Keywords: Myocardium, Tissue Characterization, Data Acquisition, Image Reconstruction, Preclinical
Motivation: Routine multi-shot T2-weighted dark-blood fast spin echo (T2W DB-FSE) is hindered by susceptibility to respiratory motion and the requirement for breath-holding.
Goal(s): To develop a single-shot cardiac T2W-DB imaging technique with a short echo train to eliminate breath-holding.
Approach: We designed a single-shot DB-FSE sequence with a deep learning-based reconstruction model. Transfer learning was employed to pre-train the model on large cardiac MR datasets and fine-tune it on clinical DB-FSE data. Validation was performed with single-shot imaging in 20 healthy volunteers.
Results: The transfer learning strategy enhanced model performance with limited data. Single-shot T2W DB-FSE showed image quality comparable to conventional multi-shot imaging.
Impact: The proposed single-shot imaging overcome the challenge of conventional cardiac T2W DB-FSE. It has the potential for clinical application in the assessment of myocardium edema on patients having trouble with long breath-holding.
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