The diagnostic accuracy of multiparametric MRI for detection and localization of prostate cancer depends on the affected region

Risk score model to automatically detect prostate cancer patients by integrating diagnostic parameters

Introduction

Prostate cancer (PCa) is one of the prevailing forms of cancer among men. At present, multiparametric MRI is the imaging method for localizing tumors and staging cancer. Radiomics plays a key role and hold potential for PCa detection, reducing the need for unnecessary biopsies, characterizing tumor aggression, and overseeing PCa recurrence post-treatment.

Methods

Furthermore, the integration of radiomics data with clinical and histopathological data can further enhance the understanding and management of PCa and decrease unnecessary transfers to specialized care for expensive and intrusive biopsies. Therefore, the aim of this study is to develop a risk model score to automatically detect PCa patients by integrating non-invasive diagnostic parameters (radiomics and Prostate-Specific Antigen levels) along with patient's age.

Results

The proposed approach was evaluated using a dataset of 189 PCa patients who underwent bi-parametric MRI from two centers. Elastic-Net Regularized Generalized Linear Model achieved 91% AUC to automatically detect PCa patients. The model risk score was also used to assess doubt cases of PCa at biopsy and then compared to bi-parametric PI-RADS v2.

Discussion

This study explored the relative utility of a well-developed risk model by combining radiomics, Prostate-Specific Antigen levels and age for objective and accurate PCa risk stratification and supporting the process of making clinical decisions during follow up.

Surgeon seniority and experience have no effect on CaP detection rates using MRI/TRUS fusion-guided targeted biopsies

OBJECTIVE

To determine (i) whether urologist seniority and experience are associated with prostate cancer (CaP) and clinically significant CaP (csCaP) detection rates using magnetic resonance imaging/ultrasound (MRI/US) fusion-guided targeted biopsies, taking multiparametric magnetic resonance imaging (mpMRI) as the reference standard, and (ii) if cancer detection rates (CDR) differ across regions of the prostate using Dickinson's 27-sector map, regardless of seniority.

METHODS

We retrospectively reviewed a consecutive series of patients with suspicion of prostate cancer who underwent targeted and systematic biopsies at 1 center by 1 of 7 urologists (2 seniors and 5 juniors) between January 1, 2016 and December 31, 2021, following positive mpMRI.

RESULTS

The cohort comprised 403 patients (454 lesions) aged 67.7±6.8. The combined (junior and senior) CDR was 57% for CaP and 28% for csCaP. There were no differences in CDR between junior and senior urologists for CaP (58% vs. 55%, P = 0.538) or csCaP (29% vs. 26%, P = 0.58). A general trend was observed for the learning curve, which indicated increasing CDR with urologist experience. Across the 27 sectors, combined CDR ranged between 39% and 99% for CaP and 1% to 67% for csCaP. When grouping anterior vs. posterior sectors, there were no differences in combined CDR of CaP (64% vs. 67%, P = 0.48) and csCaP (31% vs. 38%, P = 0.19) CONCLUSIONS: Urologist seniority is not associated with CDR, urologist experience tends to improve cancer detection, and CDR does not differ between the anterior and posterior regions of the prostate.