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May 6, 20261 citations

Clinical evaluation of deep learning accelerated 3D magnetic resonance cholangiopancreatography at 1.5 T and 3 T.

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IJIvan JamborRDRanjodh S. DhamiMPMadhangi Parameswaran

Key Points

  • This research aims to evaluate the effectiveness of deep learning in enhancing 3D magnetic resonance cholangiopancreatography (MRCP).
  • Sixty-four patients underwent 1.5 T MRCP scans and thirty-two patients underwent 3 T scans.
  • Two deep learning MRCP acquisitions were performed for each magnetic field strength with different scan techniques.
  • Three radiologists assessed the MRCP datasets based on image quality, noise, sharpness, and artifacts.
  • Deep learning MRCP showed better overall image quality scores compared to standard MRCP, with significant differences (p < 0.05).
  • Fewer artifacts were observed in deep learning MRCP acquisitions compared to standard techniques.
  • Variability in quality scores among radiologists indicates further validation is necessary for deep learning methods.

Abstract

OBJECTIVE: 3D (SDL), as compared to the standard 3D MRCP.. MATERIAL AND METHODS: Sixty-four and 32 patients underwent 1.5 T and 3 T MRCP scans, respectively. The standard 3D MRCP was obtained using a BH and NAV. Two SDL MRCP acquisitions for each magnetic field were performed with BH and scan times of 11-17 s, utilizing the SDL based acquisition and reconstruction technique. Three radiologists visually evaluated all MRCP datasets for 4 different features: overall image quality, image noise, image sharpness and artifacts. Differences were compared using the Wilcoxon matched-pairs signed rank and chi-squared tests. RESULTS: At both field strengths (1.5 T and 3 T) the proportion of overall image quality scores of 3 or higher (good, very good and excellent) and proportion of cases with reduced artifacts were better (p < 0.05) for both SDL MRCP acquisitions compared to the standard with NAV or BH. However, SDL MRCP was not superior to the standard MRCP technique for all evaluated feature categories and scoring varied between readers. CONCLUSION: SDL MRCP demonstrated improved image quality consistency and scan time, however, variations between radiologists in quality scores were present, underlying the need for future development and validation.

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Cite This Study

Jambor et al. (2026) studied this question.

synapsesocial.com/papers/69faa2e204f884e66b53383ahttps://doi.org/10.1016/j.ejrad.2026.112906
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Accelerated 3D MR cholangiopancreatography using a deep learning-based reconstruction in patients with cholelithiasis2024
  2. 2Accelerated MR Cholangiopancreatography with Deep Learning-based Reconstruction2024
  3. 33-dimensional gradient and spin-echo magnetic resonance cholangiopancreatography with deep learning reconstruction at 3T: Achieving superior image quality with reduced acquisition time2026 · 1 citations
  4. 4Super-resolution deep learning–enhanced 2D MRCP improves main pancreatic duct visualization compared with 3D MRCP2026
  5. 53D gadolinium-enhanced high-resolution near-isotropic pancreatic imaging at 3.0-T MR using deep-learning reconstruction2025 · 2 citations