Multiparametric MRI <i>Versus</i> SelectMDx Accuracy in the Diagnosis of Clinically Significant PCa in Men Enrolled in Active Surveillance

Candiano

et al. 2021

Arch Ital Urol Androl

Self Cite

Introduction: The detection rate for clinically significant prostate cancer (csPCa) in men with mpMRI PI-RADS score 3 diagnosed by affiliated radiology centers vs radiological reference center was evaluated. Materials and methods: From January 2017 to December 2020, 950 men (median age 64 years) underwent mpMRI for abnormal PSA values (median 6.3 ng/ml). Among the 950 patients who underwent mpMRI 500 were evaluated by a reference center and 450 by outpatient radiological affiliated centers. All the mpMRI index lesions characterized by a PI-RADS 3 underwent targeted cores combined with extended prostate biopsy. Two radiologists of the radiological reference center revised all the mpMRI lesions 3. Results: Overall, 361/950 (38%) patients had a mpMRI lesion PI-RADS score 3: 120/500 cases (24%) vs 241/450 cases (53.5%) were diagnosed by reference vs affiliated radiological centers. The detection rate for cT1c csPCa was equal to 26.7% (35/120 cases) vs 16.6% (40/241 cases) in men with PI-RADS 3 lesions diagnosed in the reference vs the affiliated radiological centers (p < 0.05). Among the 241 PI-RADS score 3 lesions diagnosed by affiliated radiological centers 86/241 (35.7%) and 36/241 (15%) were downgraded (PI-RADS scores < 3) and upgraded (PI-RADS score 4) by the dedicated radiologists of the reference center. Conclusions: In our series, about 35% and 15% of PI-RADS score 3 lesions diagnosed by affiliated radiological centers were downgraded and upgraded when revised by experencied radiologists, therefore a second opinion is mandatory especially in men enrolled in active surveillance protocols in whom mpMRI is recommended to reduce the number of scheduled repeated prostate biopsies.

Section: Discussionmentioning

confidence: 93%

mpMRI PI-RADS score 3 lesions diagnosed by reference vs affiliated radiological centers: Our experience in 950 cases

Candiano

et al. 2021

Arch Ital Urol Androl

Self Cite

“…Magnetic resonance imaging (MRI) has evolved as a useful tool to improve the stratification and characterization of PCa candidates for AS ( 13 14 ). However, the nature of the MRI protocol and the schedule during the follow-up are still unclear.…”

Section: Introductionmentioning

confidence: 99%

Role of Multiparametric Prostate Magnetic Resonance Imaging before Confirmatory Biopsy in Assessing the Risk of Prostate Cancer Progression during Active Surveillance

et al. 2021

Objective: To evaluate the impact of multiparametric magnetic resonance imaging (mpMRI) before confirmatory prostate biopsy in patients under active surveillance (AS). Materials and Methods: This retrospective study included 170 patients with Gleason grade 6 prostate cancer initially enrolled in an AS program between 2011 and 2019. Prostate mpMRI was performed using a 1.5 tesla (T) magnetic resonance imaging system with a 16-channel phased-array body coil. The protocol included T1-weighted, T2-weighted, diffusion-weighted, and dynamic contrast-enhanced imaging sequences. Uroradiology reports generated by a specialist were based on prostate imagingreporting and data system (PI-RADS) version 2. Univariate and multivariate analyses were performed based on regression models. Results: The reclassification rate at confirmatory biopsy was higher in patients with suspicious lesions on mpMRI (PI-RADS score ≥ 3) (n = 47) than in patients with non-suspicious mpMRIs (n = 61) and who did not undergo mpMRIs (n = 62) (66%, 26.2%, and 24.2%, respectively; p < 0.001). On multivariate analysis, presence of a suspicious mpMRI finding (PI-RADS score ≥ 3) was associated (adjusted odds ratio: 4.72) with the risk of reclassification at confirmatory biopsy after adjusting for the main variables (age, prostate-specific antigen density, number of positive cores, number of previous biopsies, and clinical stage). Presence of a suspicious mpMRI finding (adjusted hazard ratio: 2.62) was also associated with the risk of progression to active treatment during the follow-up. Conclusion: Inclusion of mpMRI before the confirmatory biopsy is useful to stratify the risk of reclassification during the biopsy as well as to evaluate the risk of progression to active treatment during follow-up.

“…On the other hand, recent risk models have been reported to detect sPC using quantitative mpMRI, which may also help standardize mpMRI and bpMRI interpretation and image recognition using new statistical tools (machine learning, deep learning and neural network analysis) [31,32]. Risk models using genetic elements and molecular markers rather than image variables are also being reported [33]. Lastly, prospective and multi-centric risk models for sPC risk prediction including such new biochemical parameters, nancial aspects and novel MRI fusion biopsy data are expected to be established in the future.…”

Section: Discussionmentioning

confidence: 99%

A Risk Model for Detecting Clinically Significant Prostate Cancer Based on Clinical Parameters and the Prostate Imaging Reporting and Data System using Bi-parametric Magnetic Resonance Imaging in a Japanese Cohort.

Hayashida

Tanaka

Oka

et al. 2021

Preprint

Background:To selectively identify men with clinically significant prostate cancer (sPC) is pivotal issue. To develop a risk model for detecting sPC based on Prostate Imaging Reporting and Data System (PI-RADS) for bi-parametric magnetic resonance imaging (bpMRI) and clinical parameters in a Japanese cohort is expected beneficial.MethodsBetween January 2011 and December 2016, we retrospectively analyzed clinical parameters and bpMRI findings from 773 biopsy-naïve patients. A risk model was established using multivariate logistic regression analysis and was presented on a nomogram. Discrimination of the risk model was compared using the area under the receiver operating characteristic curve. Statistical differences between the predictive model and clinical parameters were analyzed using DeLong’s test.ResultssPC was detected in 343 men (44.3%). In the multivariate logistic regression analysis to predict sPC, age (P=0.002), log prostate-specific antigen (P<0.001), prostate volume (P<0.001) and PI-RADS scores (P<0.001) contributed significantly to the model. The risk model showed a higher area under the curve (0.862), than age (0.646), log prostate-specific antigen (0.652), prostate volume (0.697) and imaging scores (0.822). DeLong test results also showed that the novel risk model performed significantly better compared with those parameters (P<0.05).ConclusionsThis novel risk model performed significantly better compared with PI-RADS scores and other parameters alone, and is thus expected to provide benefits in making decisions to biopsy on suspicion of sPC.