Cervical spinal cord susceptibility-weighted MRI at 7T: application to multiple sclerosis
Open accessAbstract
BACKGROUND: Susceptibility-weighted imaging (SWI) has been extensively studied in the brain and in diseases of the central nervous system such as multiple sclerosis (MS) providing unique opportunities to visualize cerebral vasculature and disease-related pathology, including the central vein sign (CVS) and paramagnetic rim lesions (PRLs). However, similar studies evaluating SWI in the spinal cord of patients with MS remain severely limited. PURPOSE: Based on our previous findings of enlarged spinal vessels in MS compared to healthy controls (HCs), we developed high-field SWI acquisition and processing methods for the cervical spinal cord with application in people with MS (pwMS) and HCs. Here, we demonstrate the vascular variability between the two cohorts and unique MS lesion features in the cervical cord. METHODS: In this retrospective, exploratory pilot study conducted between March 2021 and March 2022, we scanned 12 HCs and 9 pwMS using an optimized non-contrast 2D T2*-weighted gradient echo sequence at 7 tesla. The overall appearance of the white and gray matter as well as tissue vasculature were compared between the two cohorts and areas of MS pathology in the patient group were assessed using both the magnitude and processed SWI images. RESULTS: We show improved visibility of vessels and more pronounced gray and white matter contrast in the MS group compared to HCs, hypointensities surrounding the cord in the MS cohort, and identify signal changes indicative of the CVS and paramagnetic rims in 66 % of pwMS with cervical spinal lesions. CONCLUSION: In this first study of SWI at 7T in the human spinal cord, SWI holds promise in advancing our understanding of disease processes in the cervical cord in MS.
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Technical demands in the acquisition process as well as the need for training of neuroradiologists to improve diagnostic certainty limits the availability of novel MRI markers at present.
“Furthermore, technical demands in the acquisition process as well as the need for training of neuroradiologists to improve diagnostic certainty limits the availability of these novel MRI markers at present.”
From Applying the 2024-revised McDonald criteria for multiple sclerosis using conventional diagnostic tools: a single-centre prospective cohort study in Germany (2026) · cites this paper as [43]
The Introduction and Discussion (Limitations and future directions; pages unavailable) describe technical challenges in spinal-cord SWI acquisition and say further imaging improvements are needed for clinical translation. Materials and Methods (Image analysis; page unavailable) says a trained neuroradiologist reviewed the scans, but the paper does not say that additional neuroradiologist training is needed to improve diagnostic certainty or that such training limits marker availability. (LLM, conf=0.85)
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Cites
Susceptibility weighted imaging (SWI)
Haacke, E. M., Xu, Y., Cheng, Y. N., & Reichenbach, J. R. (2004) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20198 · Cited by 1,582 · see citing works
Wattjes, M. P., Ciccarelli, O., Reich, D. S., Banwell, B., de Stefano, N., Enzinger, C., Fazekas, F., Filippi, M., Frederiksen, J., Gasperini, C., et al. (2021) · The Lancet Neurology · doi:10.1016/s1474-4422(21)00095-8 · Cited by 674 · see citing works
Assessment of lesions on magnetic resonance imaging in multiple sclerosis: practical guidelines
Filippi, M., Preziosa, P., Banwell, B., Barkhof, F., Ciccarelli, O., Stefano, N. D., Geurts, J. J. G., Paul, F., Reich, D. S., Toosy, A., et al. (2019) · Brain · doi:10.1093/brain/awz144 · Cited by 576 · see citing works
Cooperative, O. B. O. T. N., Sati, P., Oh, J., Constable, R. T., Evangelou, N., Guttmann, C. R. G., Henry, R. G., Klawiter, E. C., Mainero, C., Massacesi, L., et al. (2016) · Nature Reviews Neurology · doi:10.1038/nrneurol.2016.166 · Cited by 425 · see citing works
Susceptibility-Weighted MR Imaging: A Review of Clinical Applications in Children
Tong, K. A., Ashwal, S., Obenaus, A., Nickerson, J. P., Kido, D. K., & Haacke, E. M. (2007) · American Journal of Neuroradiology · doi:10.3174/ajnr.a0786 · Cited by 359 · see citing works
Tracking iron in multiple sclerosis: a combined imaging and histopathological study at 7 Tesla
Bagnato, F., Hametner, S., Yao, B., van Gelderen, P., Merkle, H., Cantor, F. K., Lassmann, H., & Duyn, J. H. (2011) · Brain · doi:10.1093/brain/awr278 · Cited by 351 · 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
THE HISTOLOGY OF DISSEMINATED SCLEROSIS.
(1916) · The Lancet · doi:10.1016/s0140-6736(01)14668-4 · Cited by 239 · see citing works
Long-term evolution of multiple sclerosis iron rim lesions in 7 T MRI
Dal‐Bianco, A., Grabner, G., Kronnerwetter, C., Weber, M., Kornek, B., Kasprian, G. J., Berger, T., Leutmezer, F., Rommer, P. S., Trattnig, S., et al. (2020) · Brain · doi:10.1093/brain/awaa436 · Cited by 230 · see citing works
Evaluation of the Central Vein Sign as a Diagnostic Imaging Biomarker in Multiple Sclerosis
Sinnecker, T., Clarke, M. A., Meier, D., Enzinger, C., Calabrese, M., Stefano, N. D., Pitiot, A., Giorgio, A., Schoonheim, M. M., Paul, F., et al. (2019) · JAMA Neurology · doi:10.1001/jamaneurol.2019.2478 · Cited by 216 · see citing works
Self-citationDeistung, A., Rauscher, A., Sedlacik, J., Stadler, J., Witoszynskyj, S., & Reichenbach, J. R. (2008) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21754 · Cited by 169 · see citing works
A Comparison of 3T and 7T in the Detection of Small Parenchymal Veins Within MS Lesions
Tallantyre, E. C., Morgan, P. S., Dixon, J. E., Al-Radaideh, A., Brookes, M. J., Evangelou, N., & Morris, P. G. (2009) · Investigative Radiology · doi:10.1097/rli.0b013e3181b4c144 · Cited by 164 · see citing works
Pathology, histochemistry and immunocytochemistry of lesions in acute multiple sclerosis
Adams, C. W. M., Poston, R. N., & Buk, S. J. (1989) · Journal of the Neurological Sciences · doi:10.1016/0022-510x(89)90144-5 · Cited by 163 · see citing works
Susceptibility weighted imaging: Clinical applications and future directions
Halefoğlu, A. M., & Yousem, D. M. (2018) · World Journal of Radiology · doi:10.4329/wjr.v10.i4.30 · Cited by 162 · see citing works
Vascular anatomy of the spinal cord
Santillán, A., Nacarino-Mejías, V., Greenberg, E. D., Riina, H. A., Gobin, Y. P., & Patsalides, A. T. (2011) · Journal of NeuroInterventional Surgery · doi:10.1136/neurintsurg-2011-010018 · Cited by 156 · see citing works
Incidence of multiple sclerosis misdiagnosis in referrals to two academic centers
Kaisey, M., Solomon, A. J., Luu, M., Giesser, B. S., & Sicotte, N. L. (2019) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2019.01.048 · Cited by 148 · see citing works
Value of 3T Susceptibility-Weighted Imaging in the Diagnosis of Multiple Sclerosis
Clarke, M. A., Pareto, D., Pessini, L. M., Arrambide, G., Alberich, M., Crescenzo, F., Cappelle, S., Tintoré, M., Sastre‐Garriga, J., Auger, C., et al. (2020) · American Journal of Neuroradiology · doi:10.3174/ajnr.a6547 · Cited by 130 · see citing works
Self-citationAdvances in spinal cord imaging in multiple sclerosis
Moccia, M., Ruggieri, S., Ianniello, A., Toosy, A., Pozzilli, C., & Ciccarelli, O. (2019) · Therapeutic Advances in Neurological Disorders · doi:10.1177/1756286419840593 · Cited by 102 · see citing works
Spinal Cord Neuronal Pathology in Multiple Sclerosis
Gilmore, C. P., DeLuca, G., Bö, L., Owens, T., Lowe, J., Esiri, M., & Evangelou, N. (2009) · Brain Pathology · doi:10.1111/j.1750-3639.2008.00228.x · Cited by 99 · see citing works
CSF–Venous Fistulas: Anatomy and Diagnostic Imaging
Kranz, P. G., Gray, L., Malinzak, M. D., Houk, J. L., Kim, D. K., & Amrhein, T. J. (2021) · American Journal of Roentgenology · doi:10.2214/ajr.21.26182 · Cited by 98 · see citing works
Paramagnetic rims are a promising diagnostic imaging biomarker in multiple sclerosis
Meaton, I., AlTokhis, A. I., Allen, C. M., Clarke, M. A., Sinnecker, T., Meier, D., Enzinger, C., Calabrese, M., Stefano, N. D., Pitiot, A., et al. (2022) · Multiple Sclerosis Journal · doi:10.1177/13524585221118677 · Cited by 93 · see citing works
Self-citationCastellaro, M., Tamanti, A., Pisani, A. I., Pizzini, F. B., Crescenzo, F., & Calabrese, M. (2020) · Diagnostics · doi:10.3390/diagnostics10121025 · Cited by 88 · see citing works
Trip, S. A. (2005) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.2005.073213 · Cited by 79 · see citing works
Vascular Anatomy of the Spinal Cord and Classification of Spinal Arteriovenous Malformations
Miyasaka, K., Asano, T., Ushikoshi, S., Hida, K., & Koyanagi, I. (2000) · Interventional Neuroradiology · doi:10.1177/15910199000060s131 · Cited by 69 · see citing works
Iron and Neurodegeneration in Multiple Sclerosis
Khalil, M., Teunissen, C. E., & Langkammer, C. (2011) · Multiple Sclerosis International · doi:10.1155/2011/606807 · Cited by 65 · see citing works
Magnetic resonance imaging of the cervical spinal cord in multiple sclerosis at 7T
Dula, A. N., Pawate, S., Dortch, R. D., Barry, R. L., George‐Durrett, K., Lyttle, B. D., Dethrage, L. M., Gore, J. C., & Smith, S. A. (2015) · Multiple Sclerosis Journal · doi:10.1177/1352458515591070 · Cited by 60 · see citing works
Self-citationMultiple sclerosis lesions affect intrinsic functional connectivity of the spinal cord
Conrad, B. N., Barry, R. L., Rogers, B. P., Maki, S., Mishra, A., Thukral, S., Sriram, S., Bhatia, A., Pawate, S., Gore, J. C., et al. (2018) · Brain · doi:10.1093/brain/awy083 · Cited by 58 · see citing works
Self-citationSamaraweera, A. P. R., Clarke, M. A., Whitehead, A., Falah, Y., Driver, I. D., Dineen, R. A., Morgan, P. S., & Evangelou, N. (2016) · Journal of Neuroimaging · doi:10.1111/jon.12367 · Cited by 55 · see citing works
Self-citationRapid, high-resolution quantitative magnetization transfer MRI of the human spinal cord
Smith, A. K., Dortch, R. D., Dethrage, L. M., & Smith, S. A. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.03.005 · Cited by 54 · see citing works
Self-citationIntradural spinal vein enlargement in craniospinal hypotension.
Burtis, M. T., Ulmer, J. L., Miller, G. A., Barboli, A. C., Koss, S. A., & Brown, W. D. (2005) · PubMed Central · Cited by 49 · see citing works
Bellon, R. J., & Ozgur, H. T. (2000) · Neuroimaging · doi:10.1007/978-1-4612-1152-5_24 · Cited by 37 · see citing works
The Histology of Disseminated Sclerosis
Dawson, J. W. (1916) · Europe PMC (PubMed Central) · Cited by 37 · see citing works
Advanced spinal cord MRI in multiple sclerosis: Current techniques and future directions
Combes, A. J. E., Clarke, M. A., O’Grady, K. P., Schilling, K. G., & Smith, S. A. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2022.103244 · Cited by 32 · see citing works
Self-citationJensen-Kondering, U., Larsen, N., Huhndorf, M., Jansen, O., Lüddecke, R., Stürner, K., & Salehi Ravesh, M. (2022) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2022.07.013 · Cited by 10 · see citing works
Anan, R. A., EL-Adalany, M. A., Belal, T. M. I., & El-Mogy, S. (2020) · The Egyptian Journal of Radiology and Nuclear Medicine · doi:10.1186/s43055-020-00185-3 · Cited by 10 · see citing works
Progress towards a diagnostic biomarker for MS: Central vein sign
Solomon, A. J. (2020) · Multiple Sclerosis Journal · doi:10.1177/1352458520907910 · Cited by 8 · see citing works
Anatomy, Back, Spinal Cord Arteries
Kaiser, J. T., & Lugo-Pico, J. G. (2019) · StatPearls · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 3
- Jenkinson Mark. 2003. “ Fast, Automated,N-Dimensional Phase-Unwrapping Algorithm.” Magnetic Resonance in Medicine 49(1): 193– 97. 12509838
- Jenkinson Mark, Beckmann Christian F., Behrens Timothy E. J., Woolrich Mark W., and Smith Stephen M.. 2012. “ FSL.” NeuroImage 62(2): 782– 90. 21979382
- Witt Atlee, Kirkland Bonner, Reynolds Bryson, Conrad Benjamin N., and Smith Seth A.. 2019. “ MRI Analysis of the Anterior Vein in Multiple Sclerosis Spinal Cord.” in International Society for Magnetic Resonance in Medicine Annual Conference. Montreal, QC, Canada.
Cited by
Sorted by citations
Chronic active lesions in multiple sclerosis: classification, terminology, and clinical significance
Dal‐Bianco, A., Oh, J., Sati, P., & Absinta, M. (2024) · Therapeutic Advances in Neurological Disorders · doi:10.1177/17562864241306684 · Cited by 61 · see citing works
Keegan, B. M., Absinta, M., Cohen‐Adad, J., Flanagan, E. P., Henry, R. G., Klawiter, E. C., Kolind, S., Krieger, S. C., Laule, C., Lincoln, J. A., et al. (2024) · Brain Communications · doi:10.1093/braincomms/fcae395 · Cited by 22 · see citing works
Self-citationHarrison, D. M., Sati, P., Klawiter, E. C., Narayanan, S., Bagnato, F. R., Beck, E., Barker, P. B., Calvi, A., Cagol, A., Donadieu, M., et al. (2024) · Brain Communications · doi:10.1093/braincomms/fcae359 · Cited by 21 · see citing works
Self-citationSaltarelli, G., Cerbo, G. D., Innocenzi, A., Felici, C. D., Splendiani, A., & Cesare, E. D. (2025) · Brain Sciences · doi:10.3390/brainsci15101088 · Cited by 19 · see citing works
Advanced MRI Methods for Diagnosis and Monitoring of Multiple Sclerosis ( MS )
Elahi, R., Taremi, S., Najafi, A., Karimi, H., Asadollahzadeh, E., Sajedi, S. A., Rad, H. S., & Sahraian, M. A. (2025) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.29817 · Cited by 14 · see citing works
Neurodegeneration and Demyelination in the Multiple Sclerosis Spinal Cord
Mahajan, K. R., Herman, D. E., Zheng, Y., Androjna, C., Thoomukuntla, B., Ontaneda, D., Nakamura, K., & Trapp, B. D. (2025) · Neurology · doi:10.1212/wnl.0000000000210259 · Cited by 14 · see citing works
Bateman, G. A., & Bateman, A. R. (2024) · npj Microgravity · doi:10.1038/s41526-024-00365-9 · Cited by 11 · see citing works
Bateman, G. A., & Bateman, A. R. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120517 · Cited by 8 · see citing works
It Looks Like a Spinal Cord Tumor but It Is Not
Fournel, J., Hermier, M., Martin, A., Gamondes, D., Tommasino, E., Broussolle, T., Morgado, A., Baassiri, W., Cotton, F., Berthezène, Y., et al. (2024) · Cancers · doi:10.3390/cancers16051004 · Cited by 3 · see citing works
Pisa, M., Lockhart, A., Angell, T., Avery, A., Dhari, Z., Bailey, M. A., Hametner, S., Drakesmith, H., Hofer, M., Limbӓck-Stanic, C., et al. (2026) · Annals of Neurology · doi:10.1002/ana.78113 · Cited by 3 · see citing works
Aberrant iron deposition in the multiple sclerosis spinal cord relates to neurodegenerationPreprint
Pisa, M., Lockhart, A., Angell, T., Avery, A., Waldman, A. D., Rodriguez, C., Duarte, T. L., Pansieri, J., Dhari, Z., Bailey, M. A., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.10.25.619794 · Cited by 2 · see citing works
Callot, V., Destruel, A., Demortière, S., & Testud, B. (2026) · Revue Neurologique · doi:10.1016/j.neurol.2026.04.003 · Cited by 1 · see citing works
Nguyen, N., Lauinger, A. R., Naik, A., Liu, R., Yolcu, Y. U., & Arnold, P. M. (2026) · Clinical Neuroradiology · doi:10.1007/s00062-026-01669-x · Cited by 1 · see citing works
Konen, F. F., Mahmoudi, N., Albers, L. M., Arrambide, G., Streichert, A. L., Haar, M., Soldatov, A., Bucak, E., Jendretzky, K. F., Nay, S., et al. (2026) · eClinicalMedicine · doi:10.1016/j.eclinm.2026.104098
“,41–43 Nevertheless, studies employing the select-6* methodology for CVS have reported high sensitivity and specificity for distinguishing MS from mimics, suggesting that wider adoption is of need, but may be limited to dedicated centres and a subgroup of patients.”
High-field imaging in multiple sclerosis
Bagnato, F. R., Barter, K. M., Cho, C., Koch, C. E., Rohm, Z., & McKnight, C. D. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-95739-7.00013-7
Self-citationMartire, M. S., Gattuso, I., Vezzulli, P. Q., Guerrieri, S., Falini, A., Moiola, L., Genchi, A., & Filippi, M. (2025) · Journal of Neurology · doi:10.1007/s00415-025-13526-x
Moriyama, K., Okamoto, M., Watanabe, M., Huang, H., Nakatani, K., Saito, S., Takahashi, Y., & Hayashi, M. (2026) · International Endodontic Journal · doi:10.1111/iej.70151
Streichenberger, B., Santin, M. D., de Rochefort, L., Duché, Q., Guillemot, C., Mchinda, S., Roche, S., Kerbrat, A., & Bannier, É. (2026) · NMR in Biomedicine · doi:10.1002/nbm.70296
Spinal cord imaging for multiple sclerosis: Advances, priorities, and opportunities
Laule, C., Cohen‐Adad, J., Witt, A. A., DeLuca, G. C., Granziera, C., Keegan, B. M., Kerbrat, A., Klawiter, E. C., Kolind, S., O’Grady, K. P., et al. (2026) · Multiple Sclerosis Journal · doi:10.1177/13524585261444600
Self-citationWan, S., Li, M. M., Han, G., Wang, C. H., Liu, N., Chen, B., Zhou, D., Ji, X., Ding, Y., & Meng, R. (2026) · European journal of medical research · doi:10.1186/s40001-026-04781-3
Spinal cord imaging in multiple sclerosis: from diagnosis to disease progression
Koren, T. J., Dugal, J., Wang, D., Beadnall, H. N., Wang, C. T., Barnett, Y., Calamante, F., Montalbán, X., Oh, J., & Barnett, M. H. (2026) · Journal of Neurology · doi:10.1007/s00415-026-14122-3
- Authors
- Clarke, M. A., Witt, A. A., Robison, R. K., Fleishman, S., Combes, A. J. E., Houston, D., Prock, L. E., Sweeney, G., O'Grady, K. P., McKnight, C. D., & Smith, S. A.
- Affiliations
- Vanderbilt University (US)
- Vanderbilt University Medical Center (US)
- Corresponding author
- Witt, Atlee A.
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2023-12
- Volume
- 284
- Pages
- 120460
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC12226311
- OpenAlex
- W4388751922
- Cited by
- 21
- References
- 37
- Citations by year
- 2026: 9 · 2025: 4 · 2024: 8
- FWCI
- 3.48
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- NeuroImage (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institutes of Health
- National Institute of General Medical Sciences (T32 GM007347)
- National Institute of Neurological Disorders and Stroke (5R01NS109114, 5R01NS117816)
- National Institute of Biomedical Imaging and Bioengineering (5K01EB030039)
- National Multiple Sclerosis Society
- Radiological Society of North America
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Pathology and Forensic Medicine › Multiple Sclerosis Research Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- susceptibility-weighted imaging, cervical spinal cord, multiple sclerosis, 7T MRI, central vein sign, paramagnetic rim lesions, spinal cord vasculature, T2*-weighted gradient echo, spinal cord lesions, high-field MRI
- MeSH terms
- Humans, Magnetic Resonance Imaging, Multiple Sclerosis, Pilot Projects, Retrospective Studies, Spinal Cord, Cervical Cord
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