Motion correction methods for MRS: experts' consensus recommendations

Author:

Andronesi Ovidiu C.1ORCID,Bhattacharyya Pallab K.2,Bogner Wolfgang3ORCID,Choi In‐Young4,Hess Aaron T.5ORCID,Lee Phil6,Meintjes Ernesta M.7ORCID,Tisdall M. Dylan8,Zaitsev Maxim910,van der Kouwe André1

Affiliation:

1. Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Harvard Medical School Boston Massachusetts US

2. Imaging Institute Cleveland Clinic Cleveland Ohio US

3. High Field MR Center, Department of Biomedical Imaging and Image‐guided Therapy Medical University Vienna Vienna Austria

4. Department of Neurology, Hoglund Biomedical Imaging Center University of Kansas Medical Center Kansas City Kansas US

5. University of Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine University of Oxford UK

6. Department of Radiology, Hoglund Biomedical Imaging Center University of Kansas Medical Center Kansas City Kansas US

7. Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences University of Cape Town Cape Town South Africa

8. Department of Radiology, Perelman School of Medicine University of Pennsylvania Philadelphia US

9. Department of Radiology, Medical Physics, Medical Center, Faculty of Medicine University of Freiburg Freiburg Germany

10. High Field Magnetic Resonance Center, Center for Medical Physics and Biomedical Engineering Medical University of Vienna Vienna Austria

Abstract

Long acquisition times due to intrinsically low signal‐to‐noise ratio and the need for highly homogeneous B0 field make MRS particularly susceptible to motion or scanner instability compared with MRI. Motion‐induced changes in both localization and shimming (ie B0 homogeneity) degrade MRS data quality. To mitigate the effects of motion three approaches can be employed: (1) subject immobilization, (2) retrospective correction, and (3) prospective real‐time correction using internal and/or external tracking methods. Prospective real‐time correction methods can simultaneously update localization and the B0 field to improve MRS data quality. While localization errors can be corrected with both internal (navigators) and external (optical camera, NMR probes) tracking methods, the B0 field correction requires internal navigator methods to measure the B0 field inside the imaged volume and the possibility to update the scanner shim hardware in real time. Internal and external tracking can rapidly update the MRS localization with submillimeter and subdegree precision, while scanner frequency and first‐order shims of scanner hardware can be updated by internal methods every sequence repetition. These approaches are most well developed for neuroimaging, for which rigid transformation is primarily applicable. Real‐time correction greatly improves the stability of MRS acquisition and quantification, as shown in clinical studies on subjects prone to motion, including children and patients with movement disorders, enabling robust measurement of metabolite signals including those with low concentrations, such as gamma‐aminobutyric acid and glutathione. Thus, motion correction is recommended for MRS users and calls for tighter integration and wider availability of such methods by MR scanner manufacturers.

Funder

Austrian Science Fund

BHF Centre of Research Excellence, Oxford

National Cancer Institute

National Institute of Child Health and Human Development

Publisher

Wiley

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