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.

Significance of the cribriform pattern in prostatic adenocarcinomas

INTRODUCTION

There is now increased understanding that invasive cribriform carcinoma is a relatively aggressive disease. In some recent publications, the recommendation is that all cribriform patterns be classified as Gleason pattern (GP) 4 rather than GP 3.

MATERIALS AND METHODS

We assessed the cribriform foci (CF) associated with the more definitive patterns 3, 4, and 5 elsewhere on the 185 radical prostatectomy specimens and evaluated the association of the cribriform pattern with extraprostatic extension, surgical margin.

RESULTS

CF were more frequently observed in cases with definitive patterns 4 and 5 than in cases with pattern 3 (all cases with pattern 5 exhibited CF). Cases with Gleason score 3+3 and CF were more frequently associated with extraprostatic extension, and a positive surgical margin.

CONCLUSIONS

Our results demonstrate that diagnosing all cribriform patterns as at least GP 4 would significantly affect further therapeutic options and prognosis. However, as many of these modifications are empirical and supported by only a few studies, long-term follow-up studies with clinical endpoints are necessary to validate these recommendations.

Development and External Validation of a Novel Nomogram to Predict Side-specific Extraprostatic Extension in Patients with Prostate Cancer Undergoing Radical Prostatectomy

BACKGROUND

Prediction of side-specific extraprostatic extension (EPE) is crucial in selecting patients for nerve-sparing radical prostatectomy (RP).

OBJECTIVE

To develop and externally validate nomograms including multiparametric magnetic resonance imaging (mpMRI) information to predict side-specific EPE.

DESIGN, SETTING, AND PARTICIPANTS

A retrospective analysis of 1870 consecutive prostate cancer patients who underwent robot-assisted RP from 2014 to 2018 at three institutions.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Four multivariable logistic regression models were established, including combinations of patient-based and side-specific variables: prostate-specific antigen (PSA) density, highest ipsilateral International Society of Urological Pathology (ISUP) biopsy grade, ipsilateral percentage of positive cores on systematic biopsy, and side-specific clinical stage assessed by both digital rectal examination and mpMRI. Discrimination (area under the curve [AUC]), calibration, and net benefit of these models were assessed in the development cohort and two external validation cohorts.

RESULTS AND LIMITATIONS

On external validation, AUCs of the four models ranged from 0.80 (95% confidence interval [CI] 0.68-0.88) to 0.83 (95% CI 0.72-0.90) in cohort 1 and from 0.77 (95% CI 0.62-0.87) to 0.78 (95% CI 0.64-0.88) in cohort 2. The three models including mpMRI staging information resulted in relatively higher AUCs compared with the model without mpMRI information. No major differences between the four models regarding net benefit were established. The model based on PSA density, ISUP grade, and mpMRI T stage was superior in terms of calibration. Using this model with a cut-off of 20%, 1980/2908 (68%) prostatic lobes without EPE would be found eligible for nerve sparing, whereas non-nerve sparing would be advised in 642/832 (77%) lobes with EPE.

CONCLUSIONS

Our analysis resulted in a simple and robust nomogram for the prediction of side-specific EPE, which should be used to select patients for nerve-sparing RP.

PATIENT SUMMARY

We developed a prediction model that can be used to assess accurately the likelihood of tumour extension outside the prostate. This tool can guide patient selection for safe nerve-sparing surgery.

The Role of Magnetic Resonance Imaging and Positron Emission Tomography/Computed Tomography in the Primary Staging of Newly Diagnosed Prostate Cancer: A Systematic Review of the Literature

CONTEXT

Management of newly diagnosed prostate cancer (PCa) is guided in part by accurate clinical staging. The role of imaging, including magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT), in initial staging remains controversial.

OBJECTIVE

To systematically review the studies of MRI and/or PET/CT in the staging of newly diagnosed PCa with respect to tumor (T), nodal (N), and metastatic (M) staging (TNM staging).

EVIDENCE ACQUISITION

We performed a systematic review of the literature using MEDLINE and Web of Science databases between 2012 and 2020 following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement guidelines.

EVIDENCE SYNTHESIS

A total of 139 studies (83 on T, 47 on N, and 24 on M status) were included. Ninety-nine (71%) were retrospective, 39 (28%) were prospective, and one was a randomized controlled trial (RCT). Most studies on T staging examined MRI, while PET/CT was used primarily for N and M staging. Sensitivity for the detection of extraprostatic extension, seminal vesicle invasion, or lymph node invasion ranged widely. When imaging was incorporated into existing risk tools, gain in accuracy was observed in some studies, although these findings have not been replicated. For M staging, most favorable results were reported for prostate-specific membrane antigen (PSMA) PET/CT, which demonstrated significantly better performance than conventional imaging.

CONCLUSIONS

A variety of studies on modern imaging techniques for TNM staging in newly diagnosed PCa exist. For T and N staging, reported sensitivity of imaging modalities such as MRI or PET/CT varied widely due to data heterogeneity, small sample size, and low event rates resulting in large confidence intervals and a high level of uncertainty. Therefore, uniformity in data presentation and standardization on this topic are needed. The most promising technique for M staging, which was evaluated recently in an RCT, is PSMA-PET/CT.

PATIENT SUMMARY

We performed a systematic review of currently available imaging modalities to stage newly diagnosed prostate cancer. With respect to local tumor and lymph node assessment, performance of imaging ranged widely. However, prostate-specific membrane antigen positron emission tomography/computed tomography showed favorable results for the detection of distant metastases.

Extraprostatic extension in prostate cancer: primer for radiologists

The presence of extraprostatic extension (EPE) on multiparametric MRI (mpMRI) is an important factor in determining the management of prostate cancer. EPE is an established risk factor for biochemical recurrence of prostate cancer after radical prostatectomy (RP) and patients with EPE may be considered for wider resection margins, non-nerve-sparing surgery, adjuvant radiation therapy (RT), or androgen deprivation therapy (ADT). Several statistical nomograms and scoring systems have been developed to predict pathological stage at time of RP but with varying accuracies. Using the current PI-RADS v2 mpMRI staging guidelines results in high specificity but lacks in sensitivity. These findings reveal the need for more standardization and further refinement of existing MRI protocols and prostate cancer prediction tools. Current studies have looked into indirect additional imaging criteria such as index tumor volume, length of capsular contact, and apparent diffusion coefficient. Measuring for these features can improve the robustness of mpMRI in staging prostate cancer, as they have been shown to be independent predictors of EPE. MRI/ultrasound fusion-guided targeted biopsy can detect EPE not found on standard biopsy. Collectively, these measurements and imaging techniques can augment the detection of EPE and subsequent risk stratification.

Multiparametric Magnetic-Resonance to Confirm Eligibility to an Active Surveillance Program for Low-Risk Prostate Cancer: Intermediate Time Results of a Third Referral High Volume Centre Active Surveillance Protocol

BACKGROUND

To evaluate the role of confirmatory multiparametric magnetic resonance imaging (mpMRI) of the prostate at the time of Active Surveillance (AS) enrollment to reduce disease misclassification.

MATERIALS

From 2012 to 2016, 383 patients with low-risk disease respecting Prostate Cancer Research International AS criteria underwent confirmatory 1.5-T mpMRI. AS was proposed to patients with Prostate Imaging and Report and Data System (PI-RADS) score ≤3 and no extraprostatic extension (EPE), whereas patients with PI-RADS score ≥4 and/or EPE were treated actively. Kaplan-Meier analyses quantified progression-free survival (PFS) in patients enrolled in the AS program. Logistic regression analyses tested the association between confirmatory mpMRI and clinically significant prostate cancer (csPCa) at radical prostatectomy (RP). Diagnostic performance of mpMRI was calculated in patients submitted to immediate RP.

RESULTS

PFS rate was 99, 90 and 86% at 1, 2 and 3 years respectively. At multivariable analysis, PI-RADS 3, PI-RADS 4, PI-RADS 5 and EPE increased the probability of having csPCa at immediate RP (PI-RADS 3 [OR] 1.2, p = 0.26; PI-RADS 4 [OR] 5.1, p = 0.02; PI-RADS 5 [OR] 6.7; p = 0.009; EPE [OR] 11.8, p < 0.001). Confirmatory mpMRI showed sensibility, specificity, positive predictive value and negative predictive value of 85, 55, 68 and 76% respectively.

CONCLUSIONS

MpMRI at the time of AS enrollment reduces the misclassification rate of csPCa. We suggest to perform target biopsies in patients with PI-RADS score 3 and 4 lesions.

External validation of the Martini nomogram for prediction of side-specific extraprostatic extension of prostate cancer in patients undergoing robot-assisted radical prostatectomy

INTRODUCTION

To establish oncological safe nerve-sparing robot-assisted radical prostatectomy, accurate assessment of extraprostatic extension (EPE) is critical. A recently developed nomogram including magnetic resonance imaging parameters accurately predicted side-specific EPE in the development cohort. The aim of this study is to assess this model's performance in an external patient population.

PATIENTS AND METHODS

Model fit was assessed in a cohort of 550 patients who underwent robot-assisted radical prostatectomy in 2014 to 2017 for prostate cancer. Model calibration was evaluated using calibration slopes. Discriminative ability was quantified using the area under the receiver operating characteristic curve. Model updating was done by adjusting the linear predictor to minimize differences in expected and observed risk for EPE.

RESULTS

A total of 792 prostate lobes were included for model validation. Discriminative ability expressed in terms of receiver operating characteristic curve was 0.78, 95%CI 0.75-0.82. Graphical evaluation of the calibration showed poor fit with a high disagreement between predicted probabilities and observed probabilities of EPE in the population. Model updating resulted in excellent agreement between mean predicted and observed probabilities. However, calibration plots showed substantial miscalibration; including both under- and overestimation.

CONCLUSION

External validation of the novel nomogram for the prediction of side specific EPE developed by Martini and co-workers showed good discriminative ability but poor calibration. After updating, substantial miscalibration was still present. Use of this nomogram for individualized risk predictions is therefore not recommended.

Impact of positive surgical margin on biochemical recurrence in localized prostate cancer

BACKGROUND

We analyzed the relationship between biochemical recurrence (BCR) and the status of positive surgical margin (PSM) in patients with pT3a prostate cancer (PCa).

MATERIALS AND METHODS

Patients (n = 150) who underwent radical prostatectomy for pT3a PCa without nodal/distant metastasis were retrospectively reviewed between 2010 and 2013. The data regarding the status of PSM including the number, length, and margin Gleason score were collected. The predictors of BCR were analyzed using Cox regression hazard models. BCR-free survival was compared between the patients with negative surgical margin (NSM) and with PSM using Kaplan-Meier curves and log-rank tests.

RESULTS

PSM was noted in 74 patients (49.3%). Seventy-six patients (50.7%) had NSM and 38 patients (25.3%) had single PSM. Twenty patients (13.3%) had two PSMs and 16 patients (10.7%) had ≥3 PSMs. In total patients, the multivariate analysis demonstrated that a pathological Gleason score of ≥8 was significantly associated with BCR [hazard ratio (HR), 2.173; 95% confidence interval (CI), 1.244-3.797; P = 0.038]. In patients with PSM, the number of PSM more than two was significantly associated with BCR (HR, 2.723; 95% CI, 1.256-5.902; P = 0.011). PSM length of ≥3 mm was also a significant predictive factor (HR, 1.024; 95% CI, 0.994-1.055, P = 0.042). Patients with the highest margin Gleason score of ≥4 had poorer BCR-free survival than those with that of 3/no surgical margin.

CONCLUSIONS

Number (more than one), length (≥3 mm), and higher margin Gleason score (≥4) of PSM were significantly associated with an increased likelihood of BCR in patients with pT3a PCa.

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.

Effects of perineural invasion in prostate needle biopsy on tumor grade and biochemical recurrence rates after radical prostatectomy

To predict local invasive disease before retropubic radical prostatectomy (RRP), the correlation of perineural invasion (PNI) on prostate needle biopsy (PNB) and RRP pathology data and the effect of PNI on biochemical recurrence (BR) were researched. For patients with RRP performed between 2005 and 2014, predictive and pathologic prognostic factors were assessed. Initially all and D'Amico intermediate-risk group patients were comparatively assessed in terms of being T2 or T3 stage on RRP pathology, positive or negative for PNI presence on PNB and positive or negative BR situation. Additionally the effect of PNI presence on recurrence-free survival (RFS) rate was investigated. When all patients are investigated, multivariate analysis observed that in T3 patients PSA, PNB Gleason score (GS) and tumor percentage were significantly higher; in PNI positive patients PNB GS, core number and tumor percentage were significantly higher and in BR positive patients PNB PNI positivity and core number were significantly higher compared to T2, PNI negative and BR negative patients, separately (p < 0.05). When D'Amico intermediate-risk patients are evaluated, for T3 patients PSA and PNB tumor percentage; for PNI positive patients PNB core number and tumor percentage; and for BR positive patients PNB PNI positivity were significantly higher compared to T2, PNI negative and BR negative patients, separately (p < 0.05). Mean RFS in the whole patient group was 56.4 ± 4.2 months for PNI positive and 96.1 ± 5.7 months for negative groups. In the intermediate-risk group, mean RFS was 53.7 ± 5.1 months for PNI positive and 100.3 ± 7.7 months for negative groups (p < 0.001). PNI positivity on PNB was shown to be an important predictive factor for increased T3 disease and BR rates and reduced RFS.

Determining the cut-off values of tumor diameter, degree of extraprostatic extension, and extent of surgical margin positivity with regard to biochemical recurrence of prostate cancer after radical prostatectomy

BACKGROUND

The pre-biopsy (bx) prostate-specific antigen (PSA) level, tumor volume/diameter, degree of extraprostatic extension (EPE), and extent of surgical margin positivity have been shown to be significant prognostic parameters of biochemical recurrence (BCR) after radical prostatectomy. The present study assessed the cut-off values of the pre-bx PSA level, maximum tumor diameter, radial and circumferential distances of EPE, and circumferential length of surgical margin (SM) positivity with regard to BCR.

MATERIAL AND METHODS

The study included 445 radical prostatectomy specimens, and the cut-off values of all parameters were determined using receiver operating characteristic curve analysis.

RESULTS

An ISUP grade group ≥ 3, radial distance of EPE >1 mm, and circumferential length of SM positivity ≥2 mm were identified as independent predictors of BCR after radical prostatectomy. The parameters that showed statistical significance in univariate analysis, such as pre-bx PSA level ≥ 7.20 ng/mL, tumor diameter ≥ 19.5 mm, presence of seminal vesicle invasion, and circumferential distance of EPE >3 mm, did not have independent prognostic values for BCR.

CONCLUSIONS

An ISUP grade group ≥ 3, radial distance of EPE >1 mm, and circumferential length of SM positivity ≥2 mm are predictors of BCR. Our findings might have significance in risk classification and adjuvant therapy consideration among patients with localized prostate cancer.

Quality assessment of prostate MRI by PI-QUAL score: Inter-reader agreement and impact on prostate cancer local staging at 3 Tesla

PURPOSE

To evaluate whether the Prostate Imaging Quality (PI-QUAL) score impacts prostate cancer (PCa) staging on MRI. The secondary goal was to test inter-reader agreement among radiologists experienced in prostate imaging.

METHOD

A retrospective, single-center study with patients who underwent 3 Tesla prostate MRI scans and were submitted to radical prostatectomy (RP) between January 2018 and November 2021 and were eligible for our study. Extraprostatic extension (EPE) data were collected from original MR reports (EPEm) and pathological reports of RP specimens (EPEp). Three expert prostate radiologists (ESUR/ESUI criteria R1, R2, R3) independently evaluated all MRI exams according to PI-QUAL score for image quality (1 to 5; 1: poor, 5: excellent), blinded to original imaging reports and clinical data. We studied the diagnostic performance of MRI using pooled data from PI-QUAL scores (≤3 vs. ≥4). We also performed univariate and multivariate analyses to assess the PI-QUAL score impact on local PCa staging. Cohen's K and Tau-b Kendall tests were used to assess the inter-reader agreement for PI-QUAL score, T2WI, DWI, and DCE.

RESULTS

Our final cohort included 146 patients, of which 27.4% presented EPE on pathology. We observed no impact of imaging quality on accuracy for EPE prediction: AUC of 0.750 (95% CI 0.26-1) for PI-QUAL ≤ 3 and 0.705 (95% CI 0.618-0.793) for PI-QUAL ≥ 4. The multivariate analysis demonstrated a correlation of EPEm (OR 3.25, p 0.001) and ISUP grade group (OR 1.89, p 0.012) to predict EPEp. The inter-reader agreement was moderate to substantial (0.539 for R1-R2, 0.522 for R2-R3, and 0.694 for R1-R3).

CONCLUSION

Our clinical impact evaluation showed no direct correlation between MRI quality by PI-QUAL score and accuracy in detecting EPE in patients undergoing RP. Additionally, we had moderate to a substantial inter-reader agreement for the PI-QUAL score.

[Imaging of locally advanced prostate cancer : Importance of ultrasound and especially MRI]

Prostate cancer is the most common male malignant tumor in Germany, which thus places growing demands on differentiated imaging and risk-adapted therapeutic approaches. Multiparametric MRI (mpMRI) of the prostate enables reliable detection of clinically significant cancers and is currently the leading imaging modality for the detection, characterization, and local staging of prostate cancer. According to the German S3 guideline, mpMRI of the prostate is currently primarily recommended in patients with previous negative TRUS biopsies and persisting tumor suspicion. The serial use of mpMRI in the pretherapeutic setting can support individual therapy planning of patients with locally advanced prostate cancer in the near future.

Digital versus light microscopy assessment of extraprostatic extension in radical prostatectomy samples

Focal or non-focal/extensive extraprostatic extension of prostate carcinoma is an important pathologic prognostic parameter to be reported after radical prostatectomy. Currently, there is no agreement on how to measure and what are the best cutoff points to be used in practice. We hypothesized that digital microscopy would potentially provide more objective measurements of extraprostatic extension, thus better defining its clinical significance. To further our knowledge on digital prostate pathology, we evaluated the status of extraprostatic extension in 107 consecutive laparoscopic radical prostatectomy samples, using digital and conventional light microscopy. Mean linear and radial measurements of extraprostatic extension by digital microscopy significantly correlated to pT status (p = 0.022 and p = 0.050, respectively) but only radial measurements correlated to biochemical recurrence (p = 0.042) and grade groups (p = 0.022). None of the measurements, whether conventional or digital, were associated with lymph node status. Receiving operating characteristic analysis showed a potential cutoff point to assess linear measurements by conventional (< vs. > 24.21 mm) or digital microscopy (< vs. > 15 mm) or by radial measurement (< vs. > 1.6 mm). Finally, we observed an association between the number of paraffin blocks bearing EPE with pT (p = 0.041) status (digital microscopy), and linear measurements by conventional (p = 0.044) or digital microscopy (p = 0.045) with lymph node status. Reporting EPE measurements by digital microscopy, both linear and radial, and the number of paraffin blocks with EPE, might provide additional prognostic features after radical prostatectomy.

Iatrogenic Extraprostatic Extension of Prostate Cancer From a Needle Biopsy

Seeding of prostate cancer along a needle biopsy track is a rare complication. The diagnosis of this presents a significant upstaging of the disease and profound potential changes to the treatment strategy. In this report, we present a 71 year-old male with otherwise low-risk prostate cancer on final pathology except for extraprostatic extension (EPE) along a probable needle track. We further review the relevant literature regarding this rare but important complication with prostate needle biopsy.

The role of T2-weighted images in assessing the grade of extraprostatic extension of the prostate carcinoma

PURPOSE

Extraprostatic extension (EPE) is an unfavorable prognostic factor and the grade of EPE is also shown to be correlated with the prognosis of prostate cancer. The current study assessed the value of prostate magnetic resonance imaging (MRI) in measuring the radial distance (RD) of EPE and the role of T2 WI signs in predicting the grade of EPE.

MATERIALS AND METHODS

A total of 110 patients who underwent prostate MRI before radical prostatectomy are enrolled in this retrospective study. Eighty-four patients have organ confined disease and the remaining twenty-six patients have EPE all verified by histopathology. Prostate MRI examinations were conducted with 3T MRI scanner and phased array coil with the following sequences: T2 WI, T1 WI, DCE, DWI with ADC mapping, and high b-value at b = 1500 s/mm². The likelihood of EPE with 5-point Likert scale was assigned, several MRI features were extracted for each dominant tumor identified by using T2 WI. Tumors with Likert scales 4-5 were evaluated further to obtain MRI-based RD. The relationship between pathological and MRI-determined RD was tested. Univariate and multivariate logistic regression models were developed to detect the grade of pathological EPE. The inputs were among the 2 clinical parameters and 4 MRI features.

RESULTS

There is a moderate correlation between pathological RD and MRI-determined RD (ρ = 0.45, P < 0.01). In univariate and multivariate models, MRI features and clinical parameters possess varying significance levels (univariate models; P = 0.048-0.788, multivariate models; P = 0.173-0.769). Multivariate models perform better than the univariate models by offering fair to good performances (AUC = 0.69-0.85). The multivariate model that employs the MRI features offers better performance than the model employs clinical parameters (AUC = 0.81 versus 0.69).

CONCLUSION

Co-existence of T2 WI signs provide higher diagnostic value even than clinical parameters in predicting the grade of EPE. Combined use of clinical parameters and MRI features deliver slightly superior performance than MRI features alone.

MRI detected extaprostatic extension (EPE) in prostate cancer: Do all T3a patients have the same outcomes?

MRI-detected T3a prostate cancer is a heterogeneous disease. This post-hoc analysis of a prospective trial found that patients with T3a disease presenting obliteration of the recto-prostatic angle, contact-asymmetry of neuro-vascular bundle and periprostatic fat invasion, may be at higher risk of biochemical failure and metastases.

Impact of Endorectal Coil Use on Extraprostatic Extension Detection in Prostate MRI: A Retrospective Monocentric Study

RATIONALE AND OBJECTIVES

Accurate preoperative mpMRI-based detection of extraprostatic extension (EPE) in prostate cancer (PCa) is critical for surgical planning and patient outcomes. This study aims to evaluate the impact of endorectal coil (ERC) use on the diagnostic performance of mpMRI in detecting EPE.

MATERIALS AND METHODS

This retrospective study with prospectively collected data included participants who underwent mpMRI and subsequent radical prostatectomy for PCa between 2007 and 2024. Participants were divided based on ERC use on mpMRI: MRI without ERC and with ERC. Surgical pathology reports were used to determine the patients with pathologic EPE on whole-mount histopathology. One radiologist evaluated mpMRI using an in-house (National Cancer Institute [NCI]) EPE grading system. Logistic regression (LR) analyses were conducted to identify significant predictors of pathologic EPE, including ERC use and NCI EPE grades.

RESULTS

934 men (median age: 62 years [IQR = 57-67]) were included. For NCI EPE grade≥1, ERC MRI group (n = 612) had higher NPV (91% [320/353] vs. 83% [166/200], p = 0.01) and sensitivity (75% [101/134] vs. 62% [56/90], p = 0.04) compared to non-ERC group (n = 322). For NCI EPE grade = 3, ERC MRI group had higher NPV (83% [452/546] vs. 75% [221/294], p = 0.01) and accuracy (80% [492/612] vs. 74% [238/322], p = 0.03). In multivariable LR, higher NCI EPE grades were strong independent predictors of pathologic EPE, irrespective of ERC use (NCI EPE grade 2 with ERC: odds ratio [OR] = 2.01, p = 0.04; without ERC: OR = 5.63, p<0.001, NCI EPE grade 3 with ERC: OR = 4.53, p<0.001; without ERC: OR = 5.22, p = 0.002).

CONCLUSION

ERC improves sensitivity, NPV, accuracy of EPE detection with mpMRI at different NCI EPE thresholds. NCI EPE grading system remains the stronger independent predictor of pathologic EPE regardless of ERC use.

Bicenter validation of a risk model for the preoperative prediction of extraprostatic extension of localized prostate cancer combining clinical and multiparametric MRI parameters

BACKGROUND

This study aimed to validate a previously published risk model (RM) which combines clinical and multiparametric MRI (mpMRI) parameters to predict extraprostatic extension (EPE) of prostate cancer (PC) prior to radical prostatectomy (RP).

MATERIALS AND METHODS

A previously published RM combining clinical with mpMRI parameters including European Society of Urogenital Radiology (ESUR) classification for EPE was retrospectively evaluated in a cohort of two urological university hospitals in Germany. Consecutive patients (n = 205, January 2015 -June 2021) with available preoperative MRI images, clinical information including PSA, prostate volume, ESUR classification for EPE, histopathological results of MRI-fusion biopsy and RP specimen were included. Validation was performed by receiver operating characteristic analysis and calibration plots. The RM's performance was compared to ESUR criteria.

RESULTS

Histopathological T3 stage was detected in 43% of the patients (n = 89); 45% at Essen and 42% at Düsseldorf. Discrimination performance between pT2 and pT3 of the RM in the entire cohort was AUC = 0.86 (AUC = 0.88 at site 1 and AUC = 0.85 at site 2). Calibration was good over the entire probability range. The discrimination performance of ESUR classification alone was comparable (AUC = 0.87).

CONCLUSIONS

The RM showed good discriminative performance to predict EPE for decision-making for RP as a patient-tailored risk stratification. However, when experienced MRI reading is available, standardized MRI reading with ESUR scoring is comparable regarding information outcome. A main limitation is the potentially limited transferability to other populations because of the high prevalence of EPE in our subgroups.

The association between perineural invasion in mpMRI-targeted and/or systematic prostate biopsy and adverse pathological outcomes in robot-assisted radical prostatectomy

INTRODUCTION AND OBJECTIVES

This study aims to investigate the relationship between perineural invasion (PNI) in targeted (TBx) and/or systematic (SBx) prostate needle biopsy and adverse pathological features of prostate cancer (PCa) in prostatectomy specimens.

MATERIALS AND METHODS

A total of 95 male patients who underwent transperineal TBx and/or concomitant SBx subsequently treated with robot-assisted radical prostatectomy for PCa between October 2015 and June 2020 were included. The performance of PNI as a classification test (sensitivity, specificity, positive and negative predictive values) and its correlation with clinically significant PCa, surgical margin positivity, extraprostatic extension, and seminal vesicle invasion in prostatectomy were computed.

RESULTS

The median age of the patients was 65 (60-70) years. TBx and concomitant SBx were performed in 78 (82.1%) patients, while 16 (16.8%) patients underwent SBx alone and one (1.1%) patient underwent TBx alone. The frequency of PNI in TBx and SBx was 17 (21.5%) and 32 (34.0%), respectively. The specificity/negative predictive values of PNI for surgical margin positivity, extraprostatic extension, and seminal vesicle invasion were 79.7/88.7%, 92.5/79.0%, and 83.3/96.8%, in TBx, and 71.1/87.1%, 80.7/74.2%, and 69.5/91.9%, in SBx, respectively. There was also a statistically significant correlation between PNI in biopsy and surgical margin positivity, extraprostatic extension, and seminal vesicle invasion in prostatectomy as well as the ISUP grade group and pT stage.

CONCLUSIONS

The absence of PNI in prostate needle biopsy may predict localized PCa with a pT stage ≤ 2c and negative surgical margins in contrast to its presence which appears to be an indicator of unfavorable factors in final pathology.

Preoperative detection of extraprostatic tumor extension in patients with primary prostate cancer utilizing [68Ga]Ga-PSMA-11 PET/MRI

OBJECTIVES

Radical prostatectomy (RP) is a common intervention in patients with localized prostate cancer (PCa), with nerve-sparing RP recommended to reduce adverse effects on patient quality of life. Accurate pre-operative detection of extraprostatic extension (EPE) remains challenging, often leading to the application of suboptimal treatment. The aim of this study was to enhance pre-operative EPE detection through multimodal data integration using explainable machine learning (ML).

METHODS

Patients with newly diagnosed PCa who underwent [68Ga]Ga-PSMA-11 PET/MRI and subsequent RP were recruited retrospectively from two time ranges for training, cross-validation, and independent validation. The presence of EPE was measured from post-surgical histopathology and predicted using ML and pre-operative parameters, including PET/MRI-derived features, blood-based markers, histology-derived parameters, and demographic parameters. ML models were subsequently compared with conventional PET/MRI-based image readings.

RESULTS

The study involved 107 patients, 59 (55%) of whom were affected by EPE according to postoperative findings for the initial training and cross-validation. The ML models demonstrated superior diagnostic performance over conventional PET/MRI image readings, with the explainable boosting machine model achieving an AUC of 0.88 (95% CI 0.87-0.89) during cross-validation and an AUC of 0.88 (95% CI 0.75-0.97) during independent validation. The ML approach integrating invasive features demonstrated better predictive capabilities for EPE compared to visual clinical read-outs (Cross-validation AUC 0.88 versus 0.71, p = 0.02).

CONCLUSION

ML based on routinely acquired clinical data can significantly improve the pre-operative detection of EPE in PCa patients, potentially enabling more accurate clinical staging and decision-making, thereby improving patient outcomes.

CRITICAL RELEVANCE STATEMENT

This study demonstrates that integrating multimodal data with machine learning significantly improves the pre-operative detection of extraprostatic extension in prostate cancer patients, outperforming conventional imaging methods and potentially leading to more accurate clinical staging and better treatment decisions.

KEY POINTS

Extraprostatic extension is an important indicator guiding treatment approaches. Current assessment of extraprostatic extension is difficult and lacks accuracy. Machine learning improves detection of extraprostatic extension using PSMA-PET/MRI and histopathology.

A comparative analysis of techniques for measuring tumor contact length in predicting extraprostatic extension

PURPOSE

This study aims to evaluate the diagnostic performance of curvilinear and linear measurement methods in different magnetic resonance imaging (MRI) sequences for detecting extraprostatic extension (EPE) in prostate cancer, and to evaluate the added value of apparent diffusion coefficient (ADC) in detecting EPE.

METHODS

A retrospective analysis was conducted on 84 patients who underwent multiparametric MRI (mp-MRI) prior to radical prostatectomy between January 2019 and February 2022. Tumor contact length (TCL) was assessed curvilinearly and linearly on T2-weighted imaging (T2WI), ADC maps, and dynamic contrast-enhanced (DCE) MRI by two radiologists. MRI-based EPE positivity was defined as a curvilinear or linear contact length of >15 mm. Statistical comparisons were conducted using chi-squared and independent samples t-tests, with interreader agreement evaluated using weighted κ statistics. Univariate and multivariate logistic regression identified independent predictors of EPE, and two prediction models were constructed. Diagnostic performance was assessed using receiver operator characteristic (ROC) curve analysis.

RESULTS

A total of 32 (38%) and 52 (62%) patients with EPE and non-EPE, respectively, were included in this study. Patients with EPE demonstrated significantly larger tumor sizes, lower ADC values, and lower ADC ratios than those without EPE (p < 0.001). The curvilinear and linear TCL measurements for each sequence exhibited statistically significant correlations with EPE for both readers, with strong interreader agreement. Curvilinear TCL (c-TCL) and linear TCL (l-TCL) on DCE-MRI showed higher area under the curve (AUC) values than the other measurements for EPE prediction (reader 1: 0.815 and 0.803, reader 2: 0.746 and 0.713, respectively). However, there was no statistically significant difference between c-TCL and l-TCL. Multivariable models with mean ADC value improved predictive performance. Model 2 (ADC, ISUP, and c-TCL on DCE images) surpassed model 1 (ADC and c-TCL on DCE images) with an AUC of 0.919 and 0.874, respectively.

CONCLUSION

DCE-MRI demonstrated superior performance in predicting EPE compared to other sequences. Linear and curvilinear measurements had comparable diagnostic performance. Being more practical and easier, radiologists may use l-TCL measurement in daily practice. The mean ADC value provided additional diagnostic value.

Predicting contralateral extraprostatic extension in unilateral high-risk prostate cancer: a multicentric external validation study

PURPOSE

Accurate prediction of extraprostatic extension (EPE) is crucial for decision-making in radical prostatectomy (RP), especially in nerve-sparing strategies. Martini et al. introduced a three-tier algorithm for predicting contralateral EPE in unilateral high-risk prostate cancer (PCa). The aim of the study is to externally validate this model in a multicentric European cohort of patients.

METHODS

The data from 208 unilateral high-risk PCa patients diagnosed through magnetic resonance imaging (MRI)-targeted and systematic biopsies, treated with RP between January 2016 and November 2021 at eight referral centers were collected. The evaluation of model performance involved measures such as discrimination (AUC), calibration, and decision-curve analysis (DCA) following TRIPOD guidelines. In addition, a comparison was made with two established multivariable logistic regression models predicting the risk of side specific EPE for assessment purposes.

RESULTS

Overall, 38%, 48%, and 14% of patients were categorized as low, intermediate, and high-risk groups according to Martini et al.'s model, respectively. At final pathology, EPE on the contralateral prostatic lobe occurred in 6.3%, 12%, and 34% of patients in the respective risk groups. The algorithm demonstrated acceptable discrimination (AUC 0.68), comparable to other multivariable logistic regression models (p = 0.3), adequate calibration and the highest net benefit in DCA. The limitations include the modest sample size, retrospective design, and lack of central revision.

CONCLUSION

Our findings endorse the algorithm's commendable performance, supporting its utility in guiding treatment decisions for unilateral high-risk PCa patients.

Investigation of radiomic features on MRI images to identify extraprostatic extension in prostate cancer

BACKGROUND AND OBJECTIVE

Detection of extraprostatic extension (EPE) preoperatively is of critical importance in the context of prostate cancer (PCa) management and outcomes. This study aimed to characterize the radiomic features of malignant prostate lesions based on multi-paramagnetic magnetic resonance imaging (mpMRI).

METHODS

We analyzed 20 patients who underwent mpMRI followed by radical prostatectomy. Two experienced radiologists manually segmented the 3D lesions using the T2-weighted (T2WI) and Apparent Diffusion Coefficient (ADC) imaging sequences. A total of 210 radiomic features were extracted from each lesion. We used the Recursive Feature Elimination with Cross-Validation to select key features. Using the selected radiomic features, we developed a Multilayer Perceptron (MLP) neural network to classify the EPE and non-EPE lesions. The pathology results were accepted as gold standard for EPE. We measured the performance of the classifier, calculating the area-under-curve (AUC), sensitivity, and specificity.

RESULTS

A total of 25 lesions were segmented, including 12 lesions with EPE and 13 lesions without EPE, based on the pathology reports. We selected 18 radiomic features (18/210). The MLP classifier using these features provided a good sensitivity (0.75), specificity (0.79), and AUC of 0.82, 95 % CL [0.59 - 0.96] in identifying the EPE lesions.

CONCLUSIONS

This pilot study presents 18 radiomic features derived from T2-weighted and ADC images and demonstrates their potential in the preoperative prediction of EPE in PCa using an MLP model.

3D-Reconstructed Contact Surface Area and Tumour Volume on Magnetic Resonance Imaging Improve the Prediction of Extraprostatic Extension of Prostate Cancer

This study is to determine whether the volume and contact surface area (CSA) of a tumour with an adjacent prostate capsule on MRI in a three-dimensional (3D) model that can predict side-specific extraprostatic extension (EPE) at radical prostatectomy (RP). Patients with localised prostate cancer (PCa) who underwent robot-assisted RP between July 2015 and March 2021 were included in this retrospective study. MRI-based 3D prostate models incorporating the PCa volume and location were reconstructed. The tumour volume and surface variables were extracted. For the prostate-to-tumour and tumour-to-prostate CSAs, the areas in which the distances were ≤ 1, ≤ 2, ≤ 3, ≤ 4, and ≤ 5 mm were defined, and their surface (cm2) were determined. Differences in prostate sides with and without pathological EPE were analysed. Multivariable logistic regression analysis to find independent predictors of EPE. Overall, 75/302 (25%) prostate sides showed pathological EPE. Prostate sides with EPE had higher cT-stage, higher PSA density, higher percentage of positive biopsy cores, higher biopsy Gleason scores, higher radiological tumour stage, larger tumour volumes, larger prostate CSA, and larger tumour CSA (all p < 0.001). Multivariable logistic regression analysis showed that the radiological tumour stage (p = 0.001), tumour volume (p < 0.001), prostate CSA (p < 0.001), and tumour CSA (p ≤ 0.001) were independent predictors of pathological EPE. A 3D reconstruction of tumour locations in the prostate improves prediction of extraprostatic extension. Tumours with a higher 3D-reconstructed volume, a higher surface area of tumour in contact with the prostate capsule, and higher surface area of prostate capsule in contact with the tumour are at increased risk of side-specific extraprostatic extension.