Prostate MRI cancer detection rate by deep learning-assisted image quality categorization: gas-induced susceptibility artifacts in diffusion-weighted imaging.

ABSTRACT:

Objectives

To evaluate the impact of gas-induced artifacts in diffusion-weighted imaging (DWI) on prostate MRI cancer detection rate (CDR).

Methods

This three-center retrospective study included 34,697 MRI examinations between 2017 and 2022. Seven radiologists categorized the degree of gas-induced artifacts of 1595 DWI series into optimal, mild, moderate, and severe. Then, a deep learning model categorizing artifact severity was developed to help identify series with gas-induced artifacts. After excluding series used for training the model, the model was applied to 12,594 DWI series, which were performed for patients without documented prostate cancer. Of these, radiologists reviewed the bottom 300 series predicted as poor image quality and recategorized them if necessary. C

SUBMITTER: Nakai H 

PROVIDER: S-EPMC12528626 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature