Deep Learning-Based Interpretable AI for Prostate T2W MRI Quality Evaluation.

ABSTRACT:

Rationale and objectives

Prostate MRI quality is essential in guiding prostate biopsies. However, assessment of MRI quality is subjective with variation. Quality degradation sources exert varying impacts based on the sequence under consideration, such as T2W versus DWI. As a result, employing sequence-specific techniques for quality assessment could yield more advantageous outcomes. This study aims to develop an AI tool that offers a more consistent evaluation of T2W prostate MRI quality, efficiently identifying suboptimal scans while minimizing user bias.

Materials and methods

This retrospective study included 1046 patients from three cohorts (ProstateX [n = 347], All-comer in-house [n = 602], enriched bad-quality MRI in-house [n = 97]) scanned between January 2011 and May

SUBMITTER: Belue MJ 

PROVIDER: S-EPMC11015987 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature