Accelerated phase-contrast magnetic resonance imaging with use of resolution enhancement generative adversarial neural network.

ABSTRACT:

Background

Cardiovascular magnetic resonance (CMR) phase contrast is used to quantify blood flow. We sought to develop a complex-difference reconstruction for inline super-resolution of phase-contrast flow (CRISPFlow) to accelerate phase-contrast imaging.

Methods

CRISPFlow was built on the super-resolution generative adversarial network. The model was trained and tested (4:1 ratio) using retrospectively identified phase-contrast images from 2020 patients (56 ± 16 years; 1131 men) referred for clinical 3T CMR at a single center from 2018 to 2023. For testing, ascending aortic flow images collected with 2.5 × 1.9 mm² resolution using generalized autocalibrating partially parallel acquisitions (GRAPPA) were used to synthesize images with 7.5 × 1.9 mm² reso

SUBMITTER: Morales MA 

PROVIDER: S-EPMC11758573 | biostudies-literature | 2025 Summer

REPOSITORIES: biostudies-literature