Skip to main content
Advertisement

Main menu

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • Video Articles
    • AJNR Case Collection
    • Case of the Week Archive
    • Case of the Month Archive
    • Classic Case Archive
  • Special Collections
    • AJNR Awards
    • Low-Field MRI
    • Alzheimer Disease
    • ASNR Foundation Special Collection
    • Photon-Counting CT
    • View All
  • Multimedia
    • AJNR Podcasts
    • AJNR SCANtastic
    • Trainee Corner
    • MRI Safety Corner
    • Imaging Protocols
  • For Authors
    • Submit a Manuscript
    • Submit a Video Article
    • Submit an eLetter to the Editor/Response
    • Manuscript Submission Guidelines
    • Statistical Tips
    • Fast Publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Imaging Protocol Submission
    • Author Policies
  • About Us
    • About AJNR
    • Editorial Board
    • Editorial Board Alumni
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home

User menu

  • Alerts
  • Log in

Search

  • Advanced search
American Journal of Neuroradiology
American Journal of Neuroradiology

American Journal of Neuroradiology

ASHNR American Society of Functional Neuroradiology ASHNR American Society of Pediatric Neuroradiology ASSR
  • Alerts
  • Log in

Advanced Search

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • Video Articles
    • AJNR Case Collection
    • Case of the Week Archive
    • Case of the Month Archive
    • Classic Case Archive
  • Special Collections
    • AJNR Awards
    • Low-Field MRI
    • Alzheimer Disease
    • ASNR Foundation Special Collection
    • Photon-Counting CT
    • View All
  • Multimedia
    • AJNR Podcasts
    • AJNR SCANtastic
    • Trainee Corner
    • MRI Safety Corner
    • Imaging Protocols
  • For Authors
    • Submit a Manuscript
    • Submit a Video Article
    • Submit an eLetter to the Editor/Response
    • Manuscript Submission Guidelines
    • Statistical Tips
    • Fast Publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Imaging Protocol Submission
    • Author Policies
  • About Us
    • About AJNR
    • Editorial Board
    • Editorial Board Alumni
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home
  • Follow AJNR on Twitter
  • Visit AJNR on Facebook
  • Follow AJNR on Instagram
  • Join AJNR on LinkedIn
  • RSS Feeds

AJNR Awards, New Junior Editors, and more. Read the latest AJNR updates

Research ArticleULTRA-HIGH-FIELD MRI/IMAGING OF EPILEPSY/DEMYELINATING DISEASES/INFLAMMATION/INFECTION

Multiparametric Characterization and Spatial Distribution of Different MS Lesion Phenotypes

Francesco Tazza, Giacomo Boffa, Simona Schiavi, Caterina Lapucci, Gian Franco Piredda, Emilio Cipriano, Domenico Zacà, Luca Roccatagliata, Tom Hilbert, Tobias Kober, Matilde Inglese and Mauro Costagli
American Journal of Neuroradiology May 2024, DOI: https://doi.org/10.3174/ajnr.A8271
Francesco Tazza
aFrom the Departments of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (F.T., G.B., S.S., E.C., M.I., M.C.), University of Genoa, Genoa, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Francesco Tazza
Giacomo Boffa
aFrom the Departments of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (F.T., G.B., S.S., E.C., M.I., M.C.), University of Genoa, Genoa, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Giacomo Boffa
Simona Schiavi
aFrom the Departments of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (F.T., G.B., S.S., E.C., M.I., M.C.), University of Genoa, Genoa, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Caterina Lapucci
bIstituto di Ricovero e Cura a Carattere Scientifico (C.L., L.R., M.I., M.C.), Ospedale Policlinico San Martino, Genoa, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Caterina Lapucci
Gian Franco Piredda
cAdvanced Clinical Imaging Technology (G.F.P., T.H., T.K.), Siemens Healthineers International AG, Lausanne, Switzerland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Emilio Cipriano
aFrom the Departments of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (F.T., G.B., S.S., E.C., M.I., M.C.), University of Genoa, Genoa, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Domenico Zacà
fSiemens Healthcare (D.Z.), Milan, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Luca Roccatagliata
bIstituto di Ricovero e Cura a Carattere Scientifico (C.L., L.R., M.I., M.C.), Ospedale Policlinico San Martino, Genoa, Italy
gDepartment of Health Sciences (L.R.), University of Genoa, Genoa, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Luca Roccatagliata
Tom Hilbert
cAdvanced Clinical Imaging Technology (G.F.P., T.H., T.K.), Siemens Healthineers International AG, Lausanne, Switzerland
dDepartment of Radiology (T.H., T.K.), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
eLTS5 (T.H., T.K.), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Tobias Kober
cAdvanced Clinical Imaging Technology (G.F.P., T.H., T.K.), Siemens Healthineers International AG, Lausanne, Switzerland
dDepartment of Radiology (T.H., T.K.), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
eLTS5 (T.H., T.K.), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Tobias Kober
Matilde Inglese
aFrom the Departments of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (F.T., G.B., S.S., E.C., M.I., M.C.), University of Genoa, Genoa, Italy
bIstituto di Ricovero e Cura a Carattere Scientifico (C.L., L.R., M.I., M.C.), Ospedale Policlinico San Martino, Genoa, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Matilde Inglese
Mauro Costagli
aFrom the Departments of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (F.T., G.B., S.S., E.C., M.I., M.C.), University of Genoa, Genoa, Italy
bIstituto di Ricovero e Cura a Carattere Scientifico (C.L., L.R., M.I., M.C.), Ospedale Policlinico San Martino, Genoa, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Mauro Costagli
  • Article
  • Figures & Data
  • Info & Metrics
  • Responses
  • References
  • PDF
Loading

References

  1. 1.↵
    1. Kuhlmann T,
    2. Ludwin S,
    3. Prat A, et al
    . An updated histological classification system for multiple sclerosis lesions. Acta Neuropathol 2017;133:13–24 doi:10.1007/s00401-016-1653-y pmid:27988845
    CrossRefPubMed
  2. 2.↵
    1. Pardini M,
    2. Brown JWL,
    3. Magliozzi R, et al
    . Surface-in pathology in multiple sclerosis: a new view on pathogenesis? Brain J Brain 2021;144:1646–54 doi:10.1093/brain/awab025 pmid:33876200
    CrossRefPubMed
  3. 3.↵
    1. Klistorner S,
    2. Barnett MH,
    3. Graham SL, et al
    . The expansion and severity of chronic MS lesions follows a periventricular gradient. Mult Scler 2022;28:1504–14 doi:10.1177/13524585221080667 pmid:35296170
    CrossRefPubMed
  4. 4.↵
    1. Vaneckova M,
    2. Piredda GF,
    3. Andelova M, et al
    . Periventricular gradient of T1 tissue alterations in multiple sclerosis. Neuroimage Clin 2022;34:103009 doi:10.1016/j.nicl.2022.103009 pmid:35561554
    CrossRefPubMed
  5. 5.↵
    1. Marinero C,
    2. Louapre C,
    3. Govindarajan ST, et al
    . Gradient in cortical pathology in multiple sclerosis by in vivo quantitative 7 T imaging. Brain 2015;138(Pt 4):932–45 doi:10.1093/brain/awv011 pmid:25681411
    CrossRefPubMed
  6. 6.↵
    1. Poirion E,
    2. Tonietto M,
    3. Lejeune FX, et al
    . Structural and clinical correlates of a periventricular gradient of neuroinflammation in multiple sclerosis. Neurology 2021;96:e1865–75 doi:10.1212/WNL.0000000000011700 pmid:33737372
    CrossRefPubMed
  7. 7.↵
    1. Gillen KM,
    2. Mubarak M,
    3. Park C, et al
    . QSM is an imaging biomarker for chronic glial activation in multiple sclerosis lesions. Ann Clin Transl Neurol 2021;8:877–86 doi:10.1002/acn3.51338 pmid:33704933
    CrossRefPubMed
  8. 8.↵
    1. Rahmanzadeh R,
    2. Galbusera R,
    3. Lu PJ, et al
    . A new advanced MRI biomarker for remyelinated lesions in multiple sclerosis. Ann Neurol 2022;92:486–502 doi:10.1002/ana.26441 pmid:35713309
    CrossRefPubMed
  9. 9.↵
    1. Ng Kee Kwong KC,
    2. Mollison D,
    3. Meijboom R, et al
    . The prevalence of paramagnetic rim lesions in multiple sclerosis: a systematic review and meta-analysis. PLoS One 2021;16:e0256845 doi:10.1371/journal.pone.0256845 pmid:34495999
    CrossRefPubMed
  10. 10.↵
    1. Bagnato F,
    2. Sati P,
    3. Hemond CC, et al
    . Imaging chronic active lesions in multiple sclerosis: a consensus statement. Brain J Neurol 2024 Jan 16 [Epub ahead of print] doi:10.1093/brain/awae013 pmid:38226694
    CrossRefPubMed
  11. 11.↵
    1. Gho SM,
    2. Liu C,
    3. Li W, et al
    . Susceptibility map-weighted imaging (SMWI) for neuroimaging. Magn Reson Med 2014;72:337–46 doi:10.1002/mrm.24920 pmid:24006248
    CrossRefPubMed
  12. 12.↵
    1. Krajnc N,
    2. Schmidbauer V,
    3. Leinkauf J, et al
    . Paramagnetic rim lesions lead to pronounced diffuse periplaque white matter damage in multiple sclerosis. Mult Scler 2023;29:1406–17 doi:10.1177/13524585231197954 pmid:37712486
    CrossRefPubMed
  13. 13.↵
    1. Kolb H,
    2. Absinta M,
    3. Beck ES, et al
    . 7T MRI differentiates remyelinated from demyelinated multiple sclerosis lesions. Ann Neurol 2021;90:612–26 doi:10.1002/ana.26194 pmid:34390015
    CrossRefPubMed
  14. 14.↵
    1. Hu H,
    2. Ye L,
    3. Ding S, et al
    . The heterogeneity of tissue destruction between iron rim lesions and non-iron rim lesions in multiple sclerosis: a diffusion MRI study. Mult Scler Relat Disord 2022;66:104070 doi:10.1016/j.msard.2022.104070 pmid:35914471
    CrossRefPubMed
  15. 15.↵
    1. Piredda GF,
    2. Hilbert T,
    3. Thiran JP, et al
    . Probing myelin content of the human brain with MRI: a review. Magn Reson Med 2021;85:627–52 doi:10.1002/mrm.28509 pmid:32936494
    CrossRefPubMed
  16. 16.↵
    1. Mussard E,
    2. Hilbert T,
    3. Forman C, et al
    . Accelerated MP2RAGE imaging using Cartesian phyllotaxis readout and compressed sensing reconstruction. Magn Reson Med 2020;84:1881–94 doi:10.1002/mrm.28244 pmid:32176826
    CrossRefPubMed
  17. 17.↵
    1. Piredda GF,
    2. Hilbert T,
    3. Canales-Rodríguez EJ, et al
    . Fast and high-resolution myelin water imaging: Accelerating multi-echo GRASE with CAIPIRINHA. Magn Reson Med 2021;85:209–22 doi:10.1002/mrm.28427 pmid:32720406
    CrossRefPubMed
  18. 18.↵
    1. Sati P,
    2. Thomasson DM,
    3. Li N, et al
    . Rapid, high-resolution, whole-brain, susceptibility-based MRI of multiple sclerosis. Mult Scler 2014;20:1464–70 doi:10.1177/1352458514525868 pmid:24639479
    CrossRefPubMed
  19. 19.↵
    1. Zhang F,
    2. Daducci A,
    3. He Y, et al
    . Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: a review. Neuroimage 2022;249:118870 doi:10.1016/j.neuroimage.2021.118870 pmid:34979249
    CrossRefPubMed
  20. 20.↵
    1. Caruyer E,
    2. Lenglet C,
    3. Sapiro G, et al
    . Design of multishell sampling schemes with uniform coverage in diffusion MRI. Magn Reson Med 2013;69:1534–40 doi:10.1002/mrm.24736 pmid:23625329
    CrossRefPubMed
  21. 21.↵
    1. von Elm E,
    2. Altman DG,
    3. Egger M, et al
    . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for Reporting Observational Studies. Ann Intern Med 2007;147:573–77 doi:10.7326/0003-4819-147-8-200710160-00010 pmid:17938396
    CrossRefPubMedWeb of Science
  22. 22.↵
    1. Schofield MA,
    2. Zhu Y
    . Fast phase unwrapping algorithm for interferometric applications. Opt Lett 2003;28:1194–96 doi:10.1364/ol.28.001194 pmid:12885018
    CrossRefPubMed
  23. 23.↵
    1. Schweser F,
    2. Deistung A,
    3. Lehr BW, et al
    . Quantitative imaging of intrinsic magnetic tissue properties using MRI signal phase: an approach to in vivo brain iron metabolism? Neuroimage 2011;54:2789–807 doi:10.1016/j.neuroimage.2010.10.070 pmid:21040794
    CrossRefPubMedWeb of Science
  24. 24.↵
    1. Nam Y,
    2. Gho SM,
    3. Kim DH, et al
    . Imaging of nigrosome 1 in substantia nigra at 3T using multiecho susceptibility map-weighted imaging (SMWI). J Magn Reson Imaging 2017;46:528–36 doi:10.1002/jmri.25553 pmid:27859983
    CrossRefPubMed
  25. 25.↵
    1. Bilgic B,
    2. Costagli M,
    3. Chan KS, et al
    ; ISMRM Electro-Magnetic Tissue Properties Study Group. 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;91:1834–62 doi:10.1002/mrm.30006 pmid:38247051
    CrossRefPubMed
  26. 26.↵
    1. Jenkinson M,
    2. Beckmann CF,
    3. Behrens TEJ, et al
    . FSL. Neuroimage 2012;62:782–90 doi:10.1016/j.neuroimage.2011.09.015 pmid:21979382
    CrossRefPubMedWeb of Science
  27. 27.↵
    1. Lim IA,
    2. Faria AV,
    3. Li X, et al
    . Human brain atlas for automated region of interest selection in quantitative susceptibility mapping: application to determine iron content in deep gray matter structures. Neuroimage 2013;82:449–69 doi:10.1016/j.neuroimage.2013.05.127 pmid:23769915
    CrossRefPubMed
  28. 28.↵
    1. Lancione M,
    2. Tosetti M,
    3. Donatelli G, et al
    . The impact of white matter fiber orientation in single-acquisition quantitative susceptibility mapping. NMR Biomed 2017;30(11) doi:10.1002/nbm.3798 pmid:28902421
    CrossRefPubMed
  29. 29.↵
    1. Canales-Rodríguez EJ,
    2. Pizzolato M,
    3. Piredda GF, et al
    . Comparison of non-parametric T2 relaxometry methods for myelin water quantification. Med Image Anal 2021;69:101959 doi:10.1016/j.media.2021.101959 pmid:33581618
    CrossRefPubMed
  30. 30.↵
    1. Veraart J,
    2. Novikov DS,
    3. Christiaens D, et al
    . Denoising of diffusion MRI using random matrix theory. NeuroImage 2016;142:394–406 doi:10.1016/j.neuroimage.2016.08.016 pmid:27523449
    CrossRefPubMed
  31. 31.↵
    1. Andersson JLR,
    2. Sotiropoulos SN
    . An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage 2016;125:1063–78 doi:10.1016/j.neuroimage.2015.10.019 pmid:26481672
    CrossRefPubMed
  32. 32.↵
    1. Avants BB,
    2. Tustison NJ,
    3. Song G, et al
    . A reproducible evaluation of ANTs similarity metric performance in brain image registration. NeuroImage 2011;54:2033–44 doi:10.1016/j.neuroimage.2010.09.025 pmid:20851191
    CrossRefPubMed
  33. 33.↵
    1. Zhang H,
    2. Schneider T,
    3. Wheeler-Kingshott CA, et al
    . NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. Neuroimage 2012;61:1000–16 doi:10.1016/j.neuroimage.2012.03.072 pmid:22484410
    CrossRefPubMed
  34. 34.↵
    1. Daducci A,
    2. Canales-Rodríguez EJ,
    3. Zhang H, et al
    . Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data. Neuroimage 2015;105:32–44 doi:10.1016/j.neuroimage.2014.10.026 pmid:25462697
    CrossRefPubMed
  35. 35.↵
    1. Marques JP,
    2. Kober T,
    3. Krueger G, et al
    . MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field. NeuroImage 2010;49:1271–81 doi:10.1016/j.neuroimage.2009.10.002 pmid:19819338
    CrossRefPubMedWeb of Science
  36. 36.↵
    1. Hemond CC,
    2. Reich DS,
    3. Dundamadappa SK
    . Paramagnetic rim lesions in multiple sclerosis: comparison of visualization at 1.5-T and 3-T MRI. AJR Am J Roentgenol 2022;219:120–31 doi:10.2214/AJR.21.26777 pmid:34851712
    CrossRefPubMed
  37. 37.↵
    1. Hamzaoui M,
    2. Garcia J,
    3. Boffa G, et al
    . Positron emission tomography with [18F]-DPA-714 unveils a smoldering component in most multiple sclerosis lesions which drives disease progression. Ann Neurol 2023;94:366–83 doi:10.1002/ana.26657 pmid:37039158
    CrossRefPubMed
  38. 38.↵
    1. Tonietto M,
    2. Poirion E,
    3. Lazzarotto A, et al
    . Periventricular remyelination failure in multiple sclerosis: a substrate for neurodegeneration. Brain 2023;146:182–94 doi:10.1093/brain/awac334 pmid:36097347
    CrossRefPubMed
  39. 39.↵
    1. Galbusera R,
    2. Bahn E,
    3. Weigel M, et al
    . Characteristics, prevalence, and clinical relevance of juxtacortical paramagnetic rims in patients with multiple sclerosis. Neurology 2024;102:e207966 doi:10.1212/WNL.0000000000207966 pmid:38165297
    CrossRefPubMed
PreviousNext
Back to top
Advertisement
Print
Download PDF
Email Article

Thank you for your interest in spreading the word on American Journal of Neuroradiology.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Multiparametric Characterization and Spatial Distribution of Different MS Lesion Phenotypes
(Your Name) has sent you a message from American Journal of Neuroradiology
(Your Name) thought you would like to see the American Journal of Neuroradiology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Cite this article
Francesco Tazza, Giacomo Boffa, Simona Schiavi, Caterina Lapucci, Gian Franco Piredda, Emilio Cipriano, Domenico Zacà, Luca Roccatagliata, Tom Hilbert, Tobias Kober, Matilde Inglese, Mauro Costagli
Multiparametric Characterization and Spatial Distribution of Different MS Lesion Phenotypes
American Journal of Neuroradiology May 2024, DOI: 10.3174/ajnr.A8271

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
0 Responses
Respond to this article
Share
Bookmark this article
Multiparametric Characterization and Spatial Distribution of Different MS Lesion Phenotypes
Francesco Tazza, Giacomo Boffa, Simona Schiavi, Caterina Lapucci, Gian Franco Piredda, Emilio Cipriano, Domenico Zacà, Luca Roccatagliata, Tom Hilbert, Tobias Kober, Matilde Inglese, Mauro Costagli
American Journal of Neuroradiology May 2024, DOI: 10.3174/ajnr.A8271
del.icio.us logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Purchase

Jump to section

  • Article
    • Abstract
    • ABBREVIATIONS:
    • MATERIALS AND METHODS
    • RESULTS
    • DISCUSSION
    • CONCLUSIONS
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • Responses
  • References
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • No citing articles found.
  • Crossref
  • Google Scholar

This article has not yet been cited by articles in journals that are participating in Crossref Cited-by Linking.

More in this TOC Section

  • Automated Lesion Segmentation Software in MS
  • DL Image Reconstruction in T2-Weighted TSE at 7T
  • 7T MRI vasculitis imaging
Show more Ultra-High-Field MRI/Imaging of Epilepsy/Demyelinating Diseases/Inflammation/Infection

Similar Articles

Advertisement

Indexed Content

  • Current Issue
  • Accepted Manuscripts
  • Article Preview
  • Past Issues
  • Editorials
  • Editor's Choice
  • Fellows' Journal Club
  • Letters to the Editor
  • Video Articles

Cases

  • Case Collection
  • Archive - Case of the Week
  • Archive - Case of the Month
  • Archive - Classic Case

More from AJNR

  • Trainee Corner
  • Imaging Protocols
  • MRI Safety Corner
  • Book Reviews

Multimedia

  • AJNR Podcasts
  • AJNR Scantastics

Resources

  • Turnaround Time
  • Submit a Manuscript
  • Submit a Video Article
  • Submit an eLetter to the Editor/Response
  • Manuscript Submission Guidelines
  • Statistical Tips
  • Fast Publishing of Accepted Manuscripts
  • Graphical Abstract Preparation
  • Imaging Protocol Submission
  • Evidence-Based Medicine Level Guide
  • Publishing Checklists
  • Author Policies
  • Become a Reviewer/Academy of Reviewers
  • News and Updates

About Us

  • About AJNR
  • Editorial Board
  • Editorial Board Alumni
  • Alerts
  • Permissions
  • Not an AJNR Subscriber? Join Now
  • Advertise with Us
  • Librarian Resources
  • Feedback
  • Terms and Conditions
  • AJNR Editorial Board Alumni

American Society of Neuroradiology

  • Not an ASNR Member? Join Now

© 2025 by the American Society of Neuroradiology All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Print ISSN: 0195-6108 Online ISSN: 1936-959X

Powered by HighWire