Transverse prostate maximum sectional area can predict clinically significant prostate cancer in PI-RADS 3 lesions at multiparametric magnetic resonance imaging

Abstract

BackgroundTo evaluate multiparametric magnetic resonance imaging (mpMRI) parameters, such as TransPA (transverse prostate maximum sectional area), TransCGA (transverse central gland sectional area), TransPZA (transverse peripheral zone sectional area), and TransPAI (TransPZA/TransCGA ratio) in predicting prostate cancer (PCa) in prostate imaging reporting and data system (PI-RADS) 3 lesions.MethodsSensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), the area under the receiver operating characteristic curve (AUC), and the best cut-off, were calculated. Univariate and multivariate analyses were carried out to evaluate the capability to predict PCa.ResultsOut of 120 PI-RADS 3 lesions, 54 (45.0%) were PCa with 34 (28.3%) csPCas. Median TransPA, TransCGA, TransPZA and TransPAI were 15.4cm2, 9.1cm2, 5.5cm2 and 0.57, respectively. At multivariate analysis, location in the transition zone (OR=7.92, 95% CI: 2.70-23.29, P<0.001) and TransPA (OR=0.83, 95% CI: 0.76-0.92, P<0.001) were independent predictors of PCa. The TransPA (OR=0.90, 95% CI: 0.082-0.99, P=0.022) was an independent predictor of csPCa. The best cut-off of TransPA for csPCa was 18 (Sensitivity 88.2%, Specificity 37.2%, PPV 35.7%, NPV 88.9%). The discrimination (AUC) of the multivariate model was 0.627 (95% CI: 0.519-0.734, P<0.031).ConclusionsIn PI-RADS 3 lesions, the TransPA could be useful in selecting patients requiring biopsy.

An Apparent Diffusion Coefficient-Based Machine Learning Model Can Improve Prostate Cancer Detection in the Grey Area of the Prostate Imaging Reporting and Data System Category 3: A Single-Centre Experience

“…Prostate mpMRI examinations were performed on a 1.5T scanner (Signa HDxt; GE Healthcare, Chicago, IL, USA), using a pelvic phased-array surface coil combined with a disposable endorectal coil. The mpMRI acquisition protocol of the prostate gland and seminal vesicles included fast relaxation fast spin echo (FR-FSE) T2-weighted (T2w), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) sequences (scan parameters were reported in our previous study [ 15 ]. Apparent diffusion coefficient (ADC) parametric maps were obtained from DWI acquisitions at b = [50, 1000] .…”

“…This heterogeneity mainly affects the PI-RADS 3 category assessment, which represents an “equivocal” result and can hide a non-negligible probability of csPCa [ 14 ]. Proper clinical management of patients with a PI-RADS 3 lesion at the mpMRI represents an intriguing and sometimes distressing challenge for urologists, although it is significantly improved by the use of clinical parameters such as age, familiarity, digital rectal examination (DRE), PSA, PSA density, and recently introduced new tools such as transverse prostate maximum sectional area [ 15 ], which can be combined in predictive nomograms. In fact, European Urology Association (EAU) guidelines suggest a risk-adapted matrix table for biopsy management based on the utilization of PSA density (PSAD), which is considered a best predictor of csPCa.…”