Advanced Multicompartment Diffusion MRI Models and Their Application in Multiple Sclerosis

References

1. 1.↵
   1. Wallin MT,
   2. Culpepper WJ,
   3. Campbell JD, et al

   ; US Multiple Sclerosis Prevalence Workgroup. The prevalence of MS in the United States: a population-based estimate using health claims data. Neurology 2019;92:e1029–40 doi:10.1212/WNL.0000000000007035 pmid:30770430

   CrossRefPubMed
2. 2.↵
   1. Bagnato F,
   2. Jeffries N,
   3. Richert ND, et al

   . Evolution of T1 black holes in patients with multiple sclerosis imaged monthly for 4 years. Brain 2003;126:1782–89 doi:10.1093/brain/awg182 pmid:12821527

   CrossRefPubMedWeb of Science
3. 3.↵
   1. Cotton F,
   2. Weiner HL,
   3. Jolesz FA, et al

   . MRI contrast uptake in new lesions in relapsing-remitting MS followed at weekly intervals. Neurology 2003;60:640–46 doi:10.1212/01.wnl.0000046587.83503.1e pmid:12601106

   Abstract/FREE Full Text
4. 4.↵
   1. Patrikios P,
   2. Stadelmann C,
   3. Kutzelnigg A, et al

   . Remyelination is extensive in a subset of multiple sclerosis patients. Brain 2006;129:3165–72 doi:10.1093/brain/awl217 pmid:16921173

   CrossRefPubMedWeb of Science
5. 5.↵
   1. Frischer JM,
   2. Bramow S,
   3. Dal-Bianco A, et al

   . The relation between inflammation and neurodegeneration in multiple sclerosis brains. Brain 2009;132:1175–89 doi:10.1093/brain/awp070 pmid:19339255

   CrossRefPubMedWeb of Science
6. 6.↵
   1. Fox RJ,
   2. Thompson A,
   3. Baker D, et al

   . Setting a research agenda for progressive multiple sclerosis: the International Collaborative on Progressive MS. Mult Scler 2012;18:1534–40 doi:10.1177/1352458512458169 pmid:22917690

   CrossRefPubMed
7. 7.↵
   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
8. 8.↵
   1. Hutchinson EB,
   2. Avram AV,
   3. Irfanoglu MO, et al

   . Analysis of the effects of noise, DWI sampling, and value of assumed parameters in diffusion MRI models. Magn Reson Med 2017;78:1767–80 doi:10.1002/mrm.26575 pmid:28090658

   CrossRefPubMed
9. 9.
   1. Kunz N,
   2. da Silva AR,
   3. Jelescu IO

   . Intra- and extra-axonal axial diffusivities in the white matter: which one is faster? Neuroimage 2018;181:314–22 doi:10.1016/j.neuroimage.2018.07.020 pmid:30005917

   CrossRefPubMed
10. 10.↵
    1. Lee HH,
    2. Fieremans E,
    3. Novikov DS

    . What dominates the time dependence of diffusion transverse to axons: intra- or extra-axonal water? Neuroimage 2018;182:500–10 doi:10.1016/j.neuroimage.2017.12.038 pmid:29253652

    CrossRefPubMed
11. 11.↵
    1. Grussu F,
    2. Schneider T,
    3. Tur C, et al

    . Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology? Ann Clin Transl Neurol 2017;4:663–79 doi:10.1002/acn3.445 pmid:28904988

    CrossRefPubMed
12. 12.↵
    1. Chen A,
    2. Franco G,
    3. Smith S, et al

    . Measuring white matter axonal injury in patients with multiple sclerosis. In: Proceedings of the American Academy of Neurology Annual Meeting, Philadelphia, Pennsylvania. May 4–10, 2019
13. 13.↵
    1. By S,
    2. Xu J,
    3. Box BA, et al

    . Application and evaluation of NODDI in the cervical spinal cord of multiple sclerosis patients. Neuroimage Clin 2017;15:333–42 doi:10.1016/j.nicl.2017.05.010 pmid:28560158

    CrossRefPubMed
14. 14.↵
    1. Granberg T,
    2. Fan Q,
    3. Treaba CA, et al

    . In vivo characterization of cortical and white matter neuroaxonal pathology in early multiple sclerosis. Brain 2017;140:2912–26 doi:10.1093/brain/awx247 pmid:29053798

    CrossRefPubMed
15. 15.↵
    1. Schneider T,
    2. Brownlee W,
    3. Zhang H, et al

    . Sensitivity of multi-shell NODDI to multiple sclerosis white matter changes: a pilot study. Funct Neurol 2017;32:97–101 doi:10.11138/fneur/2017.32.2.097 pmid:28676143

    CrossRefPubMed
16. 16.↵
    1. Mustafi SM,
    2. Harezlak J,
    3. Kodiweera C, et al

    . Detecting white matter alterations in multiple sclerosis using advanced diffusion magnetic resonance imaging. Neural Regen Res 2019;14:114–23 doi:10.4103/1673-5374.243716 pmid:30531085

    CrossRefPubMed
17. 17.↵
    1. Collorone S,
    2. Cawley N,
    3. Grussu F, et al

    . Reduced neurite density in the brain and cervical spinal cord in relapsing-remitting multiple sclerosis: a NODDI study. Mult Scler 2019 Nov 4. [Epub ahead of print] doi:10.1177/1352458519885107] pmid:31682198

    CrossRefPubMed
18. 18.↵
    1. Spanò B,
    2. Giulietti G,
    3. Pisani V, et al

    . Disruption of neurite morphology parallels MS progression. Neurol Neuroimmunol Neuroinflamm 2018;5:e502 doi:10.1212/NXI.0000000000000502 pmid:30345330

    Abstract/FREE Full Text
19. 19.↵
    1. Kurtzke JF

    . Rating neurologic impairment in multiple sclerosis: an Expanded Disability Status Scale (EDSS). Neurology 1983;33:1444–52 doi:10.1212/wnl.33.11.1444 pmid:6685237

    Abstract/FREE Full Text
20. 20.↵
    1. Kaden E,
    2. Kruggel F,
    3. Alexander DC

    . Quantitative mapping of the per-axon diffusion coefficients in brain white matter. Magn Reson Med 2016;75:1752–53 doi:10.1002/mrm.25734 pmid:25974332

    CrossRefPubMed
21. 21.↵
    1. Kaden E,
    2. Kelm ND,
    3. Carson RP, et al

    . Multi-compartment microscopic diffusion imaging. Neuroimage 2016;139:346–59 doi:10.1016/j.neuroimage.2016.06.002 pmid:27282476

    CrossRefPubMed
22. 22.↵
    1. Bagnato F,
    2. Franco G,
    3. Li H, et al

    . Probing axons using multi-compartmental diffusion in multiple sclerosis. Ann Clin Transl Neurol 2019;6:1595–1605 doi:10.1002/acn3.50836

    CrossRef
23. 23.↵
    1. By S,
    2. Xu J,
    3. Box BA, et al

    . Multi-compartmental diffusion characterization of the human cervical spinal cord in vivo using the spherical mean technique. NMR Biomed 2018;31:e3894 doi:10.1002/nbm.3894 pmid:29388719

    CrossRefPubMed
24. 24.↵
    1. Grussu F,
    2. Ianuş A,
    3. Tur C, et al

    . Relevance of time-dependence for clinically viable diffusion imaging of the spinal cord. Magn Reson Med 2019;81:1247–64 doi:10.1002/mrm.27463 pmid:30229564

    CrossRefPubMed
25. 25.↵
    1. Wang Y,
    2. Wang Q,
    3. Haldar JP, et al

    . Quantification of increased cellularity during inflammatory demyelination. Brain 2011;134:3590–3601 doi:10.1093/brain/awr307 pmid:22171354

    CrossRefPubMed
26. 26.↵
    1. Shirani A,
    2. Sun P,
    3. Schmidt RE, et al

    . Histopathological correlation of diffusion basis spectrum imaging metrics of a biopsy-proven inflammatory demyelinating brain lesion: a brief report. Mult Scler 2019;25:1937–41 doi:10.1177/1352458518786072

    CrossRef
27. 27.↵
    1. Wang Y,
    2. Sun P,
    3. Wang Q, et al

    . Differentiation and quantification of inflammation, demyelination and axon injury or loss in multiple sclerosis. Brain 2015;138:1223–38 doi:10.1093/brain/awv046 pmid:25724201

    CrossRefPubMed
28. 28.↵
    1. Shirani A,
    2. Sun P,
    3. Trinkaus K, et al

    . Diffusion basis spectrum imaging for identifying pathologies in MS subtypes. Ann Clin Transl Neurol 2019;6:2323–27 doi:10.1002/acn3.50903 pmid:31588688

    CrossRefPubMed
29. 29.↵
    1. Assaf Y,
    2. Blumenfeld-Katzir T,
    3. Yovel Y, et al

    . AxCaliber: a method for measuring axon diameter distribution from diffusion MRI. Magn Reson Med 2008;59:1347–54 doi:10.1002/mrm.21577

    CrossRefPubMedWeb of Science
30. 30.↵
    1. Alexander DC,
    2. Hubbard PL,
    3. Hall MG, et al

    . Orientationally invariant indices of axon diameter and density from diffusion MRI. Neuroimage 2010;52:1374–89 doi:10.1016/j.neuroimage.2010.05.043 pmid:20580932

    CrossRefPubMedWeb of Science
31. 31.↵
    1. Huang SY,
    2. Tobyne SM,
    3. Nummenmaa A, et al

    . Characterization of axonal disease in patients with multiple sclerosis using high-gradient-diffusion MR imaging. Radiology 2016;280:244–51 doi:10.1148/radiol.2016151582 pmid:26859256

    CrossRefPubMed
32. 32.↵
    1. Duval T,
    2. McNab JA,
    3. Setsompop K, et al

    . In vivo mapping of human spinal cord microstructure at 300mT/m. Neuroimage 2015;118:494–507 doi:10.1016/j.neuroimage.2015.06.038 pmid:26095093

    CrossRefPubMed
33. 33.↵
    1. Huang SY,
    2. Tian Q,
    3. Fan Q, et al

    . High-gradient diffusion MRI reveals distinct estimates of axon diameter index within different white matter tracts in the in vivo human brain. Brain Struct Funct 2019 Sep 28. [Epub ahead of print] doi:10.1007/s00429-019-01961-2] pmid:31563995

    CrossRefPubMed
34. 34.↵
    1. Huang SY,
    2. Nummenmaa A,
    3. Witzel T, et al

    . The impact of gradient strength on in vivo diffusion MRI estimates of axon diameter. Neuroimage 2015;106:464–72 doi:10.1016/j.neuroimage.2014.12.008 pmid:25498429

    CrossRefPubMed
35. 35.↵
    1. Aboitiz F,
    2. Scheibel AB,
    3. Fisher RS, et al

    . Fiber composition of the human corpus callosum. Brain Res 1992;598:143–53 doi:10.1016/0006-8993(92)90178-c pmid:1486477

    CrossRefPubMedWeb of Science
36. 36.↵
    1. Burcaw LM,
    2. Fieremans E,
    3. Novikov DS

    . Mesoscopic structure of neuronal tracts from time-dependent diffusion. Neuroimage 2015;114:18–37 doi:10.1016/j.neuroimage.2015.03.061 pmid:25837598

    CrossRefPubMed
37. 37.↵
    1. Huang SY,
    2. Fan Q,
    3. Machado N, et al

    . Corpus callosum axon diameter relates to cognitive impairment in multiple sclerosis. Ann Clin Transl Neurol 2019;6:882–92 doi:10.1002/acn3.760 pmid:31139686

    CrossRefPubMed
38. 38.↵
    1. Santis SD,
    2. Herranz E,
    3. Treaba CA, et al

    . Whole brain in vivo axonal diameter mapping in multiple sclerosis. In: Proceedings of the International Engineering in Medicine and Biology Conference, Berlin, Germany. July 23–27, 2019; 204–07
39. 39.↵
    1. Kutzelnigg A,
    2. Lucchinetti CF,
    3. Stadelmann C, et al

    . Cortical demyelination and diffuse white matter injury in multiple sclerosis. Brain 2005;128:2705–12 doi:10.1093/brain/awh641 pmid:16230320

    CrossRefPubMedWeb of Science
40. 40.↵
    1. Feinberg DA,
    2. Setsompop K

    . Ultra-fast MRI of the human brain with simultaneous multi-slice imaging. J Magn Reson 2013;229:90–100 doi:10.1016/j.jmr.2013.02.002 pmid:23473893

    CrossRefPubMed
41. 41.↵
    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
42. 42.↵
    1. Shepherd TM,
    2. Thelwall PE,
    3. Stanisz GJ, et al

    . Aldehyde fixative solutions alter the water relaxation and diffusion properties of nervous tissue. Magn Reson Med 2009;62:26–34 doi:10.1002/mrm.21977 pmid:19353660

    CrossRefPubMedWeb of Science
43. 43.↵
    1. Shatil AS,
    2. Uddin MN,
    3. Matsuda KM, et al

    . Quantitative ex vivo MRI changes due to progressive formalin fixation in whole human brain specimens: longitudinal characterization of diffusion, relaxometry, and myelin water fraction measurements at 3T. Front Med (Lausanne) 2018;5:31 doi:10.3389/fmed.2018.00031 pmid:29515998

    CrossRefPubMed
44. 44.
    1. Cutter GR,
    2. Baier ML,
    3. Rudick RA, et al

    . Development of a multiple sclerosis functional composite as a clinical trial outcome measure. Brain 1999;122:871–82 doi:10.1093/brain/122.5.871 pmid:10355672

    CrossRefPubMedWeb of Science