Wellcome Centre for Integrative Neuroimaging, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom.
Magn Reson Med. 2018 Jul;80(1):171-180. doi: 10.1002/mrm.27020. Epub 2017 Nov 28.
In typical MRI protocols, time is spent acquiring a field map to calculate the shim settings for best image quality. We propose a fast template-based field map prediction method that yields near-optimal shims without measuring the field.
The template-based prediction method uses prior knowledge of the B distribution in the human brain, based on a large database of field maps acquired from different subjects, together with subject-specific structural information from a quick localizer scan. The shimming performance of using the template-based prediction is evaluated in comparison to a range of potential fast shimming methods.
Static B shimming based on predicted field maps performed almost as well as shimming based on individually measured field maps. In experimental evaluations at 7 T, the proposed approach yielded a residual field standard deviation in the brain of on average 59 Hz, compared with 50 Hz using measured field maps and 176 Hz using no subject-specific shim.
This work demonstrates that shimming based on predicted field maps is feasible. The field map prediction accuracy could potentially be further improved by generating the template from a subset of subjects, based on parameters such as head rotation and body mass index. Magn Reson Med 80:171-180, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
在典型的 MRI 协议中，需要花费时间获取磁场图以计算最佳图像质量的匀场设置。我们提出了一种快速基于模板的磁场图预测方法，该方法可以在不测量磁场的情况下生成接近最佳的匀场。
基于模板的预测方法利用了人脑中 B 分布的先验知识，基于从不同受试者获得的大量磁场图数据库，以及来自快速局部器扫描的受试者特定的结构信息。使用基于模板的预测进行匀场的性能与一系列潜在的快速匀场方法进行了评估。
基于预测磁场图的静态 B 匀场性能几乎与基于个体测量磁场图的匀场性能一样好。在 7T 的实验评估中，与使用测量磁场图的 50Hz 和不使用任何受试者特定匀场的 176Hz 相比，所提出的方法在大脑中产生的残余磁场标准偏差平均为 59Hz。
这项工作表明，基于预测磁场图的匀场是可行的。通过基于头旋转和体重指数等参数从受试者子集生成模板，可以进一步提高磁场图预测的准确性。磁共振医学 80:171-180, 2018。© 2017 作者。磁共振医学由 Wiley 期刊出版公司代表国际磁共振医学学会出版。这是在知识共享署名许可条款下的开放获取文章，允许在任何媒介中使用、分发和复制，前提是原始作品正确引用。
