Susceptibility weighted imaging (SWI)
Abstract
Susceptibility differences between tissues can be utilized as a new type of contrast in MRI that is different from spin density, T1-, or T2-weighted imaging. Signals from substances with different magnetic susceptibilities compared to their neighboring tissue will become out of phase with these tissues at sufficiently long echo times (TEs). Thus, phase imaging offers a means of enhancing contrast in MRI. Specifically, the phase images themselves can provide excellent contrast between gray matter (GM) and white matter (WM), iron-laden tissues, venous blood vessels, and other tissues with susceptibilities that are different from the background tissue. Also, for the first time, projection phase images are shown to demonstrate tissue (vessel) continuity. In this work, the best approach for combining magnitude and phase images is discussed. The phase images are high-pass-filtered and then transformed to a special phase mask that varies in amplitude between zero and unity. This mask is multiplied a few times into the original magnitude image to create enhanced contrast between tissues with different susceptibilities. For this reason, this method is referred to as susceptibility-weighted imaging (SWI). Mathematical arguments are presented to determine the number of phase mask multiplications that should take place. Examples are given for enhancing GM/WM contrast and water/fat contrast, identifying brain iron, and visualizing veins in the brain.
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Certain MRI techniques, such as SWI, QSM, and the use of gadolinium-based contrast agents and USPIOs, can help deduce microglial activity or presence due to their tendency to uptake iron whilst in an activated state.
“Instead, certain MRI techniques, such as SWI, quantitative susceptibility mapping (QSM), and the use of gadolinium-based contrast agents and ultrasmall superparamagnetic iron oxide nanoparticles (USPIOs), can help deduce microglial activity or presence due to their tendency to uptake iron whilst in an activated state (49–51).”
From The role of microglia in multiple sclerosis: implications for treatment with Bruton’s tyrosine kinase inhibitors (2025) · cites this paper as [49]
Highly vascularized areas appear darker on SWI.
“SWI images show lower intensity in highly vascularized regions (Haacke et al., 2004)”
From Multi-modal characterization of rapid anterior hippocampal volume increase associated with aerobic exercise (2016) · cites this paper as Haacke et al., 2004
Cites
Brain magnetic resonance imaging with contrast dependent on blood oxygenation.
Ogawa, S., Lee, T. M., Kay, A. R., & Tank, D. W. (1990) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.87.24.9868 · Cited by 6,483 · see citing works
Oxygenation‐sensitive contrast in magnetic resonance image of rodent brain at high magnetic fields
Ogawa, S., Lee, T., Nayak, A. S., & Glynn, P. (1990) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910140108 · Cited by 2,269 · see citing works
Simple proton spectroscopic imaging.
Dixon, W. T. (1984) · Radiology · doi:10.1148/radiology.153.1.6089263 · Cited by 2,261 · see citing works
Brain magnetic resonance imaging with contrast-dependent oxygenation
Ogawa, S. (1990) · Medical Entomology and Zoology · Cited by 1,367 · see citing works
Small vessels in the human brain: MR venography with deoxyhemoglobin as an intrinsic contrast agent.
Reichenbach, J. R., Venkatesan, R., Schillinger, D. J., Kido, D. K., & Haacke, E. M. (1997) · Radiology · doi:10.1148/radiology.204.1.9205259 · Cited by 606 · see citing works
Self-citationOgawa, S., & Lee, T. (1990) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910160103 · Cited by 565 · see citing works
Measurement of Flow with NMR Imaging Using a Gradient Pulse and Phase Difference Technique
Bryant, D. J., Payne, J. A., Firmin, D. N., et al. (1984) · Journal of Computer Assisted Tomography · doi:10.1097/00004728-198408000-00002 · Cited by 555 · see citing works
Tong, K. A., Ashwal, S., Holshouser, B. A., et al. (2003) · Radiology · doi:10.1148/radiol.2272020176 · Cited by 429 · see citing works
Weisskoff, R. M., & Kiihne, S. (1992) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910240219 · Cited by 381 · see citing works
High‐resolution BOLD venographic imaging: a window into brain function
Reichenbach, J. R., & Haacke, E. M. (2001) · NMR in Biomedicine · doi:10.1002/nbm.722 · Cited by 248 · see citing works
Self-citationMR venography of multiple sclerosis.
Tan, I. L., van Schijndel, R. A., Pouwels, P. J. W., van Walderveen, M. A. A., Reichenbach, J. R., Manoliu, R. A., & Barkhof, F. (2000) · PubMed Central · Cited by 207 · see citing works
Self-citationOgg, R. J., Langston, J. W., Haacke, E. M., Steen, R. G., & Taylor, J. S. (1999) · Magnetic Resonance Imaging · doi:10.1016/s0730-725x(99)00017-x · Cited by 205 · see citing works
Self-citationHigh-Resolution MR Venography at 3.0 Tesla
Reichenbach, J. R., Barth, M., Haacke, E. M., Klarhöfer, M., Kaiser, W. A., & Moser, E. (2000) · Journal of Computer Assisted Tomography · doi:10.1097/00004728-200011000-00023 · Cited by 199 · see citing works
Self-citationVonken, E.-J. P. A., van Osch, M. J. P., Bakker, C. J. G., & Viergever, M. A. (1999) · Journal of Magnetic Resonance Imaging · doi:10.1002/(sici)1522-2586(199908)10:2 · Cited by 176 · see citing works
Lee, B. C., Vo, K., Kido, D. K., et al. (1999) · PubMed · Cited by 142 · see citing works
Abduljalil, A., Schmalbrock, P., Novak, V., & Chakeres, D. W. (2003) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.10362 · Cited by 128 · see citing works
Intracranial calcification on gradient-echo phase image: depiction of diamagnetic susceptibility.
Yamada, N., Imakita, S., Sakuma, T., & Takamiya, M. (1996) · Radiology · doi:10.1148/radiology.198.1.8539373 · Cited by 121 · see citing works
High-resolution venography of the brain using magnetic resonance imaging
Reichenbach, J. R., Essig, M., Haacke, E. M., Lee, B. C., Przetak, C., Kaiser, W. A., & Schad, L. R. (1998) · Magnetic Resonance Materials in Physics Biology and Medicine · doi:10.1007/bf02662513 · Cited by 110 · see citing works
Self-citationHaacke, E. M., Lai, S., Yablonskiy, D. A., & Lin, W. (1995) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.1850060204 · Cited by 109 · see citing works
Self-citationAutomated unwrapping of MR phase images applied to BOLD MR‐venography at 3 Tesla
Rauscher, A., Barth, M., Reichenbach, J. R., Stollberger, R., & Moser, E. (2003) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.10346 · Cited by 105 · see citing works
Self-citationHigh-resolution MR venography of cerebral arteriovenous malformations
Essig, M., Reichenbach, J. R., Schad, L. R., et al. (1999) · Magnetic Resonance Imaging · doi:10.1016/s0730-725x(99)00084-3 · Cited by 102 · see citing works
Self-citationHigh-resolution blood oxygen-level dependent MR venography (HRBV): a new technique
Reichenbach, J. R., Jonetz-Mentzel, L., Fitzek, C., et al. (2001) · Neuroradiology · doi:10.1007/s002340000503 · Cited by 99 · see citing works
Self-citationBarth, M., Nöebauer-Huhmann, I.-M., Reichenbach, J. R., et al. (2003) · Investigative Radiology · doi:10.1097/01.rli.0000069790.89435.e7 · Cited by 73 · see citing works
Self-citationLi, T., Kastrup, A., Moseley, M. E., & Glover, G. H. (2000) · Journal of Magnetic Resonance Imaging · doi:10.1002/1522-2586(200011)12:5 · Cited by 38 · see citing works
Schad, L. R. (2001) · NMR in Biomedicine · doi:10.1002/nbm.714 · Cited by 35 · see citing works
Comparison of functional MR-venography and EPI-BOLD fMRI at 1.5 t
Baudendistel, K. T., Reichenbach, J. R., Metzner, R., et al. (1998) · Magnetic Resonance Imaging · doi:10.1016/s0730-725x(98)00085-x · Cited by 21 · see citing works
Self-citationHochaufgelöste MR-Venographie zerebraler arteriovenöser Malformationen
Essig, M., Reichenbach, J. R., Schad, L. R., et al. (2001) · Der Radiologe · doi:10.1007/s001170050989 · Cited by 20 · see citing works
Self-citationSpatial Selectivity of BOLD Contrast: Effects In and Around Draining Veins
Lai, S., Glover, G. H., & Haacke, E. M. (2000) · Medical radiology · doi:10.1007/978-3-642-58716-0_20 · Cited by 14 · see citing works
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Multimodal population brain imaging in the UK Biobank prospective epidemiological study
Miller, K. L., Alfaro-Almagro, F., Bangerter, N. K., Thomas, D. L., Yacoub, E., Xu, J., Bartsch, A. J., Jbabdi, S., Sotiropoulos, S. N., Andersson, J. L. R., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4393 · Cited by 2,020 · see citing works
Cerebral microbleeds: a guide to detection and interpretation
Greenberg, S. M., Vernooij, M. W., Cordonnier, C., Viswanathan, A., Al-Shahi Salman, R., Warach, S., Launer, L. J., Van Buchem, M. A., & Breteler, M. M. (2009) · The Lancet Neurology · doi:10.1016/s1474-4422(09)70013-4 · Cited by 1,798 · see citing works
Sperling, R. A., Jack, C. R., Black, S. E., Frosch, M. P., Greenberg, S. M., Hyman, B. T., Scheltens, P., Carrillo, M. C., Thies, W., Bednar, M. M., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.05.2351 · Cited by 857 · see citing works
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Wilde, E. A., McCauley, S. R., Hunter, J. V., Bigler, E. D., Chu, Z., Wang, Z. J., Hanten, G. R., Troyanskaya, M., Yallampalli, R., Li, X., et al. (2008) · Neurology · doi:10.1212/01.wnl.0000305961.68029.54 · Cited by 525 · see citing works
Quantitative susceptibility mapping: current status and future directions
Haacke, E. M., Liu, S., Buch, S., Zheng, W., Wu, D., & Ye, Y. (2015) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2014.09.004 · Cited by 511 · see citing works
Self-citationMRI estimates of brain iron concentration in normal aging using quantitative susceptibility mapping
Bilgic, B., Pfefferbaum, A., Rohlfing, T., Sullivan, E. V., & Adalsteinsson, E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.08.077 · Cited by 499 · see citing works
Slow expansion of multiple sclerosis iron rim lesions: pathology and 7 T magnetic resonance imaging
Dal-Bianco, A., Grabner, G., Kronnerwetter, C., Weber, M., Höftberger, R., Berger, T., Auff, E., Leutmezer, F., Trattnig, S., Lassmann, H., et al. (2017) · Acta Neuropathologica · doi:10.1007/s00401-016-1636-z · Cited by 463 · see citing works
Deistung, A., Schäfer, A., Schweser, F., Biedermann, U., Turner, R., & Reichenbach, J. R. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.09.055 · Cited by 442 · see citing works
Self-citationCharidimou, A., Linn, J., Vernooij, M. W., Opherk, C., Akoudad, S., Baron, J.-C., Greenberg, S. M., Jäger, H. R., & Werring, D. J. (2015) · Brain · doi:10.1093/brain/awv162 · Cited by 385 · see citing works
Overview of quantitative susceptibility mapping
Deistung, A., Schweser, F., & Reichenbach, J. R. (2017) · NMR in Biomedicine · doi:10.1002/nbm.3569 · Cited by 338 · see citing works
Characterizing iron deposition in multiple sclerosis lesions using susceptibility weighted imaging
Haacke, E. M., Makki, M., Ge, Y., Maheshwari, M., Sehgal, V., Hu, J., Selvan, M., Wu, Z., Latif, Z., Xuan, Y., et al. (2009) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.21676 · Cited by 329 · see citing works
Self-citationWáng, Y. X. J., & Idée, J.-M. (2017) · Quantitative Imaging in Medicine and Surgery · doi:10.21037/qims.2017.02.09 · Cited by 247 · see citing works
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Bernasconi, A., Bernasconi, N., Bernhardt, B. C., & Schrader, D. (2011) · Nature Reviews Neurology · doi:10.1038/nrneurol.2010.199 · Cited by 233 · see citing works
Thomas, A. G., Dennis, A., Rawlings, N. B., Stagg, C. J., Matthews, L., Morris, M., Kolind, S. H., Foxley, S., Jenkinson, M., Nichols, T. E., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.090 · Cited by 152 · see citing works
“…2005; Barbier et al., 2001), thus it would obviously increase if vasculature increased, but a myelin change would not be predicted to change CBV. • SWI images show lower intensity in highly vascularized regions (Haacke et al., 2004), thus an decrease in SWI would support an increase in vasculature.”
BackgroundInfluentialAdvanced MRI techniques to improve our understanding of experience-induced neuroplasticity
Tardif, C. L., Gauthier, C. J., Steele, C. J., Bazin, P.-L., Schäfer, A., Schaefer, A., Turner, R., & Villringer, A. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.08.047 · Cited by 127 · see citing works
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Kirsch, W., McAuley, G., Holshouser, B., Petersen, F., Ayaz, M., Vinters, H. V., Dickson, C., Haacke, E. M., Britt III, W., Larsen, J., et al. (2009) · Journal of Alzheimer's Disease · doi:10.3233/jad-2009-1073 · Cited by 139 · see citing works
Self-citationNeurodegeneration with brain iron accumulation–clinical syndromes and neuroimaging
Schipper, H. M. (2012) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2011.06.016 · Cited by 141 · see citing works
Duyn, J. (2013) · Journal of Magnetic Resonance · doi:10.1016/j.jmr.2012.11.013 · Cited by 95 · see citing works
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Liem, M. K., Lesnik Oberstein, S. A. J., Versluis, M. J., Maat-Schieman, M. L. C., Haan, J., Webb, A. G., Ferrari, M. D., van Buchem, M. A., & van der Grond, J. (2012) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp-2012-302545 · Cited by 50 · see citing works
The future of functionally-related structural change assessment
Johansen-Berg, H. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.10.073 · Cited by 45 · see citing works
Magnetic Resonance Imaging of Amyloid Plaques in Transgenic Mouse Models of Alzheimers Disease
Chamberlain, R., M. Wengenack, T., F. Poduslo, J., Garwood, M., & R. Jack, C. (2011) · Current Medical Imaging Reviews · doi:10.2174/157340511794653522 · Cited by 26 · see citing works
“This is advantageous because we found that SWI can provide significantly greater plaque contrast than other techniques.”
MethodInfluentialSWI and phase imaging reveal intracranial calcifications in the P301L mouse model of human tauopathy
Ni, R., Zarb, Y., Kuhn, G. A., Müller, R., Yundung, Y., Nitsch, R. M., Kulic, L., Keller, A., & Klohs, J. (2020) · Magnetic Resonance Materials in Physics, Biology and Medicine · doi:10.1007/s10334-020-00855-3 · Cited by 24 · see citing works
Vermersch, P., Airas, L., Berger, T., Deisenhammer, F., Grigoriadis, N., Hartung, H.-P., Magyari, M., Popescu, V., Pozzilli, C., Pugliatti, M., et al. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1495529 · Cited by 21 · see citing works
“…such as SWI, quantitative susceptibility mapping (QSM), and the use of gadolinium-based contrast agents and ultrasmall superparamagnetic iron oxide nanoparticles (USPIOs), can help deduce microglial activity or presence due to their tendency to uptake iron whilst in an activated state (49 – 51).”
Cervical spinal cord susceptibility-weighted MRI at 7T: application to multiple sclerosis
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Evaluation of SWI in Children with Sickle Cell Disease
Winchell, A. M., Taylor, B. A., Song, R., Loeffler, R. B., Grundlehner, P., Hankins, J. S., Wang, W. C., Ogg, R. J., Hillenbrand, C. M., & Helton, K. J. (2014) · American Journal of Neuroradiology · doi:10.3174/ajnr.a3794 · Cited by 13 · see citing works
- Authors
- Haacke, E. M., Xu, Y., Cheng, Y. N., & Reichenbach, J. R.
- Affiliations
- Wayne State University (US)
- Friedrich Schiller University Jena (DE)
- Corresponding author
- Haacke, E. Mark
- Venue
- Magnetic Resonance in Medicine
- Publisher
- Wiley
- Published
- 2004-08-23
- Volume
- 52
- Issue
- 3
- Pages
- 612-618
- ISSN
- 0740-3194 (ISSN-L)
- 1522-2594
- OpenAlex
- W2146336531
- Cited by
- 1,582
- References
- 28
- Citations by year
- 2026: 31 · 2025: 46 · 2024: 49 · 2023: 57 · 2022: 74 · 2021: 72 · 2020: 76 · 2019: 75 · 2018: 84 · 2017: 87 · 2016: 98 · 2015: 104 · 2014: 113 · 2013: 112 · 2012: 97
- FWCI
- 14.53
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Magnetic Resonance in Medicine (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute on Aging (R01AG020948, AG 20948)
- National Heart, Lung, and Blood Institute (R01HL062983, HL62983)
- 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
- susceptibility-weighted imaging, phase imaging, magnetic susceptibility contrast, brain iron, phase mask, high-pass filtering
- MeSH terms
- Body Water, Brain, Cerebrovascular Circulation, Humans, Iron, Magnetic Resonance Imaging, Lipid Metabolism
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