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February 25, 2026European Radiology Experimental0 citationsOpen Access

Comparison of respiratory-gated and breath‑hold accelerated T2-weighted sequences for liver MRI with deep learning reconstruction

HLHualing LiHangzhou Normal UniversityCHChenglin HuChinese Academy of Medical Sciences & Peking Union Medical CollegeQWQiuxia WangTongji Hospital

Key Points

  • This research aims to compare respiratory-gated and breath-hold T2-weighted sequences in liver MRI using deep learning reconstruction.
  • Used T2-weighted imaging (T2WI) sequences under respiratory-gated and breath-hold conditions.
  • Applied deep learning reconstruction techniques to enhance image quality.
  • Assessed the impact of respiratory curve traits on MRI quality.
  • Both imaging techniques resulted in satisfactory image quality.
  • Respiratory curve characteristics varied the quality of T2WI.
  • Respiratory-gated approaches were particularly beneficial for patients struggling with breath-holding.

Abstract

Respiratory-gated and breath-hold deep learning T2WI exhibited satisfactory image quality. Respiratory curve traits variably impact T2WI quality, guiding personalized imaging workflows.‌ Respiratory-gated deep learning-reconstructed T2WI benefits patients with breath-holding difficulties in liver MRI.

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Cite This Study

Li et al. (2026) studied this question.

synapsesocial.com/papers/699e9143f5123be5ed04e9e8https://doi.org/10.1186/s41747-026-00679-1
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