Journal Article

Use of Multiparametric and Biparametric Magnetic Resonance Imaging in Bladder Cancer Staging: Prospective Observational Study and Analysis of Radiologist Learning Curve

Sica, M., De Cillis, S., Ortenzi, M., Desana, B., Piana, A., Fiori, C., Frattoni, P., Piramide, F., Cirillo, S., Porpiglia, F., Grosso, G., Ziani, N., Amparore, D., Manfredi, M., Ferrando, L., Checcucci, E., Fondello, G., Mesterca, G.

2024

Overview

Background: Nowadays, thanks to the introduction of the VI-RADS scoring system, mpMRI has shown promising results in pre-TURBT assessment of muscular invasiveness of BCa, even if its application in everyday practice is still limited. This might be due to a lack in the literature about the learning curve of radiologists and about the characteristics of the exam. With the aim to reduce scan time and patient discomfort while maintaining diagnostic accuracy, bpMRI has been introduced as a possible alternative to mpMRI in this group of patients. This study reports a single-center experience using mpMRI and the VI-RADS scoring system to differentiate NMIBC from MIBC. The primary aim of the study is to assess diagnostic accuracy of mpMRI using the VI-RADS scoring system. The secondary aim is to evaluate the learning curve of an experienced mpMRI radiologist. Additionally, we perform a retrospective assessment of the same group of patients evaluating only DWIs and T2-weighted images, as they underwent bpMRI, to compare the performance of mpMRI and bpMRI. Materials and Methods: From 11/2021 to 11/2023, patients with suspected newly diagnosed BCa were enrolled in this prospective study. All patients underwent mpMRI prior to TURBT in a highly specialized radiology center for MRI. According to VI-RADS, a cutoff of ≥3 was assumed to define MIBC. Histological TURBT reports were compared with preoperative VI-RADS scores to assess the accuracy of mpMRI in discriminating between NMIBC and MIBC. Furthermore, to assess the learning curve of the reading radiologist we analyzed the rate of patients correctly classified as MIBC at MRI. Finally, we evaluated the performance of a hypothetic biparametric MRI in classifying our cohort according to VI-RADS score and compared it with mpMRI performance by using DeLong’s test. Data analysis was performed using Jamovi software v.2.3 and R software v.4.2.1. Results: A total of 133 patients were enrolled. mpMRI showed sensitivity and specificity of 86% (95% confidence interval [CI]: 64–97) and 95% (95% CI: 89–98), respectively. The learning curve analysis of the reading radiologist showed that the rate of patients correctly classified as MIBC rapidly increases reaching its plateau after 40 cases. The hypothetic bpMRI showed a sensitivity of 76% (95% CI: 53–92) and a specificity of 93% (95% CI: 86–97), with no significant difference with mpMRI performance (p = 0.10). Conclusions: Our study confirms the effectiveness of MRI, particularly with the VI-RADS scoring system, in differentiating NMIBC from MIBC. The learning curve analysis underscores the importance of radiologist training in optimizing diagnostic accuracy. Future research should focus on enhancing the sensitivity of bpMRI and further validating these findings in larger and multicentric studies.

• Publisher: MDPI AG,MDPI
• Subject: Accuracy / Bladder cancer / Clinical medicine / Diagnosis / Ethics / Learning curves / Magnetic resonance imaging / Medical equipment / Methods / Morphology / Observational studies / Patients / Software / Tumor staging / Tumors / Urology / Variables