Roundtable: arguments in support of using multi-parametric prostate MRI protocol

Comparing and Combining Artificial Intelligence and Spectral/Statistical Approaches for Elevating Prostate Cancer Assessment in a Biparametric MRI: A Pilot Study

Background: Prostate cancer management optimally requires non-invasive, objective, quantitative, accurate evaluation of prostate tumors. The current research applies visual inspection and quantitative approaches, such as artificial intelligence (AI) based on deep learning (DL), to evaluate MRI. Recently, a different spectral/statistical approach has been used to successfully evaluate spatially registered biparametric MRIs for prostate cancer. This study aimed to further assess and improve the spectral/statistical approach through benchmarking and combination with AI. Methods: A zonal-aware self-supervised mesh network (Z-SSMNet) was applied to the same 42-patient cohort from previous spectral/statistical studies. Using the probability of clinical significance of prostate cancer (PCsPCa) and a detection map, the affiliated tumor volume, eccentricity was computed for each patient. Linear and logistic regression were applied to the International Society of Urological Pathology (ISUP) grade and PCsPCa, respectively. The R, p-value, and area under the curve (AUROC) from the Z-SSMNet output were computed. The Z-SSMNet output was combined with the spectral/statistical output for multiple-variate regression. Results: The R (p-value)-AUROC [95% confidence interval] from the Z-SSMNet algorithm relating ISUP to PCsPCa is 0.298 (0.06), 0.50 [0.08-1.0]; relating it to the average blob volume, it is 0.51 (0.0005), 0.37 [0.0-0.91]; relating it to total tumor volume, it is 0.36 (0.02), 0.50 [0.0-1.0]. The R (p-value)-AUROC computations showed a much poorer correlation for eccentricity derived from the Z-SSMNet detection map. Overall, DL/AI showed poorer performance relative to the spectral/statistical approaches from previous studies. Multi-variable regression fitted AI average blob size and SCR results at a level of R = 0.70 (0.000003), significantly higher than the results for the univariate regression fits for AI and spectral/statistical approaches alone. Conclusions: The spectral/statistical approaches performed well relative to Z-SSMNet. Combining Z-SSMNet with spectral/statistical approaches significantly enhanced tumor grade prediction, possibly providing an alternative to current prostate tumor assessment.

Interpretation of Prostate Magnetic Resonance Imaging Using Prostate Imaging and Data Reporting System Version 2.1: A Primer

Prostate magnetic resonance imaging (MRI) is increasingly being used to diagnose and stage prostate cancer. The Prostate Imaging and Data Reporting System (PI-RADS) version 2.1 is a consensus-based reporting system that provides a standardized and reproducible method for interpreting prostate MRI. This primer provides an overview of the PI-RADS system, focusing on its current role in clinical interpretation. It discusses the appropriate use of PI-RADS and how it should be applied by radiologists in clinical practice to assign and report PI-RADS assessments. We also discuss the changes from prior versions and published validation studies on PI-RADS accuracy and reproducibility.

Abbreviated MR Protocols in Prostate MRI

Prostate MRI is an integral part of the clinical work-up in biopsy-naïve patients with suspected prostate cancer, and its use has been increasing steadily over the last years. To further its general availability and the number of men benefitting from it and to reduce the costs associated with MR, several approaches have been developed to shorten examination times, e.g., by focusing on sequences that provide the most useful information, employing new technological achievements, or improving the workflow in the MR suite. This review highlights these approaches; discusses their implications, advantages, and disadvantages; and serves as a starting point whenever an abbreviated prostate MRI protocol is being considered for implementation in clinical routine.

[Clinical impact of abbreviated unenhanced prostate protocols in magnetic resonance imaging]

BACKGROUND

According to the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 multiparametric magnetic resonance imaging (mpMRI) with gadolinium-(Gd)-based contrast agents is the diagnostic standard of care in the detection of prostate cancer (PCa). Recent data suggest equivalent performance of biparametric MRI (bpMRI) and mpMRI in defined indications.

OBJECTIVES

Evaluation of the current role of abbreviated or unenhanced protocols in MRI of the prostate in various clinical settings.

MATERIALS AND METHODS

Evaluation of clinical trials, guidelines and expert opinions.

RESULTS

The use of dynamic contrast-enhanced (DCE) MRI sequences is associated with contrast agent-associated risks and has significant impact on the imaging procedure and costs. Arguments for and against the use of contrast agent in prostate protocols as well as equivalence from bpMRI and mpMRI are discussed.

CONCLUSIONS

Currently, bpMRI can only be performed if very good image quality is available and in the hands of a radiologist with extensive experience in reading prostate MRI. There is a need for prospective studies to qualify bpMRI as the diagnostic method for the primary diagnosis of PCa.

How Fast Can We Go: Abbreviated Prostate MR Protocols

PURPOSE OF REVIEW

Multiparametric MRI (mpMRI), composed of T2WI, DWI, and DCE sequences, is effective in identifying prostate cancer (PCa), but length and cost preclude its application as a PCa screening tool. Here we review abbreviated MRI protocols that shorten or omit conventional mpMRI components to reduce scan time and expense without forgoing diagnostic accuracy.

RECENT FINDINGS

The DCE sequence, which plays a limited diagnostic role in PI-RADS, is eliminated in variations of the biparametric MRI (bpMRI). T2WI, the lengthiest sequence, is truncated by only acquiring the axial plane or utilizing 3D acquisition with subsequent 2D reconstruction. DW-EPI_SMS further accelerates DWI acquisition. The fastest protocol described to date consists of just DW-EPI_SMS and axial-only 2D T2WI and runs less than 5 min. Abbreviated protocols can mitigate scan expense and increase scan access, allowing prostate MRI to become an efficient PCa screening tool.