Brain Structure and Function

, Volume 224, Issue 5, pp 1797–1813 | Cite as

Neurite orientation dispersion and density imaging of mouse brain microstructure

  • Nian WangEmail author
  • Jieying Zhang
  • Gary Cofer
  • Yi Qi
  • Robert J. Anderson
  • Leonard E. White
  • G. Allan JohnsonEmail author
Original Article


Advanced biophysical models like neurite orientation dispersion and density imaging (NODDI) have been developed to estimate the microstructural complexity of voxels enriched in dendrites and axons for both in vivo and ex vivo studies. NODDI metrics derived from high spatial and angular resolution diffusion MRI using the fixed mouse brain as a reference template have not yet been reported due in part to the extremely long scan time required. In this study, we modified the three-dimensional diffusion-weighted spin-echo pulse sequence for multi-shell and undersampling acquisition to reduce the scan time. This allowed us to acquire several exhaustive datasets that would otherwise not be attainable. NODDI metrics were derived from a complex 8-shell diffusion (1000–8000 s/mm2) dataset with 384 diffusion gradient-encoding directions at 50 µm isotropic resolution. These provided a foundation for exploration of tradeoffs among acquisition parameters. A three-shell acquisition strategy covering low, medium, and high b values with at least angular resolution of 64 is essential for ex vivo NODDI experiments. The good agreement between neurite density index (NDI) and the orientation dispersion index (ODI) with the subsequent histochemical analysis of myelin and neuronal density highlights that NODDI could provide new insight into the microstructure of the brain. Furthermore, we found that NDI is sensitive to microstructural variations in the corpus callosum using a well-established demyelination cuprizone model. The study lays the ground work for developing protocols for routine use of high-resolution NODDI method in characterizing brain microstructure in mouse models.


NODDI Compressed sensing Diffusion MRI Demyelination Cuprizone Neurite density 



This work was supported by the NIH P41 EB015897 (to GA Johnson), NIH 1S10OD010683-01 (to GA Johnson), 1R01NS096720-01A1 (to GA Johnson). The authors thank James Cook and Lucy Upchurch for significant technical support. The authors thank Prof. Jie Zhuang for insight comments and discussions. The authors thank Tatiana Johnson for editorial comments on the manuscript. The authors thank NIEHS with histology help.

Compliance with ethical standards

Conflict of interest

The authors declare no competing financial interests.

Ethical approval

All animal studies have been approved by the appropriate ethics committee: Duke University Institutional Animal Care and Use Committee.

Informed consent

No human subject was used in this study.

Supplementary material

429_2019_1877_MOESM1_ESM.docx (23.6 mb)
Supplementary material 1 (DOCX 24119 kb)


  1. Aggarwal M, Jones MV, Calabresi PA, Mori S, Zhang JY (2012) Probing mouse brain microstructure using oscillating gradient diffusion MRI. Magn Reson Med 67(1):98–109. Google Scholar
  2. Alexander DC, Hubbard PL, Hall MG, Moore EA, Ptito M, Parker GJ, Dyrby TB (2010) Orientationally invariant indices of axon diameter and density from diffusion MRI. Neuroimage 52(4):1374–1389. Google Scholar
  3. Alomair OI, Brereton IM, Smith MT, Galloway GJ, Kurniawan ND (2015) In vivo high angular resolution diffusion-weighted imaging of mouse brain at 16.4 Tesla. PLoS One 10(6):e0130133. Google Scholar
  4. Anderson C, Gerding WM, Fraenz C, Schluter C, Friedrich P, Raane M, Arning L, Epplen JT, Gunturkun O, Beste C, Genc E, Ocklenburg S (2018) PLP1 and CNTN1 gene variation modulates the microstructure of human white matter in the corpus callosum. Brain Struct Funct 223(8):3875–3887. Google Scholar
  5. Assaf Y (2018) Imaging laminar structures in the gray matter with diffusion MRI. Neuroimage 17:31120–31125. Google Scholar
  6. Barazany D, Basser PJ, Assaf Y (2009) In vivo measurement of axon diameter distribution in the corpus callosum of rat brain. Brain 132(Pt 5):1210–1220. Google Scholar
  7. Barth M, Breuer F, Koopmans PJ, Norris DG, Poser BA (2016) Simultaneous multislice (SMS) imaging techniques. Magn Reson Med 75(1):63–81. Google Scholar
  8. Basser PJ, Mattiello J, LeBihan D (1994) MR diffusion tensor spectroscopy and imaging. Biophys J 66(1):259–267. Google Scholar
  9. Beaujoin J, Palomero-Gallagher N, Boumezbeur F, Axer M, Bernard J, Poupon F, Schmitz D, Mangin JF, Poupon C (2018) Post-mortem inference of the human hippocampal connectivity and microstructure using ultra-high field diffusion MRI at 11.7 T. Brain Struct Funct 223(5):2157–2179. Google Scholar
  10. Calabrese E, Badea A, Cofer G, Qi Y, Johnson GA (2015) A diffusion MRI tractography connectome of the mouse brain and comparison with neuronal tracer data. Cereb Cortex 25(11):4628–4637. Google Scholar
  11. Colgan N, Siow B, O’Callaghan JM, Harrison IF, Wells JA, Holmes HE, Ismail O, Richardson S, Alexander DC, Collins EC, Fisher EM, Johnson R, Schwarz AJ, Ahmed Z, O’Neill MJ, Murray TK, Zhang H, Lythgoe MF (2016) Application of neurite orientation dispersion and density imaging (NODDI) to a tau pathology model of Alzheimer’s disease. Neuroimage 125:739–744. Google Scholar
  12. Crombe A, Planche V, Raffard G, Bourel J, Dubourdieu N, Panatier A, Fukutomi H, Dousset V, Oliet S, Hiba B, Tourdias T (2018) Deciphering the microstructure of hippocampal subfields with in vivo DTI and NODDI: applications to experimental multiple sclerosis. Neuroimage 172:357–368. Google Scholar
  13. Deshmane A, Gulani V, Griswold MA, Seiberlich N (2012) Parallel MR imaging. J Magn Reson Imaging 36(1):55–72. Google Scholar
  14. Dhital B, Kellner E, Kiselev VG, Reisert M (2018) The absence of restricted water pool in brain white matter. Neuroimage 182:398–406. Google Scholar
  15. Doan V, Kleindienst AM, McMahon EJ, Long BR, Matsushima GK, Taylor LC (2013) Abbreviated exposure to cuprizone is sufficient to induce demyelination and oligodendrocyte loss. J Neurosci Res 91(3):363–373. Google Scholar
  16. Edwards LJ, Pine KJ, Ellerbrock I, Weiskopf N, Mohammadi S (2017) NODDI-DTI: estimating neurite orientation and dispersion parameters from a diffusion tensor in healthy white matter. Front Neurosci 11:720. Google Scholar
  17. Genc S, Malpas CB, Ball G, Silk TJ, Seal ML (2018) Age, sex, and puberty related development of the corpus callosum: a multi-technique diffusion MRI study. Brain Struct Funct 223(6):2753–2765. Google Scholar
  18. Glasser MF, Smith SM, Marcus DS, Andersson JL, Auerbach EJ, Behrens TE, Coalson TS, Harms MP, Jenkinson M, Moeller S, Robinson EC, Sotiropoulos SN, Xu J, Yacoub E, Ugurbil K, Van Essen DC (2016) The human connectome project’s neuroimaging approach. Nat Neurosci 19(9):1175–1187. Google Scholar
  19. Grussu F, Schneider T, Tur C, Yates RL, Tachrount M, Ianus A, Yiannakas MC, Newcombe J, Zhang H, Alexander DC, DeLuca GC, Gandini Wheeler-Kingshott CAM (2017) Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology? Ann Clin Transl Neurol 4(9):663–679. Google Scholar
  20. Guglielmetti C, Le Blon D, Santermans E, Salas-Perdomo A, Daans J, De Vocht N, Shah D, Hoornaert C, Praet J, Peerlings J, Kara F, Bigot C, Mai ZH, Goossens H, Hens N, Hendrix S, Verhoye M, Planas AM, Berneman Z, van der Linden A, Ponsaerts P (2016a) Interleukin-13 immune gene therapy prevents CNS inflammation and demyelination via alternative activation of microglia and macrophages. Glia 64(12):2181–2200. Google Scholar
  21. Guglielmetti C, Veraart J, Roelant E, Mai Z, Daans J, Van Audekerke J, Naeyaert M, Vanhoutte G, Palacios RDY, Praet J, Fieremans E, Ponsaerts P, Sijbers J, Van der Linden A, Verhoye M (2016b) Diffusion kurtosis imaging probes cortical alterations and white matter pathology following cuprizone induced demyelination and spontaneous remyelination. Neuroimage 125:363–377. Google Scholar
  22. Holdsworth SJ, Skare S, Newbould RD, Guzmann R, Blevins NH, Bammer R (2008) Readout-segmented EPI for rapid high resolution diffusion imaging at 3T. Eur J Radiol 65(1):36–46. Google Scholar
  23. Hollingsworth KG (2015) Reducing acquisition time in clinical MRI by data undersampling and compressed sensing reconstruction. Phys Med Biol 60(21):R297–R322. Google Scholar
  24. Holz M, Heil SR, Sacco A (2000) Temperature-dependent self-diffusion coefficients of water and six selected molecular liquids for calibration in accurate H-1 NMR PFG measurements. Phys Chem Chem Phys 2(20):4740–4742. Google Scholar
  25. Hutchinson EB, Avram AV, Irfanoglu MO, Koay CG, Barnett AS, Komlosh ME, Ozarslan E, Schwerin SC, Juliano SL, Pierpaoli C (2017) Analysis of the effects of noise, DWI sampling, and value of assumed parameters in diffusion MRI models. Magn Reson Med 78(5):1767–1780. Google Scholar
  26. Jelescu IO, Veraart J, Adisetiyo V, Milla SS, Novikov DS, Fieremans E (2015) One diffusion acquisition and different white matter models: how does microstructure change in human early development based on WMTI and NODDI? Neuroimage 107:242–256. Google Scholar
  27. Jelescu IO, Veraart J, Fieremans E, Novikov DS (2016) Degeneracy in model parameter estimation for multi-compartmental diffusion in neuronal tissue. NMR Biomed 29(1):33–47. Google Scholar
  28. Johnson GA, Calabrese E, Badea A, Paxinos G, Watson C (2012) A multidimensional magnetic resonance histology atlas of the Wistar rat brain. Neuroimage 62(3):1848–1856. Google Scholar
  29. Kaden E, Kelm ND, Carson RP, Does MD, Alexander DC (2016) Multi-compartment microscopic diffusion imaging. Neuroimage 139:346–359. Google Scholar
  30. Kamagata K, Hatano T, Okuzumi A, Motoi Y, Abe O, Shimoji K, Kamiya K, Suzuki M, Hori M, Kumamaru KK, Hattori N, Aoki S (2016) Neurite orientation dispersion and density imaging in the substantia nigra in idiopathic Parkinson disease. Eur Radiol 26(8):2567–2577. Google Scholar
  31. Kamagata K, Zalesky A, Hatano T, Ueda R, Di Biase MA, Okuzumi A, Shimoji K, Hori M, Caeyenberghs K, Pantelis C, Hattori N, Aoki S (2017) Gray matter abnormalities in idiopathic parkinson’s disease: evaluation by diffusional kurtosis imaging and neurite orientation dispersion and density imaging. Hum Brain Mapp 38(7):3704–3722. Google Scholar
  32. Kleinnijenhuis M, Zerbi V, Kusters B, Slump CH, Barth M, van Cappellen van Walsum AM (2013a) Layer-specific diffusion weighted imaging in human primary visual cortex in vitro. Cortex 49(9):2569–2582. Google Scholar
  33. Kleinnijenhuis M, Zhang H, Wiedermann D, Kusters B, Norris D, van Cappellen van Walsum AM (2013b) Detailed laminar characteristics of the human neocortex revealed by NODDI and histology. In: Proceedings 19th Annual Meeting of the OHBM, pp 3815Google Scholar
  34. Koay CG, Ozarslan E, Johnson KM, Meyerand ME (2012) Sparse and optimal acquisition design for diffusion MRI and beyond. Med Phys 39(5):2499–2511. Google Scholar
  35. Lampinen B, Szczepankiewicz F, Martensson J, van Westen D, Sundgren PC, Nilsson M (2017) Neurite density imaging versus imaging of microscopic anisotropy in diffusion MRI: a model comparison using spherical tensor encoding. Neuroimage 147:517–531. Google Scholar
  36. Larkman DJ, Nunes RG (2007) Parallel magnetic resonance imaging. Phys Med Biol 52(7):R15–R55. Google Scholar
  37. Le Bihan D, Mangin JF, Poupon C, Clark CA, Pappata S, Molko N, Chabriat H (2001) Diffusion tensor imaging: concepts and applications. J Magn Reson Imaging 13(4):534–546Google Scholar
  38. Lin TH, Chiang CW, Perez-Torres CJ, Sun P, Wallendorf M, Schmidt RE, Cross AH, Song SK (2017) Diffusion MRI quantifies early axonal loss in the presence of nerve swelling. J Neuroinflammation 14:78. Google Scholar
  39. Lustig M, Donoho D, Pauly JM (2007) Sparse MRI: the application of compressed sensing for rapid MR imaging. Magn Reson Med 58(6):1182–1195. Google Scholar
  40. Matsushima GK, Morell P (2001) The neurotoxicant, cuprizone, as a model to study demyelination and remyelination in the central nervous system. Brain Pathol 11(1):107–116Google Scholar
  41. Nikic I, Merkler D, Sorbara C, Brinkoetter M, Kreutzfeldt M, Bareyre FM, Bruck W, Bishop D, Misgeld T, Kerschensteiner M (2011) A reversible form of axon damage in experimental autoimmune encephalomyelitis and multiple sclerosis. Nat Med 17(4):495. Google Scholar
  42. Petiet AE, Kaufman MH, Goddeeris MM, Brandenburg J, Elmore SA, Johnson GA (2008) High-resolution magnetic resonance histology of the embryonic and neonatal mouse: a 4D atlas and morphologic database. Proc Natl Acad Sci USA 105(34):12331–12336. Google Scholar
  43. Rane S, Duong TQ (2011) Comparison of in vivo and ex vivo diffusion tensor imaging in rhesus macaques at short and long diffusion times. Open Neuroimag J 5:172–178. Google Scholar
  44. Sato K, Kerever A, Kamagata K, Tsuruta K, Irie R, Tagawa K, Okazawa H, Arikawa-Hirasawa E, Nitta N, Aoki I, Aoki S (2017) Understanding microstructure of the brain by comparison of neurite orientation dispersion and density imaging (NODDI) with transparent mouse brain. Acta Radiol Open 6(4):2058460117703816. Google Scholar
  45. Schneider T, Brownlee W, Zhang H, Ciccarelli O, Miller DH, Wheeler-Kingshott CG (2017) Sensitivity of multi-shell NODDI to multiple sclerosis white matter changes: a pilot study. Funct Neurol 32(2):97–101Google Scholar
  46. Sepehrband F, Clark KA, Ullmann JF, Kurniawan ND, Leanage G, Reutens DC, Yang Z (2015) Brain tissue compartment density estimated using diffusion-weighted MRI yields tissue parameters consistent with histology. Hum Brain Mapp 36(9):3687–3702. Google Scholar
  47. Sepehrband F, Alexander DC, Kurniawan ND, Reutens DC, Yang Z (2016) Towards higher sensitivity and stability of axon diameter estimation with diffusion-weighted MRI. NMR Biomed 29(3):293–308. Google Scholar
  48. Sepehrband F, O’Brien K, Barth M (2017) A time-efficient acquisition protocol for multipurpose diffusion-weighted microstructural imaging at 7 Tesla. Magn Reson Med 78(6):2170–2184. Google Scholar
  49. Simons M, Misgeld T, Kerschensteiner M (2014) A unified cell biological perspective on axon-myelin injury. J Cell Biol 206(3):335–345. Google Scholar
  50. Skripuletz T, Lindner M, Kotsiari A, Garde N, Fokuhl J, Linsmeier F, Trebst C, Stangel M (2008) Cortical demyelination is prominent in the murine cuprizone model and is strain-dependent. Am J Pathol 172(4):1053–1061. Google Scholar
  51. Stejskal EO, Tanner JE (1965) Spin diffusion measurements: spin echoes in the presence of a time-dependent field gradient. J Chem Phys 42(1):288–292. Google Scholar
  52. Sun SW, Liang HF, Trinkaus K, Cross AH, Armstrong RC, Song SK (2006) Noninvasive detection of cuprizone induced axonal damage and demyelination in the mouse corpus callosum. Magn Reson Med 55(2):302–308. Google Scholar
  53. Tagge I, O’Connor A, Chaudhary P, Pollaro J, Berlow Y, Chalupsky M, Bourdette D, Woltjer R, Johnson M, Rooney W (2016) Spatio-temporal patterns of demyelination and remyelination in the cuprizone mouse model. PLoS One 11(4):e0152480. Google Scholar
  54. Tariq M, Schneider T, Alexander DC, Gandini Wheeler-Kingshott CA, Zhang H (2016) Bingham-NODDI: mapping anisotropic orientation dispersion of neurites using diffusion MRI. Neuroimage 133:207–223. Google Scholar
  55. Thiessen JD, Zhang Y, Zhang H, Wang L, Buist R, Del Bigio MR, Kong J, Li XM, Martin M (2013) Quantitative MRI and ultrastructural examination of the cuprizone mouse model of demyelination. NMR Biomed 26(11):1562–1581. Google Scholar
  56. Vu AT, Auerbach E, Lenglet C, Moeller S, Sotiropoulos SN, Jbabdi S, Andersson J, Yacoub E, Ugurbil K (2015) High resolution whole brain diffusion imaging at 7T for the Human Connectome Project. Neuroimage 122:318–331. Google Scholar
  57. Wang N, Anderson RJ, Badea A, Cofer G, Dibb R, Qi Y, Johnson GA (2018a) Whole mouse brain structural connectomics using magnetic resonance histology. Brain Struct Funct 223(9):4323–4335. Google Scholar
  58. Wang N, Badar F, Xia Y (2018b) Compressed sensing in quantitative determination of GAG concentration in cartilage by microscopic MRI. Magn Reson Med 79(6):3163–3171. Google Scholar
  59. Wang N, Mirando AJ, Cofer G, Qi Y, Hilton MJ, Johnson GA (2019) Diffusion tractography of the rat knee at microscopic resolution. Magn Reson Med 81(6):3775–3786. Google Scholar
  60. Xie M, Tobin JE, Budde MD, Chen CI, Trinkaus K, Cross AH, McDaniel DP, Song SK, Armstrong RC (2010) Rostrocaudal analysis of corpus callosum demyelination and axon damage across disease stages refines diffusion tensor imaging correlations with pathological features. J Neuropathol Exp Neurol 69(7):704–716. Google Scholar
  61. Yeh FC, Wedeen VJ, Tseng WY (2011) Estimation of fiber orientation and spin density distribution by diffusion deconvolution. Neuroimage 55(3):1054–1062. Google Scholar
  62. Yeh FC, Verstynen TD, Wang Y, Fernandez-Miranda JC, Tseng WY (2013) Deterministic diffusion fiber tracking improved by quantitative anisotropy. PLoS One 8(11):e80713. Google Scholar
  63. Zhang H, Hubbard PL, Parker GJ, Alexander DC (2011) Axon diameter mapping in the presence of orientation dispersion with diffusion MRI. Neuroimage 56(3):1301–1315. Google Scholar
  64. Zhang H, Schneider T, Wheeler-Kingshott CA, Alexander DC (2012a) NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. Neuroimage 61(4):1000–1016. Google Scholar
  65. Zhang J, Jones MV, McMahon MT, Mori S, Calabresi PA (2012b) In vivo and ex vivo diffusion tensor imaging of cuprizone-induced demyelination in the mouse corpus callosum. Magn Reson Med 67(3):750–759. Google Scholar
  66. Zolal A, Sames M, Burian M, Novakova M, Malucelli A, Hejcl A, Bartos R, Vachata P, Derner M (2012) The effect of a gadolinium-based contrast agent on diffusion tensor imaging. Eur J Radiol 81(8):1877–1882. Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Center for In Vivo Microscopy, Department of Radiology, Duke Medical CenterDuke UniversityDurhamUSA
  2. 2.Department of RadiologyDuke University School of MedicineDurhamUSA
  3. 3.Department of Biomedical Engineering, School of MedicineTsinghua UniversityBeijingChina
  4. 4.Department of Biomedical EngineeringDuke UniversityDurhamUSA
  5. 5.Department of NeurologyDuke University School of MedicineDurhamUSA

Personalised recommendations