MR fingerprinting for semisolid magnetization transfer and chemical exchange saturation transfer quantification.
MR fingerprinting for semisolid magnetization transfer and chemical exchange saturation transfer quantification.
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作者：
化学交换饱和转移（CEST）MRI将自己定位为一种有前途的对比机制，能够以足够的分辨率和放大的灵敏度提供分子信息。然而，由于各种混杂因素影响其对比加权图像解释和固有的长扫描时间，它尚未成为常规使用的临床技术。CEST MR指纹（MRF）是一种新的方法，用于解决这些挑战，允许同时定量的几个质子交换参数，使用快速采集方案。最近，开发了许多深度学习算法，以进一步提高CEST和半固态大分子磁化转移（MT）MRF的性能和速度。本文介绍了半固态MT/CEST-MRF的基本理论及其主要应用。然后详细介绍了用于MRF图像重建的监督和无监督学习方法，并描述了用于协议优化的基于人工智能（AI）的管道。最后，讨论了实际的考虑，并给出了未来的前景，伴随着基本的演示代码和数据。
Chemical exchange saturation transfer (CEST) MRI has positioned itself as a promising contrast mechanism, capable of providing molecular information at sufficient resolution and amplified sensitivity. However, it has not yet become a routinely employed clinical technique, due to a variety of confounding factors affecting its contrast-weighted image interpretation and the inherently long scan time. CEST MR fingerprinting (MRF), is a novel approach for addressing these challenges, allowing simultaneous quantitation of several proton exchange parameters using rapid acquisition schemes. Recently, a number of deep-learning algorithms were developed to further boost the performance and speed of CEST and semi-solid macro-molecule magnetization transfer (MT) MRF. This review article describes the fundamental theory behind semisolid MT/CEST-MRF and its main applications. It then details supervised and unsupervised learning approaches for MRF image reconstruction and describes artificial intelligent (AI)-based pipelines for protocol optimization. Finally, practical considerations are discussed, and future perspectives are given, accompanied by basic demonstration code and data.
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DOI：
10.1148/ryai.2019190021
发表时间：
2019-03-01
期刊：
RADIOLOGY-ARTIFICIAL INTELLIGENCE
影响因子：
--
作者：
Chokshi, Falgun H.;Flanders, Adam E.;Langlotz, Curtis P.
通讯作者：
Langlotz, Curtis P.
来自Z频谱拟合的2ppm（CEST@2ppm）处的CEST信号与脑肿瘤中的肌酸分布相关。
影响因子：
2.9
作者：
Cai, Kejia;Singh, Anup;Poptani, Harish;Li, Weiguo;Yang, Shaolin;Lu, Yang;Hariharan, Hari;Zhou, Xiaohong J.;Reddy, Ravinder
通讯作者：
Reddy, Ravinder
影响因子：
16.6
作者：
Cloos MA;Knoll F;Zhao T;Block KT;Bruno M;Wiggins GC;Sodickson DK
通讯作者：
Sodickson DK
影响因子：
3.3
作者：
Flassbeck, Sebastian;Schmidt, Simon;Schmitter, Sebastian
通讯作者：
Schmitter, Sebastian
影响因子：
5.7
作者：
Dortch, Richard D.;Moore, Jay;Li, Ke;Jankiewicz, Marcin;Gochberg, Daniel F.;Hirtle, Jane A.;Gore, John C.;Smith, Seth A.
通讯作者：
Smith, Seth A.