The Quantitative Assessment of Using Multiparametric MRI for Prediction of Extraprostatic Extension in Patients Undergoing Radical Prostatectomy: A Systematic Review and Meta-Analysis

PurposeTo investigate the diagnostic performance of using quantitative assessment with multiparametric MRI (mpMRI) for prediction of extraprostatic extension (EPE) in patients with prostate cancer (PCa).MethodsWe performed a computerized search of MEDLINE, Embase, Cochrane Library, Web of Science, and Google Scholar from inception until July 31, 2021. Summary estimates of sensitivity and specificity were pooled with the bivariate model, and quality assessment of included studies was performed with the Quality Assessment of Diagnostic Accuracy Studies-2. We plotted forest plots to graphically present the results. Multiple subgroup analyses and meta-regression were performed to explore the variate clinical settings and heterogeneity.ResultsA total of 23 studies with 3,931 participants were included. The pooled sensitivity and specificity for length of capsular contact (LCC) were 0.79 (95% CI 0.75–0.83) and 0.77 (95% CI 0.73–0.80), for apparent diffusion coefficient (ADC) were 0.71 (95% CI 0.50–0.86) and 0.71 (95% CI 059–0.81), for tumor size were 0.62 (95% CI 0.57–0.67) and 0.75 (95% CI 0.67–0.82), and for tumor volume were 0.77 (95% CI 0.68–0.84) and 0.72 (95% CI 0.56–0.83), respectively. Substantial heterogeneity was presented among included studies, and meta-regression showed that publication year (≤2017 vs. >2017) was the significant factor in studies using LCC as the quantitative assessment (P=0.02).ConclusionFour quantitative assessments of LCC, ADC, tumor size, and tumor volume showed moderate to high diagnostic performance of predicting EPE. However, the optimal cutoff threshold varied widely among studies and needs further investigation to establish.

Prostate Magnetic Resonance Imaging Analyses, Clinical Parameters, and Preoperative Nomograms in the Prediction of Extraprostatic Extension

Introduction: Proper planning of laparoscopic radical prostatectomy (RP) in patients with prostate cancer (PCa) is crucial to achieving good oncological results with the possibility of preserving potency and continence. Aim: The aim of this study was to identify the radiological and clinical parameters that can predict the risk of extraprostatic extension (EPE) for a specific site of the prostate. Predictive models and multiparametric magnetic resonance imaging (mpMRI) data from patients qualified for RP were compared. Material and methods: The study included 61 patients who underwent laparoscopic RP. mpMRI preceded transrectal systematic and cognitive fusion biopsy. Martini, Memorial Sloan-Kettering Cancer Center (MSKCC), and Partin Tables nomograms were used to assess the risk of EPE. The area under the curve (AUC) was calculated for the models and compared. Univariate and multivariate logistic regression analyses were used to determine the combination of variables that best predicted EPE risk based on final histopathology. Results: The combination of mpMRI indicating or suspecting EPE (odds ratio (OR) = 7.49 (2.31–24.27), p < 0.001) and PSA ≥ 20 ng/mL (OR = 12.06 (1.1–132.15), p = 0.04) best predicted the risk of EPE for a specific side of the prostate. For the prediction of ipsilateral EPE risk, the AUC for Martini’s nomogram vs. mpMRI was 0.73 (p < 0.001) vs. 0.63 (p = 0.005), respectively (p = 0.131). The assessment of a non-specific site of EPE by MSKCC vs. Partin Tables showed AUC values of 0.71 (p = 0.007) vs. 0.63 (p = 0.074), respectively (p = 0.211). Conclusions: The combined use of mpMRI, the results of the systematic and targeted biopsy, and prostate-specific antigen baseline can effectively predict ipsilateral EPE (pT3 stage).

Revisiting extraprostatic extension based on invasion depth and number for new algorithm for substaging of pT3a prostate cancer

Extraprostatic extension (EPE) is a factor in determining pT3a stage in prostate cancer. However, the only distinction in EPE is whether it is focal or non-focal, causing diagnostic and prognostic ambiguity. We substaged pT3a malignancies using classification of EPE to improve personalized prognostication. We evaluated 465 radical prostatectomy specimens with a digital image analyzer by measuring the number, radial distance and two-dimensional square area of the EPE. The most significant cut-off value was proposed as an algorithm for the pT3a substaging system to predict biochemical recurrence (BCR). A combination of the radial distance and the number of EPEs predicted BCR the most effectively. The optimal cut-off criteria were 0.75 mm and 2 mm in radial distance and multifocal EPE (hazard ratio: 2.526, C-index 0.656). The pT3a was subdivided into pT3a1, < 0.75 mm and any number of EPEs; pT3a2, 0.75–2 mm and one EPE; and pT3a3, > 2 mm and any number of EPEs or 0.75–2 mm and ≥ 2 EPEs. This combined tier was highly significant in the prediction of BCR-free survival. The combination of radial distance and number of EPEs could be used to subdivide pT3a prostate cancer and may aid in the prediction of BCR.