Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro-magnetic tissue properties study group

QSM Consensus Organization Committee; Berkin Bilgic; Mauro Costagli; Kwok-Shing Chan; Jeff Duyn; Christian Langkammer; Jongho Lee; Xu Li; Chunlei Liu; José P Marques; Carlos Milovic; Simon Daniel Robinson; Ferdinand Schweser; Karin Shmueli; Pascal Spincemaille; Sina Straub; Peter van Zijl; Yi Wang; ISMRM Electro-Magnetic Tissue Properties Study Group

doi:10.1002/mrm.30006

Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro-magnetic tissue properties study group

Magn Reson Med. 2024 May;91(5):1834-1862. doi: 10.1002/mrm.30006. Epub 2024 Jan 21.

Authors

QSM Consensus Organization Committee; Berkin Bilgic¹, Mauro Costagli^{2

3}, Kwok-Shing Chan^{1

4}, Jeff Duyn⁵, Christian Langkammer⁶, Jongho Lee⁷, Xu Li^{8

9}, Chunlei Liu^{10

11}, José P Marques⁴, Carlos Milovic¹², Simon Daniel Robinson^{13

14}, Ferdinand Schweser^{15

16}, Karin Shmueli¹⁷, Pascal Spincemaille¹⁸, Sina Straub¹⁹, Peter van Zijl^{8

9}, Yi Wang²⁰; ISMRM Electro-Magnetic Tissue Properties Study Group

Affiliations

¹ Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA.
² Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Sciences (DINOGMI), University of Genoa, Genoa, Italy.
³ Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy.
⁴ Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
⁵ Advanced MRI Section, NINDS, National Institutes of Health, Bethesda, Maryland, USA.
⁶ Department of Neurology, Medical University of Graz, Graz, Austria.
⁷ Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea.
⁸ Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
⁹ F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA.
¹⁰ Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA.
¹¹ Helen Wills Neuroscience Institute, University of California, Berkeley, California, USA.
¹² School of Electrical Engineering (EIE), Pontificia Universidad Catolica de Valparaiso, Valparaiso, Chile.
¹³ High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
¹⁴ Centre of Advanced Imaging, University of Queensland, Brisbane, Australia.
¹⁵ Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences at the University at Buffalo, Buffalo, New York, USA.
¹⁶ Center for Biomedical Imaging, Clinical and Translational Science Institute at the University at Buffalo, Buffalo, New York, USA.
¹⁷ Department of Medical Physics and Biomedical Engineering, University College London, London, UK.
¹⁸ MRI Research Institute, Department of Radiology, Weill Cornell Medicine, New York, New York, USA.
¹⁹ Department of Radiology, Mayo Clinic, Jacksonville, Florida, USA.
²⁰ MRI Research Institute, Departments of Radiology and Biomedical Engineering, Cornell University, New York, New York, USA.

PMID: 38247051
PMCID: PMC10950544 (available on 2025-05-01)
DOI: 10.1002/mrm.30006

Abstract

This article provides recommendations for implementing QSM for clinical brain research. It is a consensus of the International Society of Magnetic Resonance in Medicine, Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available have generated a need in the neuroimaging community for guidelines on implementation. This article outlines considerations and implementation recommendations for QSM data acquisition, processing, analysis, and publication. We recommend that data be acquired using a monopolar 3D multi-echo gradient echo (GRE) sequence and that phase images be saved and exported in Digital Imaging and Communications in Medicine (DICOM) format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background field removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields within the brain mask should be removed using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of the whole brain as a region of interest in the analysis. The minimum acquisition and processing details required when reporting QSM results are also provided. These recommendations should facilitate clinical QSM research and promote harmonized data acquisition, analysis, and reporting.

Keywords: ISMRM study group; clinical brain research; data acquisition; data analysis; magnetic resonance imaging; quantitative susceptibility mapping.

MeSH terms

Algorithms
Brain Mapping / methods
Brain* / diagnostic imaging
Brain* / metabolism
Consensus
Head
Image Processing, Computer-Assisted* / methods
Magnetic Resonance Imaging / methods

Abstract

MeSH terms

Grants and funding