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

A preoperative scoring system for predicting the extraprostatic extension of prostate cancer following radical prostatectomy using magnetic resonance imaging and clinical factors

PURPOSE

We aimed to develop a preoperative prediction model for extraprostatic extension (EPE) in prostate cancer (PCa) patients following radical prostatectomy (RP) using MRI and clinical factors.

METHODS

This retrospective study enrolled 266 consecutive patients who underwent RP for PCa in 2022. These patients were divided into a training set (n = 187) and a test set (n = 79) through random assignment. The evaluated variables included age, prostate-specific antigen (PSA) level, prostate volume, PSA density (PSAD), index tumor length on MRI, Prostate Imaging-Reporting and Data System (PI-RADS) category, and EPE-related MRI features as defined by PI-RADS v2.1. A predictive model was constructed through multivariable logistic regression and subsequently translated into a scoring system. The performance of this scoring system in terms of prediction and calibration was assessed using C statistics and the Hosmer‒Lemeshow test.

RESULTS

Among patients in the training and test cohorts, 74 (39.6%) and 25 (31.6%), respectively, exhibited EPE after RP. The formulated scoring system incorporated the following factors: PSAD, index tumor length, bulging prostatic contour, and tumor-capsule interface > 10 mm as identified on MRI. This scoring system demonstrated strong prediction performance for EPE in both the training (C statistic, 0.87 [95% confidence interval, 0.86-0.87]) and test cohorts (C statistic, 0.85 [0.83-0.89]). Furthermore, the scoring system exhibited good calibration in both cohorts (P = 0.988 and 0.402, respectively).

CONCLUSION

Our scoring system, built upon MRI features defined by the PI-RADS, offers valuable assistance in assessing the likelihood of EPE after RP.

Value of a combined magnetic resonance imaging-based radiomics-clinical model for predicting extracapsular extension in prostate cancer: a preliminary study

Background

Extracapsular extension (ECE) of prostate cancer (PCa) is closely related to the treatment and prognosis of patients, and radiomics has been widely used in the study of PCa. This study aimed to evaluate the value of a combined model considering magnetic resonance imaging (MRI)-based radiomics and clinical parameters for predicting ECE in PCa.

Methods

A total of 392 PCa patients enrolled in this retrospective study were randomly divided into the training and validation sets at a ratio of 7:3. Radiologists assessed all lesions by Mehralivand grade. Radiomics features were extracted and selected to build a radiomics model, while clinical parameters were noted to construct the clinical model. The combined model was constructed by the integration of the radiomics model and clinical model. Meanwhile, the nomogram for predicting ECE was constructed based on the combined model. Then, the area under the receiver operating characteristic (ROC) curve (AUC), Delong test and the decision curve analysis (DCA) were used to compare the performance among the combined model, radiomics model, clinical model and Mehralivand grade.

Results

The AUC of the combined model in the validation set was comparable to that of the radiomics model [AUC =0.894 (95% confidence interval (CI): 0.837-0.950) vs. 0.835 (95% CI: 0.763-0.908), P>0.05]. In addition, the sensitivity of the combined model and radiomics model was 90.7% and 77.8%, with an accuracy of 81.4% and 76.3%, respectively. On the other hand, the AUCs of the Mehralivand grade of radiologists and clinical model were 0.774 (95% CI: 0.691-0.857) and 0.749 (95% CI: 0.658-0.840), respectively, in the validation set, which were lower than those in the combined model (P<0.05). The DCA implied that the combined model could obtain the maximum net clinical benefits compared with the clinical model, the Mehralivand grade and radiomics model.

Conclusions

The combined model has a satisfactory predictive value for ECE in PCa patients compared with the clinical model, Mehralivand grade of radiologists, and the radiomics model.

Imaging features of the PI-RADS for predicting extraprostatic extension of prostate cancer: systematic review and meta-analysis

OBJECTIVES

To systematically determine the diagnostic performance of each MRI feature of the PI-RADS for predicting extraprostatic extension (EPE) in prostate cancer.

METHODS

A literature search in the MEDLINE and EMBASE databases was conducted to identify original studies reporting the accuracy of each feature on MRI for the dichotomous diagnosis of EPE. The meta-analytic pooled diagnostic odds ratio (DOR), sensitivity, specificity, and their 95% confidence intervals (CIs) were obtained using a bivariate random-effects model.

RESULTS

After screening 1955 studies, 17 studies with a total of 3062 men were included. All six imaging features, i.e., bulging prostatic contour, irregular or spiculated margin, asymmetry or invasion of neurovascular bundle, obliteration of rectoprostatic angle, tumor-capsule interface > 10 mm, and breach of the capsule with evidence of direct tumor extension, were significantly associated with EPE. Breach of the capsule with direct tumor extension demonstrated the highest pooled DOR (15.6, 95% CI [7.7-31.5]) followed by tumor-capsule interface > 10 mm (10.5 [5.4-20.2]), asymmetry or invasion of neurovascular bundle (7.6 [3.8-15.2]), and obliteration of rectoprostatic angle (6.1 [3.8-9.8]). Irregular or spiculated margin showed the lowest pooled DOR (2.3 [1.3-4.2]). Breach of the capsule with direct tumor extension and tumor-capsule interface > 10 mm showed the highest pooled specificity (98.0% [96.2-99.0]) and sensitivity (86.3% [70.0-94.4]), respectively.

CONCLUSIONS

Among the six MRI features of prostate cancer, breach of the capsule with direct tumor extension and tumor-capsule interface > 10 mm were the most predictive of EPE with the highest specificity and sensitivity, respectively.

Findings on Diagnostic Magnetic Resonance Imaging Before Radiotherapy for Prostate Cancer

PURPOSE

Pre-treatment diagnostic magnetic resonance imaging (MRI) is used in prostate cancer detection and staging; however, little is known about its potential for radiotherapy treatment decision, or its prognostic value. We investigated the findings on pre-treatment MRI and its potential influence on treatment decisions, and its ability to predict biochemical recurrence in patients treated with radiotherapy.

METHODS

Files of patients treated by radiotherapy from 2014 to 2022 were searched for if they had had an MRI within 12 months before radiotherapy. Prostate Imaging Reporting & Data System (PI-RADS) score, index lesion diameter and the presence of organ confined disease or extra-prostatic extension were correlated with their Cancer of the Prostate Risk Assessment (CAPRA) score. Distribution of radiological and clinical features between groups were estimated using a chi-squared test.

RESULTS

Out of 1280 patients, 314 (24.5%) had an MRI. The distribution depended on the treatment received: 22.5% who received low-dose rate (LDR) brachytherapy as monotherapy, 24.0% treated with high-dose rate (HDR) boost and 32.0% treated with external-beam radiotherapy (EBRT) (P = .017). The CAPRA score significantly correlated with the PI-RADS score (r = .342, P < .01) and the diameter of the index lesion (r = .473, P < .01). A clinically significant number of 22% patients with CAPRA ≤ 3 disease presented with lesions ≥15 mm and were less likely to be treated with LDR monotherapy (P < .01). 39 patients had a recurrence, only 5 had an MRI: 4 had a lesion of ≥20 mm and 3 a seminal vesicle invasion.

CONCLUSION

More than twenty percent of patients with CAPRA ≤3 presented on MRI a ≥15 mm lesion. An MRI could potentially affect treatment choice, and although exploratory our results suggest an important prognostic potential.

Staging accuracy of MRI of the prostate with special reference to the influence of the time of last ejaculation on the detection of seminal vesicle invasion

AIM

To evaluate the Prostate Imaging Reporting and Data System, version 2.1 (PIRADS V2.1) criteria for seminal vesicle invasion (SVI) and examine whether the timing of last ejaculation influences the detection of SVI.

MATERIALS AND METHODS

The study population consisted of 68 patients (34 with SVI, 34 without SVI, matching groups by age and prostate volume) who underwent PIRADS V2.1-compliant multiparametric magnetic resonance imaging (MRI; 34 at 1.5 T, 34 at 3 T). Before the examination, the time of last ejaculation (38/68 ≤ 5 days, 30/68 > 5 days) was collected via a questionnaire. The five PIRADS V2.1 criteria for SVI with subsequent overall assessment were evaluated retrospectively by two independent examiners (examiner 1 with >10 years of experience, examiner 2 with 6 months of experience) in a single-blinded fashion for all patients using a questionnaire and a six-point scale (0 = no, 1 = very likely not, 2 = probably not, 3 = possible, 4 = probable, 5 = certain).

RESULTS

E1 achieved high specificity (100%) and positive predictive value (PPV; 100%) in the overall assessment, independent of the time of last ejaculation (sensitivity = 76.5%, negative predictive value [NPV] = 81%). The area under the curve (AUC) value was 0.882; for E2, it was 0.765. At ≤5 days, the AUC values of E1 and E2 differed significantly (0.867 versus 0.681, p=0.016), as did the diffusion restriction criterion (0.833 versus 0.681, p=0.028). E1 showed high AUC values independent of time. E2 had better values for all criteria at >5 days than at ≤5 days. There were no significant differences between the examiners in all observations at >5 days.

CONCLUSION

The PIRADS V2.1 criteria are well suited for an experienced examiner to detect SVI independent of time point. An inexperienced examiner will benefit from patients being abstinent >5 days prior to MRI.

Current Opinion on the Use of Magnetic Resonance Imaging in Staging Prostate Cancer: A Narrative Review

Accurate staging is critical for treatment planning and prognosis in men with prostate Cancer. Prostate magnetic imaging resonance (MRI) may aid in the staging evaluation by verifying organ-confined status, assessing the status of the pelvic lymph nodes, and establishing the local extent of the tumor in patients being considered for therapy. MRI has a high specificity for diagnosing extracapsular extension, and therefore may impact the decision to perform nerve sparing prostatectomy, along with seminal vesicle invasion and lymph node metastases; however, its sensitivity remains limited. Current guidelines vary significantly regarding endorsing the use of MRI for staging locoregional disease. For high-risk prostate cancer, most guidelines recommend cross sectional imaging, including MRI, to evaluate for more extensive disease that may merit change in radiation field, extended androgen deprivation therapy, or guiding surgical planning. Although MRI offers reasonable performance characteristics to evaluate bone metastases, guidelines continue to support the use of bone scintigraphy. Emerging imaging technologies, including coupling positron emission tomography (PET) with MRI, have the potential to improve the accuracy of prostate cancer staging with the use of novel radiotracers.

Magnetic resonance imaging improves the prediction of tumor staging in localized prostate cancer

OBJECTIVES

The aim of this study was to investigate 3 Tesla multiparametric magnetic resonance imaging (mpMRI)-based predictors for the pretherapeutic T staging of prostate cancer and their accuracy.

METHODS

Consecutive patients with 3 Tesla mpMRI, positive systematic and MR-targeted biopsy, and subsequent radical prostatectomy (RPE) between 01/2016 and 12/2017 were included. MRI parameters such as measurable extraprostatic extension (EPE) (≥ 3 mm), length of (pseudo)capsular contact (LCC), invasion of neurovascular bundle (NVBI), and/or seminal vesicles lesion contact (SVC) or infiltration (SVI) were assessed and correlated to clinical and histopathological results.

RESULTS

136 men were included. In 76 cases, a pT2 stage was determined, in 29 cases a pT3a, and in 31 a pT3b stage. The positive and negative predictive values (PPV, NPV) for the detection of T3 by measurable EPE on MRI was 98% (CI 0.88-1) and 81% (CI 0.72-0.87). No visible NVBI was found in pT2 patients (NPV 100%; CI 0.95-1). ROC analysis for T3a prediction with LCC (AUC 0.81) showed a sensitivity of 87% and a specificity of 62% at a threshold of 12.5 mm (J = 0.485) and 93% and 58% at 11 mm (Jmax = 0.512). All patients with pT3a had a LCC > 5 mm. In case of pT3b, 29/31 patients showed a SVC (PPV 76%, CI 0.61-0.87; NPV 98%, CI 0.93-0.99), and 23/31 patients showed a SVI (PPV 100%, CI 0.86-1; NPV 93%, CI 0.87-0.96). EPE (p < 0.01), LCC (p = 0.05), and SVC (p = 0.01) were independent predictors of pT3.

CONCLUSIONS

MRI-measurable EPE, LCC, and SVC were reliable, independent, preoperative predictors for a histopathological T3 stage. A LCC ≥ 11 mm indicated a pT3a stage, whereas a LCC < 5 mm excluded it. On MRI, visible SVI or even SVC of the PCa lesion was reliable preoperative predictors for a pT3b stage.

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.

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.