does it change the surgical dissection plan?

Objective

We investigated the effect of the use of multiparametric prostate magnetic resonance imaging (mp-MRI) on the dissection plan of the neurovascular bundle and the oncological results of our patients who underwent robot-assisted radical prostatectomy.

Material and methods

We prospectively evaluated 60 consecutive patients, including 30 patients who had (Group 1), and 30 patients who had not (Group 2) mp-MRI before robot-assisted radical prostatectomy. Based on the findings of mp-MRI, the dissection plan was changed as intrafascial, interfascial, and extrafascial in the mp-MRI group. Two groups were compared in terms of age, prostate-specific antigen (PSA), Gleason sum scores and surgical margin positivity.

Results

There was no statistically significant difference between the two groups in terms of age, PSA, biopsy Gleason score, final pathological Gleason score and surgical margin positivity. mp-MRI changed the initial surgical plan in 18 of 30 patients (60%) in Group 1. In seventeen of these patients (56%) surgical plan was changed from non-nerve sparing to interfascial nerve sparing plan. In one patient dissection plan was changed to non-nerve sparing technique which had extraprostatic extension on final pathology. Surgical margin positivity was similar in Groups 1, and 2 (16% and 13%, respectively) although, Group 1 had higher number of high- risk patients. mp-MRI confirmed the primary tumour localisation in the final pathology in 27 of of 30 patients (90%).

Conclusion

Preoperative mp-MRI effected the decision to perform a nerve-sparing technique in 56% of the patients in our study; moreover, changing the dissection plan from non-nerve-sparing technique to a nerve sparing technique did not increase the rate of surgical margin positivity.

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.

A novel tool for predicting extracapsular extension during graded partial nerve sparing in radical prostatectomy

OBJECTIVES

To create a statistical tool for the estimation of extracapsular extension (ECE) level of prostate cancer and determine the nerve-sparing (NS) approach that can be safely performed during radical prostatectomy (RP).

PATIENTS AND METHODS

A total of 11 794 lobes, from 6 360 patients who underwent robot-assisted RP between 2008 and 2016 were evaluated. Clinicopathological features were included in a statistical algorithm for the prediction of the maximum ECE width. Five multivariable logistic models were estimated for: presence of ECE and ECE width of >1, >2, >3, and >4 mm. A five-zone decision rule based on a lower and upper threshold is proposed. Using a graphical interface, surgeons can view patient's pre-treatment characteristics and a curve showing the estimated probabilities for ECE amount together with the areas identified by the decision rule.

RESULTS

Of the 6 360 patients, 1 803 (28.4%) were affected by non-organ-confined disease. ECE was present in 1 351 lobes (11.4%) and extended beyond the capsule for >1, >2, >3, and >4 mm in 498 (4.2%), 261 (2.2%), 148 (1.3%), 99 (0.8%) cases, respectively. ECE width was up to 15 mm (interquartile range 1.00-2.00). The five logistic models showed good predictive performance, the area under the receiver operating characteristic curve was: 0.81 for ECE, and 0.84, 0.85, 0.88, and 0.90 for ECE width of >1, >2, >3, and >4 mm, respectively.

CONCLUSION

This novel tool predicts with good accuracy the presence and amount of ECE. Furthermore, the graphical interface available at www.prece.it can support surgeons in patient counselling and preoperative planning.

Development and comparison of a Chinese nomogram adding multi-parametric MRI information for predicting extracapsular extension of prostate cancer

PURPOSE

To improve the performation of a nomogram for predicting side-specific extracapsular extension (SS-ECE).

RESULTS

One hundred and ninety-six patients (55.5%) had ECE on final pathology. Bilateral and unilateral ECE rate was 13.9% (49/353) and 41.6% (147/353), respectively. The mean age was 65.9 years and the mean serum prostate specific antigen (PSA) was 15.0 ng/ml. Based on multivariate logistic regression analysis, clinical stage (cStage), PSA, Gleason sum, percentage of positive cores, and ECE risk score were significant predictors of ECE. The current nomogram had higher predictive accuracy (0.851) and superior calibration. According to the decision curve analysis (DCA) results, the updated nomogram demonstrated a high net benefit across a wide range of threshold probabilities.

MATERIALS AND METHODS

We studied 353 patients with cStage T1c-T3 prostate cancer underwent radical prostatectomy. The candidate predictors associated with ECE were cStage, PSA, Gleason sum, percentage of positive cores, maximum cancer percentage and ECE risk score from multi-parametric magnetic resonance imaging (MP-MRI). The receiver operating characteristic (ROC) analysis was performed and an updated nomogram was constructed. The DCA was performed to test the predictive ability of the nomogram. In addition, the validation and calibration of the Memorial Sloan-Kettering cancer center (MSKCC) nomograms were performed in the current subjects.

CONCLUSIONS

Predictors, including cStage, PSA, Gleason sum, percentage of positive cores, maximum cancer percentage, and ECE risk score, were combined to construct a SS-ECE prediction nomogram. And the current nomogram might help urologists in decision-making process of preserving or resecting neurovascular bundles preoperatively.

Using Imaging to Predict Treatment Response in Genitourinary Malignancies

CONTEXT

Over the previous2 decades, there have been numerous advancements in the diagnostic evaluation, therapeutic management, and postoperative assessment of genitourinary malignancies.

OBJECTIVE

To present a review of current and novel imaging modalities and their utility in the assessment of therapeutic response in the systemic management of renal, testicular, and prostate cancers.

EVIDENCE ACQUISITION

A PubMed/Medline search of the current published literature inclusive of prospective and retrospective original research, systematic reviews, and meta-analyses was conducted evaluating imaging modalities for renal cell carcinoma, prostate cancer, and testicular cancer. All relevant literature was individually reviewed and summarized to provide a concise description of the currently available imaging modalities and their efficacy in assessing treatment response of the genitourinary malignancies targeted in this review.

EVIDENCE SYNTHESIS

Conventional imaging techniques play a pivotal role in predicting the treatment response of genitourinary malignancies and have, therefore, been incorporated into clinical guidelines. Advancements in imaging technology have led to increased utilization for prognostication of a genitourinary cancer's response to therapy.

CONCLUSIONS

A good understanding of current recommended imaging techniques to evaluate treatment response in genitourinary malignancies is of paramount importance for today's clinician, who faces increasing treatment modalities.

PATIENT SUMMARY

In this review, we summarize available imaging modalities in the evaluation of treatment response in kidney, prostate, or testicular tumors. We believe that a good understanding of current imaging modalities is of paramount importance for healthcare providers treating these cancers.

Magnetic resonance imaging for prostate cancer before radical and salvage radiotherapy: What radiation oncologists need to know

External beam radiotherapy (EBRT) is one of the principal curative treatments for patients with prostate cancer (PCa). Risk group classification is based on prostate-specific antigen (PSA) level, Gleason score, and T-stage. After risk group determination, the treatment volume and dose are defined and androgen deprivation therapy is prescribed, if appropriate. Traditionally, imaging has played only a minor role in T-staging due to the low diagnostic accuracy of conventional imaging strategies such as transrectal ultrasound, computed tomography, and morphologic magnetic resonance imaging (MRI). As a result, a notable percentage of tumours are understaged, leading to inappropriate and imprecise EBRT. The development of multiparametric MRI (mpMRI), an imaging technique that combines morphologic studies with functional diffusion-weighted sequences and dynamic contrast-enhanced imaging, has revolutionized the diagnosis and management of PCa. As a result, mpMRI is now used in staging PCa prior to EBRT, with possible implications for both risk group classification and treatment decision-making for EBRT. mpMRI is also being used in salvage radiotherapy (SRT), the treatment of choice for patients who develop biochemical recurrence after radical prostatectomy. In the clinical context of biochemical relapse, it is essential to accurately determine the site of recurrence - pelvic (local, nodal, or bone) or distant - in order to select the optimal therapeutic management approach. Studies have demonstrated the value of mpMRI in detecting local recurrences - even in patients with low PSA levels (0.3-0.5 ng/mL) - and in diagnosing bone and nodal metastasis. The main objective of this review is to update the role of mpMRI prior to radical EBRT or SRT. We also consider future directions for the use and development of MRI in the field of radiation oncology.

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.

DCE-MRI, DW-MRI, and MRS in Cancer: Challenges and Advantages of Implementing Qualitative and Quantitative Multi-parametric Imaging in the Clinic

Multi-parametric magnetic resonance imaging (mpMRI) offers a unique insight into tumor biology by combining functional MRI techniques that inform on cellularity (diffusion-weighted MRI), vascular properties (dynamic contrast-enhanced MRI), and metabolites (magnetic resonance spectroscopy) and has scope to provide valuable information for prognostication and response assessment. Challenges in the application of mpMRI in the clinic include the technical considerations in acquiring good quality functional MRI data, development of robust techniques for analysis, and clinical interpretation of the results. This article summarizes the technical challenges in acquisition and analysis of multi-parametric MRI data before reviewing the key applications of multi-parametric MRI in clinical research and practice.

Developing a new PI-RADS v2-based nomogram for forecasting high-grade prostate cancer

AIM

To establish a predictive nomogram for high-grade prostate cancer (HGPCa) in biopsy-naive patients based on the Prostate Imaging-Reporting and Data System version 2 (PI-RADS v2), magnetic resonance imaging (MRI)-based prostate volume (PV), MRI-based PV-adjusted prostate-specific antigen density (PSAD), and other classical parameters.

MATERIAL AND METHODS

Between August 2014 and August 2015, 158 men who were eligible for analysis were included as the training cohort. A prediction model for HGPCa was built using backward logistic regression and was presented on a nomogram. The prediction model was evaluated by a validation cohort between September 2015 and March 2016 (n=89). Histology of all lesions was obtained with MRI-directed transrectal ultrasound (TRUS)-guided targeted and sectoral biopsy.

RESULTS

The multivariate analysis revealed that patient age, PI-RADS v2 score, and adjusted PSAD were independent predictors for HGPCa. The most discriminative cut-off value for the logistic regression model was 0.33; the sensitivity, specificity, positive predictive value, and negative predictive value were 83.3%, 87.4%, 88.4%, and 81.2%, respectively. The diagnostic performance measures retained similar values in the validation cohort (AUC=0.83).

CONCLUSION

The nomogram for forecasting HGPCa is effective and potentially reducing harm from unnecessary prostate biopsy and over-diagnosis.

Integration of MRI to clinical nomogram for predicting pathological stage before radical prostatectomy

BACKGROUND

Debate persists regarding whether MRI should be used routinely for preoperative evaluation of prostate cancer.

OBJECTIVE

The aim is to assess the role of prostatic magnetic resonance imaging (MRI) and other preoperative data in extra-prostatic extension (EPE) evaluation.

PATIENTS AND METHODS

From 2000 to 2013, 1743 patients operated for radical prostatectomy had a preoperative MRI. Age, clinical stage with digital rectal exam (DRE), PSA, prostate weight, biopsy, MRI and pathological findings of the surgical specimen were noticed. A multiparametric score of the variables independently associated with EPE was built with or without MRI on a random sample test population and internally validated.

RESULTS

With mean age of 62.9 years and mean PSA of 9.6 ng/ml, the population was distributed as follows: 1424 DRE T1, 254 T2, 32 T3; on biopsy 990 Gleason score = 6 and 717 ≥ 7; on MRI 1322 iT2, 290 iT3A and 131 iT3B; on prostatectomy 15 pT0, 998 pT2, 548 pT3A, 181 pT3B and 1 pT4A. In multivariate analysis, DRE, PSA, Gleason score, prostate weight and MRI were independently associated with EPE and integrated in a score with an area under curve (AUC) of 0.74 [95% CI 0.71-0.77] (0.72 without MRI, p < 0.01) a positive predictive value of 61% and a negative predictive value of 74%, internally validated. The Hosmer-Lemeshow goodness-of-fit test showed good accuracy (p = 0.77).

CONCLUSIONS

Integration of MRI with clinical data for predicting pathological stage before radical prostatectomy permits to exclude accurately EPE in 74% of cases.

Role of multi-parametric MRI of the prostate for screening and staging: Experience with over 1500 cases

Objective

Contemporary prostate cancer (PCa) screening modalities such as prostate specific antigen (PSA) and digital rectal examination (DRE) are limited in their ability to predict the detection of clinically significant disease. Multi-parametric magnetic resonance imaging (mpMRI) of the prostate has been explored as a staging modality for PCa. Less is known regarding its utility as a primary screening modality. We examined our experience with mpMRI as both a screening and staging instrument.

Methods

mpMRI studies performed between 2012 and 2014 in patients without PCa were cross-referenced with transrectal ultrasonography (TRUS) biopsy findings. Statistical analyses were performed to determine association of mpMRI findings with overall cancer diagnoses and clinically significant (Gleason score ≥7) disease. Subgroup analyses were then performed on patients with a history of prior negative biopsy and those without a history of TRUS biopsy. mpMRI studies were also cross-referenced with RP specimens. Statistical analyses determined predictive ability of extracapsular extension (ECE), seminal vesicle involvement (SVI), and pathologic evidence of clinically significant disease (Gleason score ≥7).

Results

Four hundred biopsy naïve or prior negative biopsy patients had positive mpMRI studies. Overall sensitivity, specificity, positive and negative predictive values were 94%, 37%, 58%, and 87%, respectively and 95%, 31%, 42%, and 93%, respectively for overall cancer detection and Gleason score ≥7 disease. In patients with no prior biopsy history, mpMRI sensitivity, specificity, positive and negative predictive values were 94%, 36%, 65%, and 82%, for all cancers, and 95%, 30%, 50%, and 89% for Gleason score≥7 lesions, respectively. In those with prior negative biopsy sensitivity, specificity, positive and negative predictive values were 94%, 37%, 52%, and 90% for all cancers, and 96%, 32%, 36%, and 96% for Gleason score ≥7 lesions, respectively. Seventy-four patients underwent radical prostatectomy (RP) after mpMRI. Lesion size on mpMRI correlated with the presence of Gleason score ≥7 cancers (p = 0.005). mpMRI sensitivity, specificity, positive and negative predictive values were 84%, 39%, 81%, and 44% respectively, for Gleason ≥7 cancer. For ECE and SVI, sensitivity and specificity were 58% and 98% and 44% and 97%, respectively.

Conclusion

mpMRI is an accurate predictor of TRUS biopsy and RP outcomes. mpMRI has significant potential to change PCa management, particularly in the screening population, in whom a significant proportion may avoid TRUS biopsy. Further studies are necessary to determine how mpMRI should be incorporated into the current PCa screening and staging paradigms.

Multi-parametric MRI of the prostate: Factors predicting extracapsular extension at the time of radical prostatectomy

Objective

Extracapsular extension (ECE) of prostate cancer is a poor prognostic factor associated with progression, recurrence after treatment, and increased prostate cancer-related mortality. Accurate staging prior to radical prostatectomy is crucial in avoidance of positive margins and when planning nerve-sparing procedures. Multi-parametric magnetic resonance imaging (mpMRI) of the prostate has shown promise in this regard, but is hampered by poor sensitivity. We sought to identify additional clinical variables associated with pathologic ECE and determine our institutional accuracy in the detection of ECE amongst patients who went on to radical prostatectomy.

Methods

mpMRI studies performed between the years 2012 and 2014 were cross-referenced with radical prostatectomy specimens. Predictive properties of ECE as well as additional clinical and biochemical variables to identify pathology-proven prostate cancer ECE were analyzed.

Results

The prevalence of ECE was 32.4%, and the overall accuracy of mpMRI for ECE was 84.1%. Overall mpMRI sensitivity, specificity, positive predictive value, and negative predictive value for detection of ECE were 58.3%, 97.8%, 93.3%, and 81.5%, respectively. Specific mpMRI characteristics predictive of pathologic ECE included primary lesion size ((20.73 ± 9.09) mm, mean ± SD, p < 0.001), T2 PIRADS score (p = 0.009), overall primary lesion score (p < 0.001), overall study suspicion score (p = 0.003), and MRI evidence of seminal vesicle invasion (SVI) (p = 0.001).

Conclusion

While mpMRI is an accurate preoperative assessment tool for the detection of ECE, its overall sensitivity is poor, likely related to the low detection rate of standard protocol MRI for microscopic extraprostatic disease. The additional mpMRI findings described may also be considered in surgical margin planning prior to radical prostatectomy.

Can multiparametric MRI replace Roach equations in staging prostate cancer before external beam radiation therapy?

PURPOSE

To investigate the agreement between Roach equations (RE) and multiparametric magnetic resonance imaging (mpMRI) in assessing the T-stage of prostate cancer (PCa).

MATERIALS AND METHODS

Seventy-three patients with biopsy-proven PCa and previous RE assessment prospectively underwent mpMRI on a 3.0T magnet before external beam radiation therapy (EBRT). Using Cohen's kappa statistic, we assessed the agreement between RE and mpMRI in defining the T-stage (≥T3 vs.T≤2) and risk category according to the National comprehensive cancer network criteria (≤intermediate vs. ≥high). We also calculated sensitivity and specificity for ≥T3 stage in an additional group of thirty-seven patients with post-prostatectomy histological examination (mpMRI validation group).

RESULTS

The agreement between RE and mpMRI in assessing the T stage and risk category was moderate (k=0.53 and 0.56, respectively). mpMRI changed the T stage and risk category in 21.9% (95%C.I. 13.4-33-4) and 20.5% (95%C.I. 12.3-31.9), respectively, prevalently downstaging PCa compared to RE. Sensitivity and specificity for ≥T3 stage in the mpMRI validation group were 81.8% (95%C.I. 65.1-91.9) and 88.5% (72.8-96.1).

CONCLUSION

RE and mpMRI show moderate agreement only in assessing the T-stage of PCa, translating into an mpMRI-induced change in risk assessment in about one fifth of patients. As supported by high sensitivity/specificity for ≥T3 stage in the validation group, the discrepancy we found is in favour of mpMRI as a tool to stage PCa before ERBT.

Evaluation of extracapsular extension in prostate cancer using qualitative and quantitative multiparametric MRI

PURPOSE

To investigate the value of multiparametric magnetic resonance imaging (mpMRI) for extracapsular extension (ECE) in prostate cancer (PCa).

MATERIALS AND METHODS

In all, 292 patients who received radical prostatectomy and underwent preoperative mpMRI at 3T were enrolled retrospectively. For determining the associations with ECE, the likelihood of ECE was assessed qualitatively on T₂ -weighted imaging (T₂ WI) and combined T₂ WI and diffusion-weighted imaging (DWI) or dynamic contrast-enhanced imaging (DCEI). Quantitative MRI parameters were measured in PCa based on histopathological findings. Two models for detecting ECE including imaging and clinical parameters were developed using multivariate analysis: Model 1 excluding combined T₂ WI and DWI and DCEI and Model 2 excluding combined T₂ WI and DWI, and combined T₂ WI and DCEI. Diagnostic performance of imaging parameters and models was evaluated using the area under the receiver operating characteristics curve (Az).

RESULTS

For detecting ECE, the specificity, accuracy, and Az of combined T₂ WI and DWI or DCEI were statistically better than those of T₂ WI (P < 0.05), and all quantitative MRI parameters showed a statistical difference between the patients with and without ECE (P < 0.05). On multivariate analysis, significant independent markers in Model 1 were combined T₂ WI and DWI, combined T₂ WI and DCEI, and K^trans (P < 0.05). In Model 2, significant markers were combined T₂ WI and DWI and DCEI, K^trans , K_ep , and Ve (P < 0.05). The Az values of models 1 and 2 were 0.944 and 0.957, respectively.

CONCLUSION

mpMRI may be useful to improve diagnostic accuracy of the models for determining the associations with ECE in PCa.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;45:1760-1770.

External validation of a PCA-3-based nomogram for predicting prostate cancer and high-grade cancer on initial prostate biopsy

INTRODUCTION

The aim of this study was to externally validate a previously developed PCA3-based nomogram for the prediction of prostate cancer (PCa) and high-grade (intermediate and/or high-grade) prostate cancer (HGPCa) at the time of initial prostate biopsy.

METHODS

A retrospective review was performed on a cohort of 336 men from a large urban academic medical center. All men had serum PSA <20 ng/ml and underwent initial transrectal ultrasound-guided prostate biopsy with at least 10 cores sampling for suspicious exam and/or elevated PSA. Covariates were collected for the nomogram and included age, ethnicity, family history (FH) of PCa, PSA at diagnosis, PCA3, total prostate volume (TPV), and abnormal finding on digital rectal exam (DRE). These variables were used to test the accuracy (concordance index) and calibration of a previously published PCA3 nomogram.

RESULTS

Biopsy confirms PCa and HGPCa in 51.0% and 30.4% of validation patients, respectively. This differed from the original cohort in that it had significantly more PCa and HGPCA (51% vs. 44%, P = 0.019; and 30.4% vs. 19.1%, P < 0.001). Despite the differences in PCa detection the concordance index was 75% and 77% for overall PCa and HGPCa, respectively. Calibration for overall PCa was good.

CONCLUSIONS

This represents the first external validation of a PCA3-based prostate cancer predictive nomogram in a North American population. Prostate 76:1019-1023, 2016. © 2016 Wiley Periodicals, Inc.

Risk stratification of prostate cancer: integrating multiparametric MRI, nomograms and biomarkers

Accurate risk stratification of prostate cancer is achieved with a number of existing tools to ensure the identification of at-risk patients, characterization of disease aggressiveness, prediction of cancer burden and extrapolation of treatment outcomes for appropriate management of the disease. Statistical tables and nomograms using classic clinicopathological variables have long been the standard of care. However, the introduction of multiparametric MRI, along with fusion-guided targeted prostate biopsy and novel biomarkers, are being assimilated into clinical practice. The majority of studies to date present the outcomes of each in isolation. The current review offers a critical and objective assessment regarding the integration of multiparametric MRI and fusion-guided prostate biopsy with novel biomarkers and predictive nomograms in contemporary clinical practice.

The nomogram conundrum: a demonstration of why a prostate cancer risk model in Turkish men underestimates prostate cancer risk in the USA

PURPOSE

The utility of a nomogram is based on the patient population it is designed for-and their inherent properties and biases. Our aim was to demonstrate the variability in predictive model accuracy and utility between different populations.

METHODS

Our model is based on 761 men who underwent initial TRUS biopsy at a single institution in Turkey. Patients were included if they had at least 10 cores on biopsy and PSA level <20 ng/ml. Multivariable logistic regression models were used to develop a new nomogram. External validity was tested with two different cohorts one from another institution in Turkey (N = 136) and cohort from USA (N = 2242).

RESULTS

Prostate cancer (PCa) and high-grade PCa was diagnosed in 249/761 (32.7 %) and 101/761 (13.3 %) patients from Ankara, Turkey, respectively. Predictors of PCa were age (p < 0.0001, OR 2.11), PSA (p = 0.044, OR 1.44), PV (p < 0.0001, OR 0.38), %fPSA (p = 0.016, OR 0.72), and abnormal DRE (p < 0.0001, OR 2.05). The predictive accuracy (c-index) of our nomogram was 73 %. C-indices of 71 and 70 % were recorded in external validation cohorts from Turkey and the USA, respectively. Virtually ideal calibration was recorded for the internal validated predictive model, and good calibration was recorded when applied to the Istanbul cohort. However, the model/nomogram underestimates PCa risk in the US cohort.

CONCLUSION

This is the first nomogram predicting the risk of PCa at initial biopsy in a Turkish population and provides a good risk estimation tool with good predictive accuracy and calibration in the Turkish populations. However, our study demonstrates the poor transferability of predictive tools to widely different populations.