Skip to main content
SpringerLink
Log in

Pattern of Cerebellar Atrophy in Friedreich’s Ataxia—Using the SUIT Template

  • Original Paper
  • Published:
The Cerebellum Aims and scope Submit manuscript

Abstract

Whole-brain voxel-based morphometry (VBM) studies revealed patterns of patchy atrophy within the cerebellum of Friedreich’s ataxia patients, missing clear clinico-anatomic correlations. Studies so far are lacking an appropriate registration to the infratentorial space. To circumvent these limitations, we applied a high-resolution atlas template of the human cerebellum and brainstem (SUIT template) to characterize regional cerebellar atrophy in Friedreich’s ataxia (FRDA) on 3-T MRI data. We used a spatially unbiased voxel-based morphometry approach together with T2-based manual segmentation, T2 histogram analysis, and atlas generation of the dentate nuclei in a representative cohort of 18 FRDA patients and matched healthy controls. We demonstrate that the cerebellar volume in FRDA is generally not significantly different from healthy controls but mild lobular atrophy develops beyond normal aging. The medial parts of lobule VI, housing the somatotopic representation of tongue and lips, are the major site of this lobular atrophy, which possibly reflects speech impairment. Extended white matter affection correlates with disease severity across and beyond the cerebellar inflow and outflow tracts. The dentate nucleus, as a major site of cerebellar degeneration, shows a mean volume loss of about 30%. Remarkably, not the atrophy but the T2 signal decrease of the dentate nuclei highly correlates with disease duration and severity.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data Availability

The dentate atlases of FRDA patients and normal controls will be made available by the authors on request. Requests can be made via e-mail to either Tobias Lindig (Tobias.Lindig@med.uni-tuebingen.de) or Benjamin Bender (Benjamin.Bender@med.uni-tuebingen.de).

Abbreviations

CSF:

Cerebrospinal fluid

DN:

Dentate nucleus

DTI:

Diffusion tensor imaging

FRDA:

Friedreich’s ataxia

FSL:

FMRIB software library

FWE:

Family-wise error

FWHM:

Full width at half maximum

GAA:

Guanine-adenine-adenine

GM:

Gray matter

QSM:

Quantitative susceptibility mapping

ROI:

Region of interest

SARA:

Scale for the assessment and rating of ataxia

SD:

Standard deviation

SUIT:

Spatially unbiased infratentorial template

TFCE:

Threshold-free cluster enhancement

TIV:

Total intracranial volume

VBM:

Voxel-based morphometry

WM:

White matter

References

  1. Reetz K, Dogan I, Hohenfeld C, Didszun C, Giunti P, Mariotti C, et al. Nonataxia symptoms in Friedreich ataxia: report from the registry of the European Friedreich’s Ataxia Consortium for Translational Studies (EFACTS). Neurology. 2018;91(10):e917–e30.

    Article  Google Scholar 

  2. Reetz K, Dogan I, Costa AS, Dafotakis M, Fedosov K, Giunti P, et al. Biological and clinical characteristics of the European Friedreich’s Ataxia Consortium for Translational Studies (EFACTS) cohort: a cross-sectional analysis of baseline data. Lancet Neurol. 2015;14(2):174–82.

    Article  Google Scholar 

  3. Schmucker S, Puccio H. Understanding the molecular mechanisms of Friedreich’s ataxia to develop therapeutic approaches. Hum Mol Genet. 2010;19(R1):R103–10.

    Article  CAS  Google Scholar 

  4. Pastore A, Puccio H. Frataxin: a protein in search for a function. J Neurochem. 2013;126(Suppl 1):43–52.

    Article  CAS  Google Scholar 

  5. Koeppen AH, Mazurkiewicz JE. Friedreich ataxia: neuropathology revised. J Neuropathol Exp Neurol. 2013;72(2):78–90.

    Article  CAS  Google Scholar 

  6. Pagani E, Ginestroni A, Della Nave R, Agosta F, Salvi F, De Michele G, et al. Assessment of brain white matter fiber bundle atrophy in patients with Friedreich ataxia. Radiology. 2010;255(3):882–9.

    Article  Google Scholar 

  7. Della Nave R, Ginestroni A, Tessa C, Salvatore E, Bartolomei I, Salvi F, et al. Brain white matter tracts degeneration in Friedreich ataxia. An in vivo MRI study using tract-based spatial statistics and voxel-based morphometry. NeuroImage. 2008;40(1):19–25.

    Article  Google Scholar 

  8. Solbach K, Kraff O, Minnerop M, Beck A, Schols L, Gizewski ER, et al. Cerebellar pathology in Friedreich’s ataxia: atrophied dentate nuclei with normal iron content. Neuroimage Clin. 2014;6:93–9.

    Article  CAS  Google Scholar 

  9. Waldvogel D, van Gelderen P, Hallett M. Increased iron in the dentate nucleus of patients with Friedrich’s ataxia. Ann Neurol. 1999;46(1):123–5.

    Article  CAS  Google Scholar 

  10. Rezende TJ, Silva CB, Yassuda CL, Campos BM, D’Abreu A, Cendes F, et al. Longitudinal magnetic resonance imaging study shows progressive pyramidal and callosal damage in Friedreich’s ataxia. Mov Disord. 2016;31(1):70–8.

    Article  Google Scholar 

  11. Selvadurai LP, Harding IH, Corben LA, Stagnitti MR, Storey E, Egan GF, et al. Cerebral and cerebellar grey matter atrophy in Friedreich ataxia: the IMAGE-FRDA study. J Neurol. 2016;263:2215–23.

    Article  Google Scholar 

  12. Della Nave R, Ginestroni A, Giannelli M, Tessa C, Salvatore E, Salvi F, et al. Brain structural damage in Friedreich’s ataxia. J Neurol Neurosurg Psychiatry. 2008;79(1):82–5.

    Article  CAS  Google Scholar 

  13. Burk K, Malzig U, Wolf S, Heck S, Dimitriadis K, Schmitz-Hubsch T, et al. Comparison of three clinical rating scales in Friedreich ataxia (FRDA). Mov Disord. 2009;24(12):1779–84.

    Article  Google Scholar 

  14. Schmitz-Hubsch T, du Montcel ST, Baliko L, Berciano J, Boesch S, Depondt C, et al. Scale for the assessment and rating of ataxia: development of a new clinical scale. Neurology. 2006;66(11):1717–20.

    Article  CAS  Google Scholar 

  15. Diedrichsen J. A spatially unbiased atlas template of the human cerebellum. NeuroImage. 2006;33(1):127–38.

    Article  Google Scholar 

  16. Diedrichsen J, Balsters JH, Flavell J, Cussans E, Ramnani N. A probabilistic MR atlas of the human cerebellum. NeuroImage. 2009;46(1):39–46.

    Article  Google Scholar 

  17. Ashburner J, Friston KJ. Voxel-based morphometry—the methods. NeuroImage. 2000;11(6):805–21.

    Article  CAS  Google Scholar 

  18. Ashburner J, Friston KJ. Unified segmentation. NeuroImage. 2005;26(3):839–51.

    Article  Google Scholar 

  19. Rorden C, Brett M. Stereotaxic display of brain lesions. Behav Neurol. 2000;12(4):191–200.

    Article  Google Scholar 

  20. Salimi-Khorshidi G, Smith SM, Nichols TE. Adjusting the effect of nonstationarity in cluster-based and TFCE inference. NeuroImage. 2011;54(3):2006–19.

    Article  Google Scholar 

  21. Smith SM, Nichols TE. Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. NeuroImage. 2009;44(1):83–98.

    Article  Google Scholar 

  22. Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE. Permutation inference for the general linear model. NeuroImage. 2014;92:381–97.

    Article  Google Scholar 

  23. Diedrichsen J, Zotow E. Surface-based display of volume-averaged cerebellar imaging data. PLoS One. 2015;10(7):e0133402.

    Article  Google Scholar 

  24. Ridgway GR, Barnes J, Pepple T, Fox N, editors. Estimation of total intracranial volume: a comparison of methods. AAICAD Alzheimer’s imaging consortium; Paris, France; 2011.

  25. Malone IB, Leung KK, Clegg S, Barnes J, Whitwell JL, Ashburner J, et al. Accurate automatic estimation of total intracranial volume: a nuisance variable with less nuisance. NeuroImage. 2015;104:366–72.

    Article  Google Scholar 

  26. Yushkevich PA, Piven J, Hazlett HC, Smith RG, Ho S, Gee JC, et al. User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. NeuroImage. 2006;31(3):1116–28.

    Article  Google Scholar 

  27. Diedrichsen J, Maderwald S, Kuper M, Thurling M, Rabe K, Gizewski ER, et al. Imaging the deep cerebellar nuclei: a probabilistic atlas and normalization procedure. NeuroImage. 2011;54(3):1786–94.

    Article  CAS  Google Scholar 

  28. Harding IH, Corben LA, Storey E, Egan GF, Stagnitti MR, Poudel GR, et al. Fronto-cerebellar dysfunction and dysconnectivity underlying cognition in friedreich ataxia: the IMAGE-FRDA study. Hum Brain Mapp. 2016;37(1):338–50.

    Article  Google Scholar 

  29. Stefanescu MR, Dohnalek M, Maderwald S, Thurling M, Minnerop M, Beck A, et al. Structural and functional MRI abnormalities of cerebellar cortex and nuclei in SCA3, SCA6 and Friedreich’s ataxia. Brain. 2015;138(Pt 5):1182–97.

    Article  Google Scholar 

  30. Ginestroni A, Diciotti S, Cecchi P, Pesaresi I, Tessa C, Giannelli M, et al. Neurodegeneration in Friedreich’s ataxia is associated with a mixed activation pattern of the brain. A fMRI study. Hum Brain Mapp. 2012;33(8):1780–91.

    Article  Google Scholar 

  31. Deistung A, Stefanescu MR, Ernst TM, Schlamann M, Ladd ME, Reichenbach JR, et al. Structural and functional magnetic resonance imaging of the cerebellum: considerations for assessing cerebellar ataxias. Cerebellum. 2016;15(1):21–5.

    Article  Google Scholar 

  32. Dogan I, Tinnemann E, Romanzetti S, Mirzazade S, Costa AS, Werner CJ, et al. Cognition in Friedreich’s ataxia: a behavioral and multimodal imaging study. Ann Clin Transl Neurol. 2016;3(8):572–87.

    Article  Google Scholar 

  33. Selvadurai LP, Harding IH, Corben LA, Georgiou-Karistianis N. Cerebral abnormalities in Friedreich ataxia: a review. Neurosci Biobehav Rev. 2018;84:394–406.

    Article  Google Scholar 

  34. Grodd W, Hulsmann E, Lotze M, Wildgruber D, Erb M. Sensorimotor mapping of the human cerebellum: fMRI evidence of somatotopic organization. Hum Brain Mapp. 2001;13(2):55–73.

    Article  CAS  Google Scholar 

  35. Buckner RL, Krienen FM, Castellanos A, Diaz JC, Yeo BT. The organization of the human cerebellum estimated by intrinsic functional connectivity. J Neurophysiol. 2011;106(5):2322–45.

    Article  Google Scholar 

  36. Ackermann H, Brendel B. Cerebellar contributions to speech and language. In: Hickok G, Small SL, editors. Neurobiology of language. Elsevier; 2016.

  37. Schols L, Amoiridis G, Przuntek H, Frank G, Epplen JT, Epplen C. Friedreich’s ataxia. Revision of the phenotype according to molecular genetics. Brain. 1997;120(Pt 12):2131–40.

    Article  Google Scholar 

  38. Delatycki MB, Paris DB, Gardner RJ, Nicholson GA, Nassif N, Storey E, et al. Clinical and genetic study of Friedreich ataxia in an Australian population. Am J Med Genet. 1999;87(2):168–74.

    Article  CAS  Google Scholar 

  39. Brendel B, Ackermann H, Berg D, Lindig T, Scholderle T, Schols L, et al. Friedreich ataxia: dysarthria profile and clinical data. Cerebellum. 2013;12(4):475–84.

    Article  CAS  Google Scholar 

  40. Folker J, Murdoch B, Cahill L, Delatycki M, Corben L, Vogel A. Dysarthria in Friedreich’s ataxia: a perceptual analysis. Folia Phoniatr Logop. 2010;62(3):97–103.

    Article  Google Scholar 

  41. Mascalchi M. The cerebellum looks normal in Friedreich ataxia. AJNR Am J Neuroradiol. 2013;34(2):E22.

    Article  CAS  Google Scholar 

  42. Anheim M, Tranchant C, Koenig M. The autosomal recessive cerebellar ataxias. N Engl J Med. 2012;366(7):636–46.

    Article  CAS  Google Scholar 

  43. Jacobi H, Hauser TK, Giunti P, Globas C, Bauer P, Schmitz-Hubsch T, et al. Spinocerebellar ataxia types 1, 2, 3 and 6: the clinical spectrum of ataxia and morphometric brainstem and cerebellar findings. Cerebellum. 2012;11(1):155–66.

    Article  Google Scholar 

  44. Koeppen AH, Davis AN, Morral JA. The cerebellar component of Friedreich’s ataxia. Acta Neuropathol. 2011;122(3):323–30.

    Article  Google Scholar 

  45. Koeppen AH, Ramirez RL, Becker AB, Feustel PJ, Mazurkiewicz JE. Friedreich ataxia: failure of GABA-ergic and glycinergic synaptic transmission in the dentate nucleus. J Neuropathol Exp Neurol. 2015;74(2):166–76.

    Article  CAS  Google Scholar 

  46. Boddaert N, Le Quan Sang KH, Rotig A, Leroy-Willig A, Gallet S, Brunelle F, et al. Selective iron chelation in Friedreich ataxia: biologic and clinical implications. Blood. 2007;110(1):401–8.

    Article  CAS  Google Scholar 

  47. Bonilha da Silva C, Bergo FP, D’Abreu A, Cendes F, Lopes-Cendes I, Franca MC Jr. Dentate nuclei T2 relaxometry is a reliable neuroimaging marker in Friedreich’s ataxia. Eur J Neurol. 2014;21(8):1131–6.

    Article  CAS  Google Scholar 

  48. Koeppen AH, Michael SC, Knutson MD, Haile DJ, Qian J, Levi S, et al. The dentate nucleus in Friedreich’s ataxia: the role of iron-responsive proteins. Acta Neuropathol. 2007;114(2):163–73.

    Article  CAS  Google Scholar 

  49. Koeppen AH, Ramirez RL, Yu D, Collins SE, Qian J, Parsons PJ, et al. Friedreich’s ataxia causes redistribution of iron, copper, and zinc in the dentate nucleus. Cerebellum. 2012;11(4):845–60.

    Article  CAS  Google Scholar 

  50. Harding IH, Raniga P, Delatycki MB, Stagnitti MR, Corben LA, Storey E, et al. Tissue atrophy and elevated iron concentration in the extrapyramidal motor system in Friedreich ataxia: the IMAGE-FRDA study. J Neurol Neurosurg Psychiatry. 2016;87:1261–3.

    Article  Google Scholar 

  51. van Baarsen KM, Kleinnijenhuis M, Jbabdi S, Sotiropoulos SN, Grotenhuis JA, van Cappellen van Walsum AM. A probabilistic atlas of the cerebellar white matter. NeuroImage. 2016;124(Pt A):724–32.

    Article  Google Scholar 

  52. Eklund A, Nichols TE, Knutsson H. Cluster failure: why fMRI inferences for spatial extent have inflated false-positive rates. Proc Natl Acad Sci U S A. 2016;113(28):7900–5.

    Article  CAS  Google Scholar 

  53. Eklund A, Andersson M, Knutsson H. Fast random permutation tests enable objective evaluation of methods for single-subject FMRI analysis. Int J Biomed Imaging. 2011;2011:627947.

    PubMed  PubMed Central  Google Scholar 

Web References

  1. Brain and Mind Institute, University of Western Ontario, Canada. Spatially unbiased infratentorial template for normalization of cerebellum and brainstem (SUIT). http://www.diedrichsenlab.org/imaging/suit.htm (last accessed 14.05.)

  2. Wellcome Trust Centre for Neuroimaging, London, UK. Statistical Parameter Mapping (SPM). http://www.fil.ion.ucl.ac.uk/spm/ (last accessed 14.05.)

  3. Chris Rorden’s Neuropsychology Lab, University of South Carolina, USA. MRIcron. http://www.mccauslandcenter.sc.edu/crnl/tools (last accessed 14.05.)

  4. Structural Brain Mapping Group, University of Jena, Germany. Voxel Based Morphometry toolbox (VBM8). http://www.neuro.uni-jena.de/vbm/download/ (last accessed 14.05.) and http://www.neuro.uni-jena.de/vbm/check-sample-homogeneity/ (last accessed 14.05.)

  5. Center for Investigating Healthy Minds, University of Wisconsin-Madison, USA. Mean centering continuous covariates. http://www.mumford.fmripower.org/mean_centering/ (last accessed 14.05.)

  6. FMRIB, Oxford, UK. FMRIB Software Library (fsl). https://fsl.fmrib.ox.ac.uk/fsl/ (last accessed 14.05.)

  7. Penn Image Computing and Science Laboratory, and Scientific Computing and Imaging Institute, University of Pennsylvania and University of Utah, USA. ITK-SNAP. http://www.itksnap.org/pmwiki/pmwiki.php (last accessed 14.05.)

Download references

Acknowledgments

The authors wish to thank Merim Bilalic and Matthew Bladen for proof-reading of the manuscript and language editing.

Funding

This work was supported by the European Union by a grant to EFACTS (HEALTH-F2-2010-242193) and the Else-Kröner Fresenius Stiftung (to MS).

Author information

Authors and Affiliations

  1. Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany

    Tobias Lindig, Benjamin Bender, Till-Karsten Hauser, Uwe Klose & Ulrike Ernemann

  2. High-Field MR Center, Max Planck Institute for Biological Cybernetics, Spemannstr. 41, 72076, Tübingen, Germany

    Tobias Lindig, Benjamin Bender, Vinod J. Kumar, Wolfgang Grodd & Klaus Scheffler

  3. Department of Psychiatry and Psychotherapy, University Hospital Tübingen, Calwerstr. 14, 72076, Tübingen, Germany

    Bettina Brendel

  4. Institute of Clinical Epidemiology and applied Biometry (IKEaB), University of Tübingen, Silcherstr. 5, 72076, Tübingen, Germany

    Bettina Brendel

  5. Department of Neurology and Hertie Institute for Clinical Brain Research, Eberhard Karls University, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany

    Jennifer Just, Matthis Synofzik & Ludger Schöls

  6. German Research Center for Neurodegenerative Diseases (DZNE), Otfried-Müller-Str. 23, 72076, Tübingen, Germany

    Jennifer Just, Matthis Synofzik & Ludger Schöls

  7. Department of Biomedical Magnetic Resonance, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany

    Klaus Scheffler

Authors
  1. Tobias Lindig
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Benjamin Bender
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Vinod J. Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Till-Karsten Hauser
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Wolfgang Grodd
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Bettina Brendel
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jennifer Just
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Matthis Synofzik
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Uwe Klose
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Klaus Scheffler
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Ulrike Ernemann
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Ludger Schöls
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tobias Lindig.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study. This article does not contain any studies with animals performed by any of the authors.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic Supplementary Material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lindig, T., Bender, B., Kumar, V.J. et al. Pattern of Cerebellar Atrophy in Friedreich’s Ataxia—Using the SUIT Template. Cerebellum 18, 435–447 (2019). https://doi.org/10.1007/s12311-019-1008-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12311-019-1008-z

Keywords

Search

Navigation