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A relaxometry method that emphasizes practicality and availability

delete2022-07-25
delete3
PRE
AI
B
Bruno Madore *
M
Michael Jerosch‐Herold
J
Jr‐yuan George Chiou
C
Cheng‐Chieh Cheng
J
Jeffrey P. Guenette
G
Georgeta Mihai
DOI:10.1002/mrm.29394delete
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摘要

摘要

En 中文
Purpose Although many methods have been proposed to quantitatively map the main MRI parameters (e.g., T-1, T-2, C x M-0), these methods often involve special sequences not readily available on clinical scanners and/or may require long scan times. In contrast, the proposed method can readily run on most scanners, offer flexible tradeoffs between scan time and image quality, and map MRI parameters jointly to ensure spatial alignment. Methods The approach is based on the multi-shot spin-echo (SE) EPI sequence. The corresponding signal equation was derived and strategies for solving it were developed. As usual with multi-shot EPI, scan time can readily be traded-off against image quality by adjusting the echo train length. Validation was performed against reference relaxometry methods, in gel phantoms with varying concentrations of gadobutrol and gadoterate meglumine contrast agents. In vivo examples are further presented, from 3 neuroradiology patients. Results Bland-Altman analysis was performed: for T-2, as compared to 2D SE, bias was 0.29 ms and the 95% limits of agreement ranged from -1.15 to +1.73 ms. For T-1, compared to inversion-recovery SE (and MOLLI), bias was -20.2 ms (and -14.5 ms) and the limits of agreement ranged from -62.4 to +22.0 ms (and -53.8 to +24.9 ms). The mean relative T-1 error between the proposed method and each of the 2 reference methods was similar to that of the reference methods among themselves. Conclusion In the constellation of existing relaxometry methods, the proposed method is meant to stand out in terms of its practicality and availability.
Keyword:
parameter mapping
relaxometry
signal equation

期刊

Magnetic Resonance in Medicine 封面图
Magnetic Resonance in Medicine
IF:
3
论文数:
1.2W
被引数:
3.1W

机构

H
Harvard University
学者数:
26.5W
论文数: 22.0W
被引数: 28.7W
H
Harvard Medical School
学者数:
6.5W
论文数: 4.8W
被引数: 91
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