Overview of quantitative susceptibility mapping
Abstract
Magnetic susceptibility describes the magnetizability of a material to an applied magnetic field and represents an important parameter in the field of MRI. With the recently introduced method of quantitative susceptibility mapping (QSM) and its conceptual extension to susceptibility tensor imaging (STI), the non-invasive assessment of this important physical quantity has become possible with MRI. Both methods solve the ill-posed inverse problem to determine the magnetic susceptibility from local magnetic fields. Whilst QSM allows the extraction of the spatial distribution of the bulk magnetic susceptibility from a single measurement, STI enables the quantification of magnetic susceptibility anisotropy, but requires multiple measurements with different orientations of the object relative to the main static magnetic field. In this review, we briefly recapitulate the fundamental theoretical foundation of QSM and STI, as well as computational strategies for the characterization of magnetic susceptibility with MRI phase data. In the second part, we provide an overview of current methodological and clinical applications of QSM with a focus on brain imaging. Copyright © 2016 John Wiley & Sons, Ltd.
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QSM has shown sensitivity to plaque-related iron accumulation and associated tissue changes.
“Quantitative susceptibility mapping (QSM), which measures magnetic susceptibility, has shown sensitivity to plaque‐related iron accumulation and associated tissue changes.”
From Diffusion MRI reveals amyloid plaque–associated cellular signatures through spatial transcriptomic integration (2026) · cites this paper as [33]
Quantitative susceptibility mapping (QSM) aims to noninvasively estimate the magnetic susceptibility of biological tissue.
“Quantitative susceptibility mapping (QSM) is a growing field of research in MRI, aiming to noninvasively estimate the magnetic susceptibility of biological tissue [145, 146].”
From An overview of deep learning in medical imaging focusing on MRI (2019) · cites this paper as [146]
Quantitative susceptibility mapping (QSM) aims to noninvasively estimate the magnetic susceptibility of biological tissue.
“Quantitative susceptibility mapping (QSM) is a growing field of research in MRI, aiming to noninvasively estimate the magnetic susceptibility of biological tissue [145, 146].”
From An overview of deep learning in medical imaging focusing on MRI (2019) · cites this paper as [145]
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- KlassenL MenonRS.BOLD signal phase and magnitude dependence on vessel geometry. Proceedings of the 13th Annual Meeting ISMRM Miami FL USA 2005; 496.
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An overview of deep learning in medical imaging focusing on MRI
Lundervold, A. S., & Lundervold, A. (2019) · Zeitschrift für Medizinische Physik · doi:10.1016/j.zemedi.2018.11.002 · Cited by 2,058 · see citing works
“Quantitative susceptibility mapping (QSM) is a growing field of research in MRI, aiming to noninvasively estimate the magnetic susceptibility of biological tissue [144,145].”
BackgroundAn overview of deep learning in medical imaging focusing on MRI
Lundervold, A. S., & Lundervold, A. (2018) · NORA - Norwegian Open Research Archives · Cited by 1,012 · see citing works
Babayan, A., Erbey, M., Kumral, D., Reinelt, J. D., Reiter, A. M. F., Röbbig, J., Schaare, H. L., Uhlig, M., Anwander, A., Bazin, P., et al. (2019) · Scientific Data · doi:10.1038/sdata.2018.308 · Cited by 361 · see citing works
Quantitative magnetic resonance imaging of brain anatomy and in vivo histology
Weiskopf, N., Edwards, L., Helms, G., Mohammadi, S., & Kirilina, E. P. (2021) · Nature Reviews Physics · doi:10.1038/s42254-021-00326-1 · Cited by 294 · see citing works
Ravanfar, P., Loi, S. M., Syeda, W. T., Rheenen, T. E. V., Bush, A. I., Desmond, P. M., Cropley, V., Lane, D. J. R., Opazo, C., Moffat, B. A., et al. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.618435 · Cited by 231 · see citing works
“Recently developed QSM techniques provide quantitative estimates of local magnetic susceptibility at a voxel-level (Deistung et al., 2017).”
BackgroundLiu, Z., Spincemaille, P., Yao, Y., Zhang, Y., & Wang, Y. (2017) · Magnetic Resonance in Medicine · doi:10.1002/mrm.26946 · Cited by 221 · see citing works
Iron, myelin, and the brain: neuroimaging meets neurobiology
Möller, H. E., Bossoni, L., Connor, J. R., Crichton, R. R., Does, M. D., Ward, R. J., Zecca, L., Zucca, F. A., & Ronen, I. (2019) · Trends in Neurosciences · doi:10.1016/j.tins.2019.03.009 · Cited by 207 · see citing works
Key clinical benefits of neuroimaging at 7 T
Trattnig, S., Springer, E., Bogner, W., Hangel, G. J., Strasser, B., Dymerska, B., Cardoso, P. L., & Robinson, S. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.11.031 · Cited by 183 · see citing works
“The implementation of automatic reconstruction on the scanner console could increase the applicability of SWI, or other methods using phase information, such as Quantitative Susceptibility Mapping (Deistung et al., 2016; Shmueli et al., 2009), in a clinical setting.”
Quantitative susceptibility mapping: Report from the 2016 reconstruction challenge
Langkammer, C., Schweser, F., Shmueli, K., Kames, C., Li, X., Guo, L., Milovic, C., Kim, J., Wei, H., Bredies, K., et al. (2017) · Magnetic Resonance in Medicine · doi:10.1002/mrm.26830 · Cited by 184 · see citing works
“x 1⁄4 argmin x jjxjjWTV þ m 2 jjMx xwelljj22; [4]”
BackgroundGong, N.-J., Dibb, R., Bulk, M., van der Weerd, L., & Liu, C. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.02.019 · Cited by 162 · see citing works
Biomarkers used in Alzheimer’s disease diagnosis, treatment, and prevention
Mahaman, Y. A. R., Embaye, K. S., Huang, F., Li, L., Zhu, F., Wang, J.-Z., Liu, R., Feng, J., & Wang, X. (2022) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101544 · Cited by 149 · see citing works
Advances in noninvasive myelin imaging
Heath, F. C., Hurley, S. A., Johansen‐Berg, H., & Sampaio‐Baptista, C. (2017) · Developmental Neurobiology · doi:10.1002/dneu.22552 · Cited by 130 · see citing works
“…properties, magnetic susceptibility (henceforth referred to as susceptibility) is the degree to which a tissue or material is magnetized by an external magnetic field, and thus describes how the magnetic environment of MR is perturbed by the material placed within it (Deistung et al., 2017).”
BackgroundMicrostructural imaging of human neocortex in vivo
Edwards, L., Kirilina, E. P., Mohammadi, S., & Weiskopf, N. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.02.055 · Cited by 122 · see citing works
Identification of Chronic Active Multiple Sclerosis Lesions on 3T MRI
Absinta, M., Sati, P., Fechner, A., Schindler, M. K., Nair, G., & Reich, D. S. (2018) · American Journal of Neuroradiology · doi:10.3174/ajnr.a5660 · Cited by 134 · see citing works
“One way to remove these dipolar fields is to apply an extra processing step called Quantitative Susceptibility Mapping (QSM), which computes the magnetic susceptibility of tissues by solving the field-to-source inversion problem using the dipole model.(31) However, the appearance of QSM images depends heavily on the c…”
MethodDeepQSM - using deep learning to solve the dipole inversion for quantitative susceptibility mapping
Bollmann, S., Bøtker-Rasmussen, K. G., Kristensen, M., Blendal, R. G., Østergaard, L. R., Plocharski, M., O’Brien, K., Langkammer, C., Janke, A. L., & Barth, M. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.03.060 · Cited by 131 · see citing works
“Finally, the inverse problem relating the measured field perturbation to the underlying magnetic susceptibility distribution is solved (Deistung et al., 2017; Schweser et al., 2016).”
BackgroundMethodInfluentialQuantifying iron content in magnetic resonance imaging
Ghassaban, K., Liu, S., Jiang, C., & Haacke, E. M. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.04.047 · Cited by 110 · see citing works
Chen, J., Gong, N., Chaim, K. T., Otaduy, M. C. G., & Liu, C. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118477 · Cited by 111 · see citing works
“Quantitative Susceptibility Mapping (QSM) is a magnetic resonance imaging (MRI) technique to non-invasively quantify tissue magnetic susceptibility (Bilgic et al., 2012; Deistung et al., 2017; Li et al., 2011; Liu et al., 2015b, 2015a; Wang and Liu, 2015).”
Imaging plus X: multimodal models of neurodegenerative disease
Oxtoby, N. P., & Alexander, D. C. (2017) · Current Opinion in Neurology · doi:10.1097/wco.0000000000000460 · Cited by 105 · see citing works
Quantitative Susceptibility Mapping: Basic Methods and Clinical Applications
Harada, T., Kudo, K., Fujima, N., Yoshikawa, M., Ikebe, Y., Sato, R., Shirai, T., Bito, Y., Uwano, I., & Miyata, M. (2022) · Radiographics · doi:10.1148/rg.210054 · Cited by 105 · see citing works
Wang, C., Martins-Bach, A. B., Alfaro‐Almagro, F., Douaud, G., Klein, J. C., Llera, A., Fiscone, C., Bowtell, R. W., Elliott, L. T., Smith, S. M., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01074-w · Cited by 107 · see citing works
Quantitative susceptibility mapping of brain iron in healthy aging and cognition
Madden, D. J., & Merenstein, J. L. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120401 · Cited by 95 · see citing works
Quantitative myelin imaging with MRI and PET: an overview of techniques and their validation status
van der Weijden, C. W. J., Biondetti, E., Gutmann, I. W., Dijkstra, H., McKerchar, R., Faria, D. D. P., de Vries, E. F. J., Meilof, J. F., Dierckx, R., Prévost, V., et al. (2022) · Brain · doi:10.1093/brain/awac436 · Cited by 95 · see citing works
“Although the full phase could be recovered using machine learning,(88) it is recommended that the scanner is explicitly instructed to save the unfiltered phase images for further processing into QSM.(82)”
BackgroundMethodInfluentialLi, X., Chen, L., Kutten, K. S., Ceritoglu, C., Li, Y., Kang, N., Hsu, J. T., Qiao, Y., Wei, H., Liu, C., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.02.016 · Cited by 91 · see citing works
SEPIA—Susceptibility mapping pipeline tool for phase images
Chan, K., & Marques, J. P. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117611 · Cited by 93 · see citing works
The impact of brain iron accumulation on cognition: A systematic review
Spence, H., McNeil, C. J., & Waiter, G. D. (2020) · PLoS ONE · doi:10.1371/journal.pone.0240697 · Cited by 91 · see citing works
“There is a rapid increase in iron accumulation (different depending on brain region) from birth up until around 20 years old, at which point the accumulation rate slows in some regions, reaching a plateau in middle age and increasing again after 60 years old [1, 7].”
BackgroundCerebral oxygen extraction fraction MRI : Techniques and applications
Jiang, D., & Lu, H. (2022) · Magnetic Resonance in Medicine · doi:10.1002/mrm.29272 · Cited by 86 · see citing works
Probing myelin content of the human brain with MRI: A review
Piredda, G. F., Hilbert, T., Thiran, J., & Kober, T. (2020) · Magnetic Resonance in Medicine · doi:10.1002/mrm.28509 · Cited by 84 · see citing works
Jung, W., Bollmann, S., & Lee, J. (2020) · NMR in Biomedicine · doi:10.1002/nbm.4292 · Cited by 83 · see citing works
Li, Z., Feng, R., Liu, Q., Feng, J., Lao, G., Zhang, M., Li, J., Zhang, Y., & Wei, H. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120148 · Cited by 84 · see citing works
Dimov, A., Liu, Z., Spincemaille, P., et al. (2017) · Magnetic Resonance in Medicine · doi:10.1002/mrm.26648 · Cited by 77 · see citing works
Kee, Y., Liu, Z., Zhou, L., et al. (2017) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2017.2749298 · Cited by 76 · see citing works
“QSM has been applied to a wide range of biomedical problems [1], [4]–[9] including: 1) demyelination, inflammation, and iron overload in multiple sclerosis [10]–[17],”
BackgroundChen, Y., Jakary, A., Avadiappan, S., Hess, C. P., & Lupo, J. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116389 · Cited by 68 · see citing works
Quantitative susceptibility mapping (QSM) and R2* in the human brain at 3 T
Feng, X., Deistung, A., & Reichenbach, J. R. (2017) · Zeitschrift für Medizinische Physik · doi:10.1016/j.zemedi.2017.05.003 · Cited by 65 · see citing works
Chen, L., Hua, J., Ross, C. A., Cai, S., van Zijl, P. C. M., & Li, X. (2018) · Journal of Neuroscience Research · doi:10.1002/jnr.24358 · Cited by 64 · see citing works
“The present results are consistent with the gain‐of function model for HD pathogenesis, i.e., loss of Htt expression in adulthood has been reported to cause decreased rather than increased iron (Dietrich et al., 2017).”
ResultVinayagamani, S., Sheelakumari, R., Sabarish, S., Senthilvelan, S., Ros, R., Thomas, B., & Kesavadas, C. (2020) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.27058 · Cited by 65 · see citing works
Tissue magnetic susceptibility mapping as a marker of tau pathology in Alzheimer's disease
O’Callaghan, J. M., Holmes, H. E., Powell, N. M., Wells, J. A., Ismail, O., Harrison, I. F., Siow, B. M., Johnson, R. A., Ahmed, Z., Fisher, A., et al. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.08.003 · Cited by 61 · see citing works
“Quantitative Susceptibility Mapping (QSM) (Wang and Liu, 2015; Shmueli et al., 2009; Haacke et al., 2015; Liu et al., 2014; Deistung et al., 2016), uses the phase of the MRI signal to calculate maps of the bulk magnetic susceptibility of tissue.”
The Role of Magnetic Resonance Imaging for the Diagnosis of Atypical Parkinsonism
Chougar, L., Pyatigorskaya, N., Degos, B., Grabli, D., & Lehéricy, S. (2020) · Frontiers in Neurology · doi:10.3389/fneur.2020.00665 · Cited by 54 · see citing works
“Iron Imaging Using R2 relaxometry (71, 72) or quantitative susceptibility mapping (QSM) (71, 73, 74), an increase in iron deposition was detected in the SN, with QSM showing greater accuracy than R2 relaxometry (71, 75, 76).”
MethodCerebral oxygen metabolism from MRI susceptibility
Biondetti, E., Cho, J., & Lee, H. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120189 · Cited by 55 · see citing works
Studying brain microstructure with magnetic susceptibility contrast at high-field
Duyn, J. H. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.02.046 · Cited by 51 · see citing works
Kang, J. J., Chen, Y., Xu, G. D., Bao, S., Wang, J., Ge, M., Shen, L., & Jia, Z. Z. (2022) · European Radiology · doi:10.1007/s00330-022-08790-8 · Cited by 50 · see citing works
Higher-order total variation approaches and generalisations
Bredies, K., & Höller, M. (2020) · Inverse Problems · doi:10.1088/1361-6420/ab8f80 · Cited by 49 · see citing works
“Due to the short scan time that is possible by this approach as well as its robustness, it might additionally contribute to advance QSM further towards clinical applications.”
BackgroundBrain Vascular Imaging Techniques
Laviña, B. (2016) · International Journal of Molecular Sciences · doi:10.3390/ijms18010070 · Cited by 48 · see citing works
“The fact that this technique does not provide quantitative measurements, which is an important limitation, is currently overcome by the advancement of new technology such as quantitative susceptibility mapping (QSM) [115] and susceptibility tensor imaging (STI) [116].”
BackgroundInfluentialQuantitative evaluation of brain iron accumulation in different stages of Parkinson's disease
Li, K. R., Avecillas-Chasin, J. M., Nguyen, T. D., Gillen, K. M., Dimov, A., Chang, E., Skudin, C., Kopell, B. H., Wang, Y., & Shtilbans, A. (2021) · Journal of Neuroimaging · doi:10.1111/jon.12957 · Cited by 47 · see citing works
Feng, X., Deistung, A., Dwyer, M. G., Hagemeier, J., Polak, P. E., Lebenberg, J., Frouin, F., Zivadinov, R., Reichenbach, J. R., & Schweser, F. (2017) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2017.02.002 · Cited by 44 · see citing works
Iron deposition quantification: Applications in the brain and liver
Yan, F., He, N., Lin, H., & Li, R. (2018) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.26161 · Cited by 43 · see citing works
Lancione, M., Tosetti, M., Donatelli, G., et al. (2017) · NMR in Biomedicine · doi:10.1002/nbm.3798 · Cited by 42 · see citing works
Yang, Y., Ye, C., Sun, J., Li, L., Lv, H., Gao, L., Fang, J., Ma, T., & Wu, T. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102715 · Cited by 39 · see citing works
“Given that QSM images exhibit better signal contrast on certain subcortical nuclei as compared to T1 weighted images (Deistung et al., 2017), ten subcortical regions of interest, including the substantia nigra (SN), the globus pallidus, the red nucleus, the caudate nucleus, and the putamen on both…”
BackgroundWang, Z., Luo, X., & Gao, C. (2016) · Translational Neurodegeneration · doi:10.1186/s40035-016-0064-2 · Cited by 41 · see citing works
Reversible reduction in brain myelin content upon marathon running
Ramos‐Cabrer, P., Cabrera‐Zubizarreta, A., Padró, D., Matute‐González, M., Rodríguez-Antigüedad, A., & Matute, C. (2025) · Nature Metabolism · doi:10.1038/s42255-025-01244-7 · Cited by 41 · see citing works
“Another confounding factor can be iron, the main source of paramagnetic susceptibility in the brain 68 .”
Prospective motion correction improves high‐resolution quantitative susceptibility mapping at 7T
Mattern, H., Sciarra, A., Lüsebrink, F., et al. (2018) · Magnetic Resonance in Medicine · doi:10.1002/mrm.27509 · Cited by 39 · see citing works
Learned Proximal Networks for Quantitative Susceptibility Mapping
Lai, K.-W., Aggarwal, M., van Zijl, P. C. M., Li, X., & Sulam, J. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-59713-9_13 · Cited by 40 · see citing works
“To suppress such streaking artifacts [10,20], different regularization strategies are often used, e.”
BackgroundMethodInfluentialImaging the Centromedian Thalamic Nucleus Using Quantitative Susceptibility Mapping
Li, J., Li, Y., Gutierrez, L., et al. (2020) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00447 · Cited by 38 · see citing works
“Recently developed QSM image reconstructed from the GRE-sequence image is an effective technique that takes advantage of differentiated iron concentration in different subcortical microstructures to identify their locations (Deistung et al., 2017).”
BackgroundQuantitative susceptibility mapping of the rat brain after traumatic brain injury
Chary, K., Nissi, M. J., Nykänen, O., Manninen, E., Rey, R. I., Shmueli, K., Sierra, A., & Gröhn, O. (2020) · NMR in Biomedicine · doi:10.1002/nbm.4438 · Cited by 38 · see citing works
QSMxT: Robust masking and artifact reduction for quantitative susceptibility mapping
Stewart, A. W., Robinson, S., O’Brien, K., Jin, J., Widhalm, G., Hangel, G. J., Walls, A. C., Goodwin, J., Eckstein, K., Tourell, M. C., et al. (2021) · Magnetic Resonance in Medicine · doi:10.1002/mrm.29048 · Cited by 39 · see citing works
Lancione, M., Donatelli, G., Cecchi, P., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.05.004 · Cited by 36 · see citing works
Matching ex vivo MRI With Iron Histology: Pearls and Pitfalls
De Barros, A., Arribarat, G., Combis, J., Chaynes, P., & Péran, P. (2019) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2019.00068 · Cited by 31 · see citing works
“Several algorithms and methods can be used, such as Laplacian-based methods, calculation of susceptibility using multiple orientation sampling (COSMOS), morphology-enabled dipole inversion (MEDI), and sophisticated harmonic artifact reduction on phase data (SHARP) method (Wang and Liu, 2015; Deistung et al., 2016).”
BackgroundMethodAhmed, M., Chen, J., Arani, A., Senjem, M. L., Cogswell, P. M., Jack, C. R., & Liu, C. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120357 · Cited by 36 · see citing works
Rapid two-step dipole inversion for susceptibility mapping with sparsity priors
Kames, C., Wiggermann, V., & Rauscher, A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.11.018 · Cited by 35 · see citing works
“Quantitative susceptibility mapping (QSM) is a novel reconstruction method that uses gradient echo 2 (GRE) phase data to estimate the underlying tissue magnetic susceptibility (Deistung et al., 2016; 3 Haacke et al., 2015; Li, 2001; Salomir et al., 2003; Schweser et al., 2016; Shmueli et al., 2009; Wang 4 and Liu, 201…”
The Potential of Myelin-Sensitive Imaging: Redefining Spatiotemporal Patterns of Myeloarchitecture
Paquola, C., & Hong, S. (2022) · Biological Psychiatry · doi:10.1016/j.biopsych.2022.08.031 · Cited by 32 · see citing works
The role of iron and myelin in orientation dependent R2* of white matter
Kor, D., Birkl, C. R., Ropele, S., et al. (2019) · NMR in Biomedicine · doi:10.1002/nbm.4092 · Cited by 33 · see citing works
Deistung, A., Jäschke, D., Draganova, R., et al. (2022) · Brain Communications · doi:10.1093/braincomms/fcab306 · Cited by 32 · see citing works
Cardiac quantitative susceptibility mapping (QSM) for heart chamber oxygenation
Wen, Y., Nguyen, T. D., Liu, Z., Spincemaille, P., Zhou, D., Dimov, A., Kee, Y., Deh, K., Kim, J. J., Weinsaft, J. W., et al. (2017) · Magnetic Resonance in Medicine · doi:10.1002/mrm.26808 · Cited by 32 · see citing works
Schiavi, S., Palombo, M., Zacà, D., Tazza, F., Lapucci, C., Castellan, L., Costagli, M., & Inglese, M. (2023) · Human Brain Mapping · doi:10.1002/hbm.26416 · Cited by 32 · see citing works
“Future deeper investigations to validate this hypothesis should be conducted by complementing the acquisition protocol with other MRI contrasts like iron-sensitive maps from quantitative susceptibility mapping (Deistung et al., 2017).”
Adams, L. C., Bressem, K. K., Böker, S. M., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-15860-1 · Cited by 31 · see citing works
Bollmann, S., Kristensen, M. H., Larsen, M. S., Olsen, M. V., Pedersen, M. J., Østergaard, L. R., O’Brien, K., Langkammer, C., Fazlollahi, A., & Barth, M. (2019) · Zeitschrift für Medizinische Physik · doi:10.1016/j.zemedi.2019.01.001 · Cited by 31 · see citing works
Taege, Y., Hagemeier, J., Bergsland, N., Dwyer, M. G., Weinstock‐Guttman, B., Zivadinov, R., & Schweser, F. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.11.011 · Cited by 30 · see citing works
“A pilot study in patients with multiple sclerosis and normal controls Yanis Taege a, Jesper Hagemeier a, Niels Bergsland a, Michael G. Dwyer a,b, Bianca Weinstock-Guttman c, Robert Zivadinov a,b, Ferdinand Schweser a,b,* a Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Bio…”
InfluentialIs Chelation Therapy a Potential Treatment for Parkinson’s Disease?
Ward, R. J., Dexter, D. T., Martín‐Bastida, A., & Crichton, R. R. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22073338 · Cited by 30 · see citing works
“This technique uses phase images solving the magnetic susceptibility inverse source problem, generating a thre -dimensional susceptibility distribution [16].”
MethodCallewaert, B., Jones, E. A. V., Himmelreich, U., & Gsell, W. (2021) · Diagnostics · doi:10.3390/diagnostics11060926 · Cited by 30 · see citing works
Survey of MRI Usefulness for the Clinical Assessment of Bone Microstructure
Soldati, E., Rossi, F., Vicente, J., Guenoun, D., Pithioux, M., Iotti, S., Malucelli, E., & Bendahan, D. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22052509 · Cited by 30 · see citing works
Alushaj, E., Handfield-Jones, N., Kuurstra, A. B., Morava, A., Menon, R. S., Owen, A. M., Sharma, M., KHAN, A. R., & MacDonald, P. A. (2024) · NeuroImage Clinical · doi:10.1016/j.nicl.2024.103577 · Cited by 28 · see citing works
“QSM correlated well with iron content in deep gray matter nuclei, using histological measures such as Perls staining (Deistung et al., 2013; Deistung et al., 2017).”
MethodCombining images and anatomical knowledge to improve automated vein segmentation in MRI
Ward, P. G. D., Ferris, N. J., Raniga, P., et al. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.10.049 · Cited by 28 · see citing works
Magnetic Resonance Iron Imaging in Amyotrophic Lateral Sclerosis
Bhattarai, A., Egan, G. F., Talman, P. S., Chua, P. M.-L., & Chen, Z. (2021) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.27530 · Cited by 28 · see citing works
“Quantitative Susceptibility Mapping QSM is a technique that calculates quantitative magnetic susceptibility values of tissues by deconvolving MRI phase signals with models of magnetic susceptibility.(53,54) QSM eliminates the blooming artifacts in SWI, and can accurately quantify and localize isotropic distributions o…”
BackgroundMethodQuantifying Remyelination Using χ-Separation in White Matter and Cortical Multiple Sclerosis Lesions
Müller, J., Lu, P., Cagol, A., Ruberte, E., Shin, H., Ocampo‐Pineda, M., Chen, X., Tsagkas, C., Baraković, M., Galbusera, R., et al. (2024) · Neurology · doi:10.1212/wnl.0000000000209604 · Cited by 30 · see citing works
“Susceptibility-based MRI measures fi 16 under an external magnetic eld.”
BackgroundHodneland, E., Hanson, E., Sævareid, O., et al. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007073 · Cited by 27 · see citing works
The 2016 QSM Challenge: Lessons learned and considerations for a future challenge design
Milovic, C., Cristián Tejos, N., Acosta‐Cabronero, J., et al. (2020) · Magnetic Resonance in Medicine · doi:10.1002/mrm.28185 · Cited by 27 · see citing works
Lorio, S., Sedlacik, J., So, P., et al. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118102 · Cited by 27 · see citing works
Wen, Y., Spincemaille, P., Nguyen, T. D., et al. (2021) · Magnetic Resonance in Medicine · doi:10.1002/mrm.28814 · Cited by 27 · see citing works
Brain MRI with Quantitative Susceptibility Mapping: Relationship to CT Attenuation Values
Oshima, S., Fushimi, Y., Okada, T., et al. (2020) · Radiology · doi:10.1148/radiol.2019182934 · Cited by 26 · see citing works
Bhattarai, A., Chen, Z., Ward, P. G. D., Talman, P. S., Mathers, S., Phan, T. G., Chapman, C., Howe, J. R., Lee, S., Lie, Y., et al. (2020) · Quantitative Imaging in Medicine and Surgery · doi:10.21037/qims-20-187 · Cited by 25 · see citing works
Quantitative susceptibility mapping in multiple sclerosis: A systematic review and meta-analysis
Voon, C. C., Wiltgen, T., Wiestler, B., Schlaeger, S., & Mühlau, M. (2024) · NeuroImage Clinical · doi:10.1016/j.nicl.2024.103598 · Cited by 27 · see citing works
“…microstructural damage and neuroinflammation in MS through estimating concentration changes in iron, involved in neurodegeneration, and myelin, the primary target of acute inflammatory activity in MS (Alexander et al., 2011; Deistung et al., 2017; Granziera et al., 2021; Reichenbach et al., 2015).”
BackgroundValue of Quantitative Susceptibility Mapping in Clinical Neuroradiology
Fushimi, Y., Nakajima, S., Sakata, A., Okuchi, S., Otani, S., & Nakamoto, Y. (2023) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.29010 · Cited by 24 · see citing works
Distinct regional vulnerability to Aβ and iron accumulation in post mortem AD brains
Yao, J., Li, Z., Zhou, Z., Bao, A., Wang, Z., Wei, H., & He, H. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.14188 · Cited by 24 · see citing works
“9,16 For instance, dia-magnetic sources like myelin and neurodegeneration-related protein accumulations exhibit negative susceptibility values, 17,18 potentially confoundingtheinterpretationofiron-relatedchanges.”
BackgroundYu, B., Shan, Y., & Ding, J. (2021) · Annals of Palliative Medicine · doi:10.21037/apm-21-825 · Cited by 25 · see citing works
“Susceptibility mapping In recent years, a method of quantifying the local magnetic susceptibility values from MR phase images, called quantitative susceptibility mapping (QSM), has led to plaque visualization as Aβ plaques and iron sediments can affect the magnetic susceptibility of tissues (47-49).”
MethodKiersnowski, O. C., Winston, G. P., Caciagli, L., et al. (2023) · Human Brain Mapping · doi:10.1002/hbm.26432 · Cited by 24 · see citing works
Accelerating quantitative susceptibility imaging acquisition using compressed sensing
Wang, N., Cofer, G. P., Anderson, R. J., Qi, Y. P., Liu, C., & Johnson, G. A. (2018) · Physics in Medicine and Biology · doi:10.1088/1361-6560/aaf15d · Cited by 24 · see citing works
Fang, J., Bao, L., Li, X., et al. (2018) · Magnetic Resonance in Medicine · doi:10.1002/mrm.27492 · Cited by 23 · see citing works
Lancione, M., Cencini, M., Costagli, M., et al. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2022.102989 · Cited by 22 · see citing works
Use of the NESMA Filter to Improve Myelin Water Fraction Mapping with Brain MRI
Bouhrara, M., Reiter, D. A., Maring, M. C., Bonny, J.-M., & Spencer, R. G. S. (2018) · Journal of Neuroimaging · doi:10.1111/jon.12537 · Cited by 23 · see citing works
“…72–74 diffusion imaging, 75–77 diffusion tensor imaging, 78–81 quantitative magnetization transfer, 82,83 quantitative susceptibility mapping, 84,85 perfusion mapping, 86,87 dynamic contrast enhanced measurements, 88 and other quantitative modalities in which successive images are obtained…”
Sato, R., Kudo, K., Udo, N., et al. (2022) · European Radiology · doi:10.1007/s00330-022-08547-3 · Cited by 19 · see citing works
Rapid submillimeter QSM and R2* mapping using interleaved multishot 3D‐EPI at 7 and 3 Tesla
Stirnberg, R., Deistung, A., Reichenbach, J. R., et al. (2024) · Magnetic Resonance in Medicine · doi:10.1002/mrm.30216 · Cited by 19 · see citing works
XSIM : A structural similarity index measure optimized for MRI QSM
Milovic, C., Cristián Tejos, N., Silva, J., Shmueli, K., & Pablo Irarrázaval, M. (2024) · Magnetic Resonance in Medicine · doi:10.1002/mrm.30271 · Cited by 19 · see citing works
“5 To infer susceptibility values from phase data, we solve an inverse problem that is equivalent to a regularized deconvolution, 6–8 where the voxel spread function is modeled as the magnetization field generated by a magnetic dipole.”
Kan, H., Uchida, Y., Ueki, Y., Arai, N., Tsubokura, S., Kunitomo, H., Kasai, H., Aoyama, K., Matsukawa, N., & Shibamoto, Y. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2022.102938 · Cited by 19 · see citing works
Quantitative MRI in Multiple Sclerosis: From Theory to Application
Tranfa, M., Pontillo, G., Petracca, M., Brunetti, A., Tedeschi, E., Palma, G., & Cocozza, S. (2022) · American Journal of Neuroradiology · doi:10.3174/ajnr.a7536 · Cited by 15 · see citing works
Öz, G., Cocozza, S., Henry, P.-G., Lenglet, C., Deistung, A., Faber, J., Schwarz, A., Timmann, D., van Dijk, K. V., Harding, I., et al. (2023) · Cerebellum · doi:10.1007/s12311-023-01572-y · Cited by 17 · see citing works
“More details on QSM processing can be found in recent reviews [45, 49].”
BackgroundHong, J.-H., Lee, J. Y., Dutta, A., Yoon, S. L., Cho, Y. U., Kim, K., Kang, K., Kim, H. W., Kim, D.-H., Park, J., et al. (2024) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2024.116446 · Cited by 19 · see citing works
Dušek, P., Ralf Mekle, A., Skowrońska, M., et al. (2019) · Movement Disorders · doi:10.1002/mds.27827 · Cited by 18 · see citing works
Nguyen, T. D., Wen, Y., Du, J., et al. (2020) · Magnetic Resonance in Medicine · doi:10.1002/mrm.28227 · Cited by 18 · see citing works
Quantitative susceptibility mapping in ischemic stroke patients after successful recanalization
Probst, J., Rohner, M. H., Zahn, M., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-95265-3 · Cited by 17 · see citing works
Kiersnowski, O. C., Karsa, A., Wastling, S. J., et al. (2022) · Magnetic Resonance in Medicine · doi:10.1002/mrm.29550 · Cited by 17 · see citing works
Fiscone, C., Rundo, L., Lugaresi, A., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-42914-4 · Cited by 17 · see citing works
“Quantitative Susceptibility Mapping (QSM) 6, 7 is a qMRI technique sensitive to differences between the magnetic responses of adjacent tissues, returning the magnetic susceptibility voxel-by-voxel.”
Background
- Authors
- Deistung, A., Schweser, F., & Reichenbach, J. R.
- Affiliations
- Jena University Hospital (DE)
- University at Buffalo, State University of New York (US)
- Corresponding author
- Deistung, Andreas
- Reichenbach, Jürgen R.
- Venue
- NMR in Biomedicine
- Publisher
- Wiley
- Published
- 2016-07-19
- Volume
- 30
- Issue
- 4
- ISSN
- 0952-3480 (ISSN-L)
- 1099-1492
- OpenAlex
- W2495874476
- Semantic Scholar
- ec5a3dc954839666a6a5e1885fc47bf93457e22e
- Cited by
- 338
- References
- 274
- Citations by year
- 2026: 31 · 2025: 43 · 2024: 35 · 2023: 40 · 2022: 45 · 2021: 35 · 2020: 23 · 2019: 26 · 2018: 33 · 2017: 22 · 2016: 3
- FWCI
- 4.33
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NMR in Biomedicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Physical Sciences › Physics and Astronomy › Nuclear and High Energy Physics › NMR spectroscopy and applications
- Keywords
- quantitative susceptibility mapping, magnetic susceptibility, inverse problems, anisotropy of magnetic susceptibility, neuroimaging
- MeSH terms
- Algorithms, Animals, Brain, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Sensitivity and Specificity, Reproducibility of Results, Diffusion Magnetic Resonance Imaging
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