Deep Learning HASTE for Upper Abdominal MRI: Improved Image Quality, Speed, and Energy Efficiency in a Prospective Study.

ABSTRACT: This prospective study aimed to perform a qualitative and quantitative comparison of deep learning (DL) and conventional T2-weighted Half-Fourier Acquisition Single-shot Turbo spin Echo (HASTE) sequences for 3T MRI acquisition of the upper abdomen. From January 2024 to April 2024, 166 patients (60 ± 14 years) scheduled for MRI of the upper abdomen were prospectively enrolled. Each patient underwent two MRI examinations: one using a conventional T2-weighted HASTE sequence, followed by a fast T2-weighted HASTE sequence reconstructed with DL. Image quality, anatomical structure visualization, and diagnostic performance were independently assessed by three readers using a 5-point Likert scale. Quantitative analysis included measurements of signal-to-noise ratio (SNR) and contrast-to-noise rati

SUBMITTER: Gotta J 

PROVIDER: S-EPMC12678876 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature