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Updated: Mar 11, 2026

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
Optimization of sparse phase encodings for variable repetition-delay turbo-spin echo (TSE) T1 measurements for
DongKyu Lee1, Sohyun Han1, HyungJoon Cho1
1Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea.
Abstract:
A variable repetition-delay (TR) spin echo sequence with repeated refocusing pulses, i.e., a variable TR turbo-spin echo (TSE), provides an attractive means of acquiring an accurate T1 map information that is free from gradient echo based artifacts such as magnetic field inhomogeneities particularly for ultra-high field (at 7T and above) preclinical applications. However, the applicability of multi-slice TSE sequences is often limited by signal distortion from T2 relaxation due to echo-train acquisitions for short T2 tissues, inter-slice cross talks and magnetization transfer (MT) from repetitive slice-selective 180° pulse, and extended scan times with multiple TR excitations. These TSE shortcomings are difficult to remedy for preclinical applications, where small sizes of target organs usually limit the slice-gap control with restricted parallel imaging capabilities. In this study, compressed-sensing-assisted turbo-spin echo (CS-TSE) acquisitions for variable TR T1 measurements at 7T preclinical scanner were implemented to reduce the echo-trains by sparse phase encodings. Following the sparse signal simulation and sampling scheme optimization, the measured T1 values from CS-TSE and TSE were compared for phantoms, ex vivo, and in vivo subjects. The phantom T1 values from CS-TSE and TSE were identical to those from the inversion recovery spin echo. For both ex vivo and in vivo multi-slice T1 mapping, the shortened echo-trains of CS-TSE relieved the T2 relaxation, reduced the inter-slice interferences of multi-slice acquisition, and made room for additional slice encodings while maintaining a shorter scan time than the conventional TSE at the expense of local image smoothness from CS regularizations.
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