Deep Learning-Accelerated Magnetic Resonance Enterography for the Assessment of Crohn’s Disease

This is the authors' abstract. We don't add key points for this paper.

Purpose: To compare image quality (IQ) between deep learning (DL)-accelerated magnetic resonance enterography (MRE) and conventional MRE in patients with Crohn's disease.Materials and Methods: From August 2023 to July 2024, we retrospectively reviewed two patient cohorts who underwent MRE using either conventional or DL-accelerated sequences.Two radiologists independently evaluated the overall IQ, sharpness, motion artifacts, and artificial appearance for single-shot fast spin echo (SSFSE), diffusionweighted imaging (DWI), and precontrast and dynamic phases.Results: A total of 39 patients were included (median age, 31.0 years; conventional group, n = 15; DL group, n = 24).The mean overall IQ scores were 4.27 ± 0.70 (conventional coronal SSFSE) and 4.79 ± 0.41 (DL coronal SSFSE, p = 0.028), 3.00 ± 0.65 (conventional DWI) and 3.92 ± 0.65 (DL DWI, p = 0.001), and 3.60 ± 1.06 (conventional arterial-phase T1-weighted imaging [T1WI]) and 4.33 ± 0.70 (DL arterial-phase T1WI, p = 0.044).The DL group demonstrated higher overall IQ than the conventional group across all sequences.None of the examinations were classified as nondiagnostic (overall IQ <2) in either group.Across all phases, the DL group exhibited fewer motion artifacts but a more artificial appearance than the conventional group.Conclusion: DL-MRE achieved adequate IQ in patients with Crohn's disease while reducing scan time.