Bias in deep learning-based image quality assessments of T2-weighted imaging in prostate MRI.

ABSTRACT:

Objectives

To determine whether deep learning (DL)-based image quality (IQ) assessment of T2-weighted images (T2WI) could be biased by the presence of clinically significant prostate cancer (csPCa).

Methods

In this three-center retrospective study, five abdominal radiologists categorized IQ of 2,105 transverse T2WI series into optimal, mild, moderate, and severe degradation. An IQ classification model was developed using 1,719 series (development set). The agreement between the model and radiologists was assessed using the remaining 386 series with a quadratic weighted kappa. The model was applied to 11,723 examinations that were not included in the development set and without documented prostate cancer at the time of MRI (patient age, 65.5 ± 8.3 years [mean ± standard devia

SUBMITTER: Nakai H 

PROVIDER: S-EPMC12713002 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature