Skip to main content
Log in

Hoe magnetisme en diffusie kunnen bijdragen aan hersenonderzoek: toepassingen van diffusie-MRI-tractografie

  • Artikel
  • Published:
Neuropraxis

Samenvatting

Met MRI kunnen zachte weefsels in het lichaam afgebeeld worden op een niet-invasieve manier. MRI is daardoor onmisbaar bij de diagnose van veel ziektes. Diffusie-MRI is een relatief nieuwe techniek die, in tegenstelling tot conventionele MRI-technieken, ook de architectuur van weefsels in kaart kan brengen. Hiertoe wordt de MRI-sequentie gevoelig gemaakt voor de willekeurige beweging van deeltjes (diffusie). Watermoleculen bewegen zich in weefsels voort op een dergelijke willekeurige wijze, maar worden daar ook gehinderd door verschillende microstructuren. De eigenschappen van onderliggend weefsel bepalen dus de grootte van diffusie, wat met diffusie-MRI-scans in kaart kan worden gebracht. Veel lichaamsweefsels zijn opgebouwd uit vezelachtige structuren, bijvoorbeeld zenuwvezels in de witte stof van de hersenen. Diffusie-MRI-tractografie is het reconstrueren en visualiseren van vezelpaden die geassocieerd kunnen worden met deze onderliggende zenuwbanen. Hierdoor is het mogelijk om specifieke verbindingen tussen verschillende hersengebieden af te beelden en kwantitatief te bestuderen. Dit artikel gaat in op de werking van diffusie-MRI-tractografie en bespreekt (klinische) toepassingen, valkuilen, en beperkingen die gerelateerd zijn aan deze techniek.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figuur 1
Figuur 2
Figuur 3
Figuur 4
Figuur 5
Figuur 6
Figuur 7
Figuur 8
Figuur 9
Figuur 10
Figuur 11
Figuur 12

Notes

  1. De diffusiecoëfficiënt die geschat wordt uit diffusiebeelden wordt vaak de schijnbare diffusiecoëfficiënt genoemd. Dit komt omdat de diffusie afhangt van een groot aantal factoren, zoals temperatuur en de omliggende microstructuren (bijvoorbeeld celmembranen en myelineschedes).

  2. Met een volume wordt hier een drie-dimensionale MRI-scan bedoeld.

Literatuur

  1. Aarnink, S.H., Vos, S.B., Leemans, A., Jernigan, T.L., Madsen, K.S. & Baare, W.F., 2014. Automated longitudinal intra-subject analysis (ALISA) for diffusion MRI tractography. Neuroimage, 86, 404–416.

    Article  PubMed  Google Scholar 

  2. Alexander, A.L., 2010. Deterministic White Matter Tractography. In: Jones, D.K. (Ed.), Diffusion MRI: Theory, Methods, and Applications. Oxford University Press.

  3. Basser, P.J., Mattiello, J. & LeBihan, D., 1994. Estimation of the effective self-diffusion tensor from the NMR spin echo. Journal of Magnetic Resonance, series B, 103, 247–254.

    Article  CAS  Google Scholar 

  4. Beaulieu, C., 2002. The basis of anisotropic water diffusion in the nervous system—a technical review. NMR in Biomedine, 15, 435–455.

    Article  Google Scholar 

  5. Chang, L.C., Jones, D.K. & Pierpaoli, C., 2005. RESTORE: robust estimation of tensors by outlier rejection. Magnetic Resonance in Medicine, 53, 1088–1095.

    Article  PubMed  Google Scholar 

  6. Chen, F., Zhang, X., Li, M., Wang, R., Wang, H.T., Zhu, F., Lu, D.J., Zhao, H., Li, J.W., Xu, Y., Zhu, B. & Zhang, B., 2012. Axial diffusivity and tensor shape as early markers to assess cerebral white matter damage caused by brain tumors using quantitative diffusion tensor tractography. CNS Neuroscience & Therapeutics, 18, 667–673.

    Article  Google Scholar 

  7. Chun, T., Filippi, C.G., Zimmerman, R.D. & Ulug, A.M., 2000. Diffusion changes in the aging human brain. American Journal of Neuroradiology, 21, 1078–1083.

    CAS  PubMed  Google Scholar 

  8. Clayden, J.D., Jentschke, S., Munoz, M., Cooper, J.M., Chadwick, M.J., Banks, T., Clark, C.A. & Vargha-Khadem, F., 2012. Normative development of white matter tracts: similarities and differences in relation to age, gender, and intelligence. Cerebral Cortex, 22, 1738–1747.

    Article  PubMed  Google Scholar 

  9. Deprez, S., Billiet, T., Sunaert, S. & Leemans, A., 2013. Diffusion tensor MRI of chemotherapy-induced cognitive impairment in non-CNS cancer patients: a review. Brain Imaging and Behaviour, 7, 409–435.

    Article  Google Scholar 

  10. Descoteaux, M., Angelino, E., Fitzgibbons, S. & Deriche, R., 2007. Regularized, fast, and robust analytical Q-ball imaging. Magnetic Resonance in Medicine, 58, 497–510.

    Article  PubMed  Google Scholar 

  11. Ferda, J., Kastner, J., Mukensnabl, P., Choc, M., Horemuzova, J., Ferdova, E. & Kreuzberg, B., 2010. Diffusion tensor magnetic resonance imaging of glial brain tumors. European Journal of Radiology, 74, 428–436.

    Article  PubMed  Google Scholar 

  12. Gideon, P., Thomsen, C. & Henriksen, O., 1994. Increased self-diffusion of brain water in normal aging. Journal of Magnetic Resonance Imaging, 4, 185–188.

    Article  CAS  PubMed  Google Scholar 

  13. Huppi, P.S., Maier, S.E., Peled, S., Zientara, G.P., Barnes, P.D., Jolesz, F.A. & Volpe, J.J., 1998. Microstructural development of human newborn cerebral white matter assessed in vivo by diffusion tensor magnetic resonance imaging. Pediatric Research, 44, 584–590.

    Article  CAS  PubMed  Google Scholar 

  14. Jeurissen, B., Leemans, A., Jones, D.K., Tournier, J.D. & Sijbers, J., 2011. Probabilistic fiber tracking using the residual bootstrap with constrained spherical deconvolution. Human Brain Mapping, 32, 461–479.

    Article  PubMed  Google Scholar 

  15. Jeurissen, B., Leemans, A., Tournier, J.D., Jones, D.K. & Sijbers, J., 2013. Investigating the prevalence of complex fiber configurations in white matter tissue with diffusion magnetic resonance imaging. Human Brain Mapping, 34, 2747–2766.

    Article  PubMed  Google Scholar 

  16. Jones, D.K., 2010a. Challenges and limitations of quantifying brain connectivity in vivo with diffusion MRI. Imaging, 2, 341–355.

    Article  Google Scholar 

  17. Jones, D.K., 2010b. Diffusion MRI: Theory, Methods, and Applications. Oxford University Press, VS.

    Book  Google Scholar 

  18. Jones, D.K. & Cercignani, M., 2010. Twenty-five pitfalls in the analysis of diffusion MRI data. NMR in Biomedicine, 23, 803–820.

    Article  PubMed  Google Scholar 

  19. Jones, D.K., Knosche, T.R. & Turner, R., 2013. White matter integrity, fiber count, and other fallacies: the do’s and don’ts of diffusion MRI. Neuroimage, 73, 239–254.

    Article  PubMed  Google Scholar 

  20. Kreher, B.W., Mader, I. & Kiselev, V.G., 2008. Gibbs tracking: a novel approach for the reconstruction of neuronal pathways. Magnetic Resonance in Medicine, 60, 953–963.

    Article  CAS  PubMed  Google Scholar 

  21. Langen, M., Leemans, A., Johnston, P., Ecker, C., Daly, E., Murphy, C.M., Dell’acqua, F., Durston, S. & Murphy, D.G., 2012. Fronto-striatal circuitry and inhibitory control in autism: findings from diffusion tensor imaging tractography. Cortex, 48, 183–193.

    Article  PubMed  Google Scholar 

  22. Lazar, M., Weinstein, D.M., Tsuruda, J.S., Hasan, K.M., Arfanakis, K., Meyerand, M.E., Badie, B., Rowley, H.A., Haughton, V., Field, A. ? Alexander, A.L., 2003. White matter tractography using diffusion tensor deflection. Human Brain Mapping, 18, 306–321.

    Article  PubMed  Google Scholar 

  23. Mori, S., Crain, B.J., Chacko, V.P. & Zijl, P.C. van, 1999. Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Annals of Neurology, 45, 265–269.

  24. Özarslan, E., Koay, C.G., Shepherd, T.M., Komlosh, M.E., Irfanoglu, M.O., Pierpaoli, C. & Basser, P.J., 2013. Mean apparent propagator (MAP) MRI: a novel diffusion imaging method for mapping tissue microstructure. Neuroimage, 78, 16–32.

    Article  PubMed  Google Scholar 

  25. Parker, G.J.M., 2010. Probabilistic Fiber Tracking. In: Jones, D.K. (Ed.), Diffusion MRI: Theory, Methods, and Applications. Oxford University Press.

  26. Pierpaoli, C., 2010. Artifacts in Diffusion MRI. In: Jones, D.K. (Ed.), Diffusion MRI: Theory, Methods, and Applications. Oxford University Press.

  27. Pierpaoli, C., Barnett, A., Pajevic, S., Chen, R., Penix, L.R., Virta, A., Basser, P., 2001. Water diffusion changes in Wallerian degeneration and their dependence on white matter architecture. Neuroimage, 13, 1174–1185.

    Article  CAS  PubMed  Google Scholar 

  28. Reijmer, Y.D., Leemans, A., Heringa, S.M., Wielaard, I., Jeurissen, B., Koek, H.L. & Biessels, G.J., 2012. Improved sensitivity to cerebral white matter abnormalities in Alzheimer’s disease with spherical deconvolution based tractography. PLoS One, 7, e44074.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  29. Roine, U., Roine, T., Salmi, J., Nieminen-Von, W.T., Leppamaki, S., Rintahaka, P., Tani, P., Leemans, A. & Sams, M., 2013. Increased coherence of white matter fiber tract organization in adults with asperger syndrome: a diffusion tensor imaging study. Autism Research, 6, 642–650.

    Article  PubMed  Google Scholar 

  30. Schneider, J.F., Confort-Gouny, S., Le, F.Y., Viout, P., Bennathan, M., Chapon, F., Fogliarini, C., Cozzone, P. & Girard, N., 2007. Diffusion-weighted imaging in normal fetal brain maturation. European Radiology, 17, 2422–2429.

    Article  CAS  PubMed  Google Scholar 

  31. Tax, C.M.W., 2012. Improved Reconstruction of the Optic Radiation for Epilepsy Surgery. Master thesis, Eindhoven University of Technology.

  32. Tax, C.M.W., Duits, R., Romeny, B.M., Vilanova, A. & Ossenblok, P., 2012. Tractography of the Optic Radiation for Vision Sparing Epilepsy Surgery. In: Proceedings of the IEEE ICIA, 441–445.

  33. Tax, C.M.W., Jeurissen, B., Vos, S.B., Viergever, M.A. & Leemans, A., 2013. Recursive calibration of the fiber response function for spherical deconvolution of diffusion MRI data. Neuroimage 86, 67–80.

    Article  PubMed  Google Scholar 

  34. Tax, C.M.W., Otte, W.M., Viergever, M.A., Dijkhuizen, R.M. & Leemans, A., 2014. REKINDLE: Robust Extraction of Kurtosis INDices with Linear Estimation. Magnetic Resonance in Medicine. doi: 10.1002/mrm.25165.

    PubMed  Google Scholar 

  35. Tournier, J.D., Calamante, F. & Connelly, A., 2007. Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution. Neuroimage, 35, 1459–1472.

    Article  PubMed  Google Scholar 

  36. Tournier, J.D., Mori, S. & Leemans, A., 2011. Diffusion tensor imaging and beyond. Magnetic Resonance in Medicine, 65, 1532–1556.

    Article  PubMed Central  PubMed  Google Scholar 

  37. Tuch, D.S., 2004. Q-ball imaging. Magnetic Resonance in Medicine, 52, 1358–1372.

    Article  PubMed  Google Scholar 

  38. Jagt, P.K. van der, Dik, P., Froeling, M., Kwee, T.C., Nievelstein, R.A., ten, H.B. & Leemans, A., 2012. Architectural configuration and microstructural properties of the sacral plexus: a diffusion tensor MRI and fiber tractography study. Neuroimage, 62, 1792–1799.

  39. Zijden, J.P. van der, Toorn, A. van der, Marel, K. van der & Dijkhuizen, R.M., 2008. Longitudinal in vivo MRI of alterations in perilesional tissue after transient ischemic stroke in rats. Experimental Neurology, 212, 207–212.

  40. Wang, H.C., Hsu, J.L. & Leemans, A., 2012. Diffusion tensor imaging of vascular parkinsonism: structural changes in cerebral white matter and the association with clinical severity. Archives of Neurology, 69, 1340–1348.

    Article  PubMed  Google Scholar 

  41. Wedeen, V.J., Hagmann, P., Tseng, W.Y., Reese, T.G. & Weisskoff, R.M., 2005. Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging. Magnetic Resonance in Medicine, 54, 1377–1386.

    Article  PubMed  Google Scholar 

  42. Wimberger, D.M., Roberts, T.P., Barkovich, A.J., Prayer, L.M., Moseley, M.E &, Kucharczyk, J., 1995. Identification of ‘premyelination’ by diffusion-weighted MRI. Journal of Computer Assisted Tomography, 19, 28–33.

  43. Wu, O., Nentwich, L., Chutinet, A. & Bayrlee, A., 2010. Diffusion in Acute Stroke. In: Jones, D.K. (Ed.), Diffusion MRI: Theory, Methods, and Applications. Oxford University Press.

  44. Yamada, K., Sakai, K., Akazawa, K., Yuen, S. & Nishimura, T., 2009. MR tractography: a review of its clinical applications. Magnetic Resonance in Medical Sciences, 8, 165–174.

    Article  PubMed  Google Scholar 

  45. Yasmin, H., Nakata, Y., Aoki, S., Abe, O., Sato, N., Nemoto, K., Arima, K., Furuta, N., Uno, M., Hirai, S., Masutani, Y. & Ohtomo, K., 2008. Diffusion abnormalities of the uncinate fasciculus in Alzheimer’s disease: diffusion tensor tract-specific analysis using a new method to measure the core of the tract. Neuroradiology, 50, 293–299.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chantal M. W. Tax.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tax, C.M.W., Leemans, A. Hoe magnetisme en diffusie kunnen bijdragen aan hersenonderzoek: toepassingen van diffusie-MRI-tractografie. Neuroprax 18, 92–105 (2014). https://doi.org/10.1007/s12474-014-0050-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12474-014-0050-3

Navigation