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September 17, 2025

Deep Learning Accelerated Single Breath-hold abdominal DWI with full liver and kidney coverage

Key Points

Single breath-hold DWI yielded more stable ADC estimations compared to FB DWI and RT DWI, with fewer motion artifacts.
DL-reconstructed images showed improved image quality and reduced slice discontinuities, enhancing diagnostic potential.
Evaluation included healthy volunteers using FB DWI, RT DWI, and breath-hold DWI using deep learning techniques for comparison.
These findings suggest that single breath-hold DWI could be a viable option for quicker and more reliable abdominal MRI scans.

Abstract

Motivation: Free-breathing (FB) abdominal DWI is prone to motion artifacts, leading to unstable and unreliable ADC map estimations. Goal(s): Implement and evaluate a single breath-hold DWI sequence utilizing deep learning (DL) reconstruction. Approach: Healthy volunteer underwent FB DWI, respiratory triggered (RT) DWI and single breath-hold DWI accelerated by deep learning reconstruction. Image quality and ADC histograms were compared. Results: DL-reconstructed single breath-hold DWI showed more reliable and stable ADC estimations, with fewer motion artifacts, image mismatches, and slice discontinuities compared to FB DWI and RT DWI. Impact: Single breath-hold DWI can shorten scanning time, reduce artifacts and improve ADC estimation, potentially improving diagnostic reliability in abdominal MRI.

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Cite This Study

Fu et al. (Tue,) studied this question.

synapsesocial.com/papers/68d45b1b31b076d99fa5d42b https://doi.org/https://doi.org/10.58530/2025/4814

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