Reducing Contrast Agent Dose in Cardiovascular MR Angiography with Deep Learning.

ABSTRACT:

Background

Contrast-enhanced magnetic resonance angiography (MRA) is used to assess various cardiovascular conditions. However, gadolinium-based contrast agents (GBCAs) carry a risk of dose-related adverse effects.

Purpose

To develop a deep learning method to reduce GBCA dose by 80%.

Study type

Retrospective and prospective.

Population

A total of 1157 retrospective and 40 prospective congenital heart disease patients for training/validation and testing, respectively.

Field strength/sequence

A 1.5 T, T1-weighted three-dimensional (3D) gradient echo.

Assessment

A neural network was trained to enhance low-dose (LD) 3D MRA using retrospective synthetic data and tested with prospective LD data. Image quality for LD (LD-MRA), enhanced LD (ELD-MRA), and

SUBMITTER: Montalt-Tordera J 

PROVIDER: S-EPMC9681557 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature