在0.55T的结构材料中使用mt抑制激发实现精确的MRF T2。

IF 2.1 4区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Zhibo Zhu , Nam G. Lee , Krishna S. Nayak
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引用次数: 0

摘要

目的:开发0.55 T FISP-MRF方法,在结构化材料(如白质)中提供更准确的T2图谱。方法:采用非选择性低带宽激励策略,减少非共振MT效应。使用传统的单池模型模拟字典。使用非选择性方法估计的MRF T2图与使用常规板选择性方法的MRF T2图以及常规但缓慢的参考测量进行比较。结果:所提出的方法大大减少了白质中T2的低估,从~40 %到结论:使用非选择性低带宽激励大大降低了0.55T FISP-MRF中的MT效应,从而可以使用单一池模型。这对于低场强和结构材料(如白质)的磁流变尤为重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards accurate MRF T2 in structured material at 0.55T using MT-suppressed excitations

Purpose

To develop a 0.55 T FISP-MRF approach that provides more accurate T2 maps in structured materials (e.g. white matter).

Method

Non-selective low-bandwidth excitation strategies that reduce on-resonance MT effects were implemented. Dictionaries were simulated using a conventional single pool model. Estimated MRF T2 maps using the non-selective approach with 2 pulse durations were compared against MRF T2 maps using the conventional slab-selective approach, and against conventional but slow reference measurements.

Results

The proposed approach substantially reduces T2 underestimation in white matter from ∼40 % to <10 % without compromising precision.

Conclusion

The use of non-selective low-bandwidth excitations substantially reduces MT effects in 0.55T FISP-MRF, enabling use of a single pool model. This is particularly important for MRF at low field strengths and in structured materials such as white matter.
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来源期刊
Magnetic resonance imaging
Magnetic resonance imaging 医学-核医学
CiteScore
4.70
自引率
4.00%
发文量
194
审稿时长
83 days
期刊介绍: Magnetic Resonance Imaging (MRI) is the first international multidisciplinary journal encompassing physical, life, and clinical science investigations as they relate to the development and use of magnetic resonance imaging. MRI is dedicated to both basic research, technological innovation and applications, providing a single forum for communication among radiologists, physicists, chemists, biochemists, biologists, engineers, internists, pathologists, physiologists, computer scientists, and mathematicians.
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