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

Diagnostic performance of prediction models for extraprostatic extension in prostate cancer: a systematic review and meta-analysis

PURPOSE

In recent decades, diverse nomograms have been proposed to predict extraprostatic extension (EPE) in prostate cancer (PCa). We aimed to systematically evaluate the accuracy of MRI-inclusive nomograms and traditional clinical nomograms in predicting EPE in PCa. The purpose of this meta-analysis is to provide baseline summative and comparative estimates for future study designs.

MATERIALS AND METHODS

The PubMed, Embase, and Cochrane databases were searched up to May 17, 2023, to identify studies on prediction nomograms for EPE of PCa. The risk of bias in studies was assessed by using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). Summary estimates of sensitivity and specificity were obtained with bivariate random-effects model. Heterogeneity was investigated through meta-regression and subgroup analysis.

RESULTS

Forty-eight studies with a total of 57 contingency tables and 20,395 patients were included. No significant publication bias was observed for either the MRI-inclusive nomograms or clinical nomograms. For MRI-inclusive nomograms predicting EPE, the pooled AUC of validation cohorts was 0.80 (95% CI: 0.76, 0.83). For traditional clinical nomograms predicting EPE, the pooled AUCs of the Partin table and Memorial Sloan Kettering Cancer Center (MSKCC) nomogram were 0.72 (95% CI: 0.68, 0.76) and 0.79 (95% CI: 0.75, 0.82), respectively.

CONCLUSION

Preoperative risk stratification is essential for PCa patients; both MRI-inclusive nomograms and traditional clinical nomograms had moderate diagnostic performance for predicting EPE in PCa. This study provides baseline comparative values for EPE prediction for future studies which is useful for evaluating preoperative risk stratification in PCa patients.

CRITICAL RELEVANCE STATEMENT

This meta-analysis firstly evaluated the diagnostic performance of preoperative MRI-inclusive nomograms and clinical nomograms for predicting extraprostatic extension (EPE) in prostate cancer (PCa) (moderate AUCs: 0.72-0.80). We provide baseline estimates for EPE prediction, these findings will be useful in assessing preoperative risk stratification of PCa patients.

KEY POINTS

• MRI-inclusive nomograms and traditional clinical nomograms had moderate AUCs (0.72-0.80) for predicting EPE. • MRI combined clinical nomogram may improve diagnostic accuracy of MRI alone for EPE prediction. • MSKCC nomogram had a higher specificity than Partin table for predicting EPE. • This meta-analysis provided baseline and comparative estimates of nomograms for EPE prediction for future studies.

MRI-based nomograms and radiomics in presurgical prediction of extraprostatic extension in prostate cancer: a systematic review

PURPOSE

Prediction of extraprostatic extension (EPE) is essential for accurate surgical planning in prostate cancer (PCa). Radiomics based on magnetic resonance imaging (MRI) has shown potential to predict EPE. We aimed to evaluate studies proposing MRI-based nomograms and radiomics for EPE prediction and assess the quality of current radiomics literature.

METHODS

We used PubMed, EMBASE, and SCOPUS databases to find related articles using synonyms for MRI radiomics and nomograms to predict EPE. Two co-authors scored the quality of radiomics literature using the Radiomics Quality Score (RQS). Inter-rater agreement was measured using the intraclass correlation coefficient (ICC) from total RQS scores. We analyzed the characteristic s of the studies and used ANOVAs to associate the area under the curve (AUC) to sample size, clinical and imaging variables, and RQS scores.

RESULTS

We identified 33 studies-22 nomograms and 11 radiomics analyses. The mean AUC for nomogram articles was 0.783, and no significant associations were found between AUC and sample size, clinical variables, or number of imaging variables. For radiomics articles, there were significant associations between number of lesions and AUC (p < 0.013). The average RQS total score was 15.91/36 (44%). Through the radiomics operation, segmentation of region-of-interest, selection of features, and model building resulted in a broader range of results. The qualities the studies lacked most were phantom tests for scanner variabilities, temporal variability, external validation datasets, prospective designs, cost-effectiveness analysis, and open science.

CONCLUSION

Utilizing MRI-based radiomics to predict EPE in PCa patients demonstrates promising outcomes. However, quality improvement and standardization of radiomics workflow are needed.

A Critical Analysis of the Magnetic Resonance Imaging Lesion Diameter Threshold for Adverse Pathology Features

To investigate the relationship between lesion size determined using multiparametric magnetic resonance imaging (mpMRI) and histopathological findings of specimens obtained after mpMRI fusion biopsy and radical prostatectomy (RP). We retrospectively analysed 290 patients with PCa who underwent an MRI fusion biopsy. We measured the diameter of suspicious tumour lesions on diffusion-weighted mpMRI and stratified the cohort into two groups. Group A included patients with a suspicious tumour lesion 10 mm and Group B included those with a suspicious tumour lesion &gt; 10 mm. In Group B, the PI-RADS score determined in mpMRI was higher than Group A, and there was a statistically significant difference between the two groups in terms of clinical T-stage. The PCa detection rate and the number of positive cores were statistically significantly higher in Group B than in Group A. In addition, there was a statistically significant difference between the two groups in relation to the biopsy, the International Society of Urological Pathology (ISUP) grade values, and the presence of clinically significant PCa. In Group B, pathological T-stage and extraprostatic extension (EPE) and surgical margin (SM) positivity were found to be higher among the patients who underwent RP. In the multivariate analysis, the mpMRI lesion size being &gt; 10 mm was found to be an independent predictive factor for SM and EPE positivity. The clinical results of this study support the modification of the lesion size threshold as 10 mm for use in the differentiation of PI-RADS scores 4 and 5.

Concordance between Preoperative mpMRI and Pathological Stage and Its Influence on Nerve-Sparing Surgery in Patients with High-Risk Prostate Cancer

Background: We aimed to determine the concordance between the radiologic stage (rT), using multiparametric magnetic resonance imaging (mpMRI), and pathologic stage (pT) in patients with high-risk prostate cancer and its influence on nerve-sparing surgery compared to the use of the intraoperative frozen section technique (IFST). Methods: The concordance between rT and pT and the rates of nerve-sparing surgery and positive surgical margin were assessed for patients with high-risk prostate cancer who underwent radical prostatectomy. Results: The concordance between the rT and pT stages was shown in 66.4% (n = 77) of patients with clinical high-risk prostate cancer. The detection of patients with extraprostatic disease (≥pT3) by preoperative mpMRI showed a sensitivity, negative predictive value and accuracy of 65.1%, 51.7% and 67.5%. In addition to the suspicion of extraprostatic disease in mpMRI (≥rT3), 84.5% (n = 56) of patients with ≥rT3 underwent primary nerve-sparing surgery with IFST, resulting in 94.7% (n = 54) of men with at least unilateral nerve-sparing surgery after secondary resection with a positive surgical margin rate related to an IFST of 1.8% (n = 1). Conclusion: Patients with rT3 should not be immediately excluded from nerve-sparing surgery, as by using IFST some of these patients can safely undergo nerve-sparing surgery.

The prognostic value of digital rectal exam for the existence of advanced pathologic features after prostatectomy

BACKGROUND

Accurate staging at the time of prostate cancer diagnosis is fundamental to risk stratification and management counseling. Digital rectal exam (DRE) is foundational in clinical staging of prostate cancer, even with a known limited interexaminer agreement and poor sensitivity for detecting extraprostatic disease. We sought to evaluate the prognostic value of DRE for the presence of advanced pathologic features (APFs) following radical prostatectomy (RP).

METHODS

All patients undergoing RP as primary treatment for clinically localized prostate cancer in the National Cancer Database between 2008 and 2014 were identified. Patients with additional malignancies, prior treatment with radiation or systemic therapy, incongruent clinical staging and DRE findings or without fully evaluable clinical staging were excluded. The primary outcome was the presence of postsurgical APFs, defined as positive surgical margins, nodal disease, or pathologic stage T3 or greater. Multivariable logistic regression analysis was performed to account for prostate-specific antigen (PSA), biopsy grade group, percent of positive biopsy cores, and clinical stage.

RESULTS

In total, 91,525 patients consisting of 69,182 cT1, 20,641 cT2, and 1702 cT3-T4 were included. The average age was 61.1 ± 7.0 years, and the average PSA was 8.6 ± 10.3 ng/ml. On multivariable analysis, cT3 and T4 were associated with the presence of APFs (odds ratio [OR] 11.12, p < .01 and 5.28, p = .04), however, cT2 was only slightly associated with the presence of APFs when compared with cT1 (OR 1.15, p < .01). Furthermore, cT2 was associated with more node-positive disease (OR 1.63, p < .01), positive margins (OR 1.06, p < .01), and more than or equal to pT3 disease (OR 1.22, p < .01).

CONCLUSIONS

Overall, advanced clinical stage as assessed by DRE was independently associated with an increasing risk of APFs. For individual APFs, the greatest effect is noticed between clinical stage and nodal positivity and less so between clinical stage and positive margins. DRE continues to hold value, particularly for patients with locally advanced disease and potential lymph node disease.

International Multi-Site Initiative to Develop an MRI-Inclusive Nomogram for Side-Specific Prediction of Extraprostatic Extension of Prostate Cancer

BACKGROUND

To develop an international, multi-site nomogram for side-specific prediction of extraprostatic extension (EPE) of prostate cancer based on clinical, biopsy, and magnetic resonance imaging- (MRI) derived data.

METHODS

Ten institutions from the USA and Europe contributed clinical and side-specific biopsy and MRI variables of consecutive patients who underwent prostatectomy. A logistic regression model was used to develop a nomogram for predicting side-specific EPE on prostatectomy specimens. The performance of the statistical model was evaluated by bootstrap resampling and cross validation and compared with the performance of benchmark models that do not incorporate MRI findings.

RESULTS

Data from 840 patients were analyzed; pathologic EPE was found in 320/840 (31.8%). The nomogram model included patient age, prostate-specific antigen density, side-specific biopsy data (i.e., Gleason grade group, percent positive cores, tumor extent), and side-specific MRI features (i.e., presence of a PI-RADSv2 4 or 5 lesion, level of suspicion for EPE, length of capsular contact). The area under the receiver operating characteristic curve of the new, MRI-inclusive model (0.828, 95% confidence limits: 0.805, 0.852) was significantly higher than that of any of the benchmark models (p < 0.001 for all).

CONCLUSIONS

In an international, multi-site study, we developed an MRI-inclusive nomogram for the side-specific prediction of EPE of prostate cancer that demonstrated significantly greater accuracy than clinical benchmark models.

Prediction of Pathologic Findings with MRI-Based Clinical Staging Using the Bayesian Network Modeling in Prostate Cancer: A Radiation Oncologist Perspective

Purpose

This study aimed to develop a model for predicting pathologic extracapsular extension (ECE) and seminal vesicle invasion (SVI) while integrating magnetic resonance imaging-based T-staging (cTMRI, cT1c-cT3b).

Materials and Methods

A total of 1,915 who underwent radical prostatectomy between 2006-2016 met the inclusion/exclusion criteria. We performed a multivariate logistic regression analysis as well as Bayesian network (BN) modeling based on possible confounding factors. The BN model was internally validated using 5-fold validation.

Results

According to the multivariate logistic regression analysis, initial prostate-specific antigen (iPSA) (β=0.050, p<0.001), percentage of positive biopsy cores (PPC) (β=0.033, p<0.001), both lobe involvement on biopsy (β=0.359, p=0.009), Gleason score (β=0.358, p<0.001), and cTMRI (β=0.259, p<0.001) were significant factors for ECE. For SVI, iPSA (β=0.037, p<0.001), PPC (β=0.024, p<0.001), GS (β=0.753, p<0.001), and cTMRI (β=0.507, p<0.001) showed statistical significance. BN models to predict ECE and SVI were also successfully established. The overall AUC/accuracy of the BN models were 0.76/73.0% and 0.88/89.6% for ECE and SVI, respectively. According to internal comparison between the BN model and Roach formula, BN model had improved AUC values for predicting ECE (0.76 vs. 0.74; p=0.060) and SVI (0.88 vs. 0.84, p<0.001).

Conclusion

wo models to predict pathologic ECE and SVI integrating cTMRI were established and installed on a separate website for public access to guide radiation oncologists.

Nomograms in Urologic Oncology: Lights and Shadows

Decision-making in urologic oncology involves integrating multiple clinical data to provide an answer to the needs of a single patient. Although the practice of medicine has always been an “art” involving experience, clinical data, scientific evidence and judgment, the creation of specialties and subspecialties has multiplied the challenges faced every day by physicians. In the last decades, with the field of urologic oncology becoming more and more complex, there has been a rise in tools capable of compounding several pieces of information and supporting clinical judgment and experience when approaching a difficult decision. The vast majority of these tools provide a risk of a certain event based on various information integrated in a mathematical model. Specifically, most decision-making tools in the field of urologic focus on the preoperative or postoperative phase and provide a prognostic or predictive risk assessment based on the available clinical and pathological data. More recently, imaging and genomic features started to be incorporated in these models in order to improve their accuracy. Genomic classifiers, look-up tables, regression trees, risk-stratification tools and nomograms are all examples of this effort. Nomograms are by far the most frequently used in clinical practice, but are also among the most controversial of these tools. This critical, narrative review will focus on the use, diffusion and limitations of nomograms in the field of urologic oncology.

Prostate MRI added to CAPRA, MSKCC and Partin cancer nomograms significantly enhances the prediction of adverse findings and biochemical recurrence after radical prostatectomy

Background

To determine the added value of preoperative prostate multiparametric MRI (mpMRI) supplementary to clinical variables and their role in predicting post prostatectomy adverse findings and biochemically recurrent cancer (BCR).

Methods

All consecutive patients treated at HUS Helsinki University Hospital with robot assisted radical prostatectomy (RALP) between 2014 and 2015 were included in the analysis. The mpMRI data, clinical variables, histopathological characteristics, and follow-up information were collected. Study end-points were adverse RALP findings: extraprostatic extension, seminal vesicle invasion, lymph node involvement, and BCR. The Memorial Sloan Kettering Cancer Center (MSKCC) nomogram, Cancer of the Prostate Risk Assessment (CAPRA) score and the Partin score were combined with any adverse findings at mpMRI. Predictive accuracy for adverse RALP findings by the regression models was estimated before and after the addition of MRI results. Logistic regression, area under curve (AUC), decision curve analyses, Kaplan-Meier survival curves and Cox proportional hazard models were used.

Results

Preoperative mpMRI data from 387 patients were available for analysis. Clinical variables alone, MSKCC nomogram or Partin tables were outperformed by models with mpMRI for the prediction of any adverse finding at RP. AUC for clinical parameters versus clinical parameters and mpMRI variables were 0.77 versus 0.82 for any adverse finding. For MSKCC nomogram versus MSKCC nomogram and mpMRI variables the AUCs were 0.71 and 0.78 for any adverse finding. For Partin tables versus Partin tables and mpMRI variables the AUCs were 0.62 and 0.73 for any adverse finding. In survival analysis, mpMRI-projected adverse RP findings stratify CAPRA and MSKCC high-risk patients into groups with distinct probability for BCR.

Conclusions

Preoperative mpMRI improves the predictive value of commonly used clinical variables for pathological stage at RP and time to BCR. mpMRI is available for risk stratification prebiopsy, and should be considered as additional source of information to the standard predictive nomograms.

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.

Digital Rectal Examination Remains a Key Prognostic Tool for Prostate Cancer: A National Cancer Database Review

BACKGROUND

Prostate cancer clinical stage T2 (cT2) subclassifications, as determined by digital rectal examination (DRE), are a historic method of staging prostate cancer. However, given the potential discomfort associated with prostate examination and the wide availability of other prognostic tests, the necessity of DRE is uncertain. This study sought to determine the prognostic value of the prostate cancer cT2 subclassifications in a contemporary cohort of patients.

METHODS

The National Cancer Database was used to identify a cohort of men with high-risk clinical T2N0M0 prostate cancer treated with external-beam radiotherapy and androgen deprivation therapies ± surgery from 2004 to 2010. We assessed overall survival from a landmark time of 10 months using Kaplan-Meier and log-rank test analysis. A multivariate proportional hazards model was used to estimate the simultaneous effects of multiple factors, including cT2 subclassification and other well-established prognostic indicators of overall survival in prostate cancer.

RESULTS

A total of 5,291 men were included in the final analysis, with a median follow-up of 5.4 years. The cT2a, cT2b, and cT2c subclassifications demonstrated increasing hazard ratios of 1.00 (reference), 1.25 (95% CI, 1.07-1.45; P=.0046), and 1.43 (95% CI, 1.25-1.63; P<.0001), respectively, reflecting a higher probability of death with each incremental increase in cT2 subclassification. This finding was independent of other known prognostic variables on multivariate analysis.

CONCLUSIONS

Results show that cT2 subclassifications had independent prognostic value in a large and contemporary cohort of men. cT2 classification remains an important, low-cost prognostic tool for men with prostatic adenocarcinoma. The clinical relevance of this test should be appreciated and accounted for by providers treating prostate adenocarcinoma.

Local staging with multiparametric MRI in daily clinical practice: diagnostic accuracy and evaluation of a radiologic learning curve

PURPOSE

To estimate the diagnostic accuracy of multiparametric MRI (mpMRI) for the detection of locally advanced prostate cancer (T-stage 3-4) prior to radical prostatectomy, in a multicenter cohort representing daily clinical practice. In addition, the radiologic learning curve for the detection of locally advanced disease is evaluated.

METHODS

Preoperative mpMRI findings of 430 patients (2012-2016) were compared to pathology results following radical prostatectomy. The diagnostic accuracy (sensitivity, specificity, PPV, and NPV) for the detection of locally advanced disease was calculated and compared for all years separately, to evaluate the presence of a radiological learning curve.

RESULTS

Of all 137 patients with locally advanced disease, 62 patients were preoperatively detected with mpMRI [sensitivity 45.3% (95% CI 36.9-53.6%), specificity 75.8% (CI 70.9-80.7%), PPV 46.6% (CI 38.1-55.1%), and NPV 74.7% (CI 69.8-79.7%)]. The diagnostic accuracy did not improve significantly over time (sensitivity p = 0.12; specificity p = 0.57).

CONCLUSIONS

In daily clinical practice, the diagnostic accuracy of mpMRI for the detection of locally advanced prostate cancer remains limited. It, therefore, seems questionable whether mpMRI is adequate to guide preoperative decision-making. No significant radiologic learning curve for the detection of locally advance disease was observed.

[Prostate cancer diagnostic by saturation randomized biopsy versus rigid targeted biopsy]

INTRODUCTION

Optimal diagram teaming up randomized biopsy (BR) to targeted biopsy (BC) is still missing for the diagnostic of prostate cancer (CP). This study compares diagram of 6, 12 or 18 BR with or without BC rigid.

METHODS

Between January 2014 and May 2016, 120 patients had prostate biopsy BR and BC. Each patient had 18 BR and BC. Results compared sextant (6 BR), standard (12 BR) and saturation (18 BR) protocol with or without the adding of BC for the detection of CP.

RESULTS

Rectal examination was normal, mean PSA at 8.99ng/mL and mean volume at 54cm³. It was first round for 48% of patients. Forty-four cancers were found by the group 18 BR+BC (control). The detection rate was respectively, for 6, 12 and 18 BR of 61%, 82% and 91%. The add of BC increased this detection of +27% for 6 BR+BC, +13% for 12 BR+BC and +9% for 18 BR+BC. BC found 70% of all CP. Nine percent of CP were missed by BR only. Significant CP (Gleason≥7) diagnostic was the same for 12 BR+BC and 18 BR+BC.

CONCLUSION

The add of BC to BR increase the detection of CP by 10%. Twelve BR+BC is the optimal diagram for the diagnostic of CP finding 95% of CP and 97% of significant CP.

LEVEL OF EVIDENCE

4.