Keywords: Diffusion Acquisition, AI/ML Image Reconstruction, single breath-hold DWI
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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