15 years MR-encephalography |
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Author: | Hennig, Juergen1,2; Kiviniemi, Vesa3; Riemenschneider, Bruno4; |
Organizations: |
1Department of Radiology, Medical Physics, Faculty of Medicine, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany 2Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany 3Oulu Functional NeuroImaging Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland
4Department of Radiology, Center for Biomedical Imaging, New York University Grossman School of Medicine, New York, NY, USA
5Departments of Radiology and Paediatrics, Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada |
Format: | article |
Version: | published version |
Access: | open |
Online Access: | PDF Full Text (PDF, 7.7 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2021042111293 |
Language: | English |
Published: |
Springer Nature,
2021
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Publish Date: | 2021-04-21 |
Description: |
AbstractObjective: This review article gives an account of the development of the MR-encephalography (MREG) method, which started as a mere ‘Gedankenexperiment’ in 2005 and gradually developed into a method for ultrafast measurement of physiological activities in the brain. After going through different approaches covering k-space with radial, rosette, and concentric shell trajectories we have settled on a stack-of-spiral trajectory, which allows full brain coverage with (nominal) 3 mm isotropic resolution in 100 ms. The very high acceleration factor is facilitated by the near-isotropic k-space coverage, which allows high acceleration in all three spatial dimensions. Methods: The methodological section covers the basic sequence design as well as recent advances in image reconstruction including the targeted reconstruction, which allows real-time feedback applications, and—most recently—the time-domain principal component reconstruction (tPCR), which applies a principal component analysis of the acquired time domain data as a sparsifying transformation to improve reconstruction speed as well as quality. Applications: Although the BOLD-response is rather slow, the high speed acquisition of MREG allows separation of BOLD-effects from cardiac and breathing related pulsatility. The increased sensitivity enables direct detection of the dynamic variability of resting state networks as well as localization of single interictal events in epilepsy patients. A separate and highly intriguing application is aimed at the investigation of the glymphatic system by assessment of the spatiotemporal patterns of cardiac and breathing related pulsatility. Discussion: MREG has been developed to push the speed limits of fMRI. Compared to multiband-EPI this allows considerably faster acquisition at the cost of reduced image quality and spatial resolution. see all
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Series: |
Magnetic resonance materials in physics, biology and medicine |
ISSN: | 0968-5243 |
ISSN-E: | 1352-8661 |
ISSN-L: | 0968-5243 |
Volume: | 34 |
Issue: | 1; SI |
Pages: | 85 - 108 |
DOI: | 10.1007/s10334-020-00891-z |
OADOI: | https://oadoi.org/10.1007/s10334-020-00891-z |
Type of Publication: |
A2 Review article in a scientific journal |
Field of Science: |
217 Medical engineering |
Subjects: | |
Funding: |
This work was supported by ERC Advanced Grant European Research Council, Grant agreement 232908. Deutsche Forschungsgemeinschaft. Excellence Cluster BrainLinks-BrainTools, Grant EXC 1086, German Federal Ministry of Education and Research. Grant: 13N9208. German Federal Ministry of Education and Research, Grant 01EQ0605. Deutsche Forschungsgemeinschaft. Reinhard-Kosselleck-Grant He 1875/28-1. Jane ja Aatos Erkko Foundation Grant Academy of Finland Grants 275352, 314497. Open Access funding enabled and organized by Projekt DEAL. |
Academy of Finland Grant Number: |
275352 314497 |
Detailed Information: |
275352 (Academy of Finland Funding decision) 314497 (Academy of Finland Funding decision) |
Copyright information: |
© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
https://creativecommons.org/licenses/by/4.0/ |