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Corticospinal tract involvement in spinocerebellar ataxia type 3: a diffusion tensor imaging study

  • Functional Neuroradiology
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Abstract

Purpose

The aim of this study was to evaluate the integrity of the corticospinal tracts (CST) in patients with SCA3 and age- and gender-matched healthy control subjects using diffusion tensor imaging (DTI). We also looked at the clinical correlates of such diffusivity abnormalities.

Methods

We assessed 2 cohorts from different Brazilian centers: cohort 1 (n = 29) scanned in a 1.5 T magnet and cohort 2 (n = 91) scanned in a 3.0 T magnet. We used Pearson’s coefficients to assess the correlation of CST DTI parameters and ataxia severity (expressed by SARA scores).

Results

Two different results were obtained. Cohort 1 showed no significant between-group differences in DTI parameters. Cohort 2 showed significant between-group differences in the FA values in the bilateral precentral gyri (p < 0.001), bilateral superior corona radiata (p < 0.001), bilateral posterior limb of the internal capsule (p < 0.001), bilateral cerebral peduncle (p < 0.001), and bilateral basis pontis (p < 0.001). There was moderate correlation between CST diffusivity parameters and SARA scores in cohort 2 (Pearson correlation coefficient: 0.40–0.59).

Conclusion

DTI particularly at 3 T is able to uncover and quantify CST damage in SCA3. Moreover, CST microstructural damage may contribute with ataxia severity in the disease.

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References

  1. Kawaguchi Y, Okamoto T, Taniwaki M, Aizawa M, Inoue M, Katayama S, Kawakami H, Nakamura S, Nishimura M, Akiguchi I, Kimura J, Narumiya S, Kakizuka A (1994) CAG expansions in a novel gene for Machado-Joseph disease at chromosome 14q32.1. Nat Genet 8:221–228. https://doi.org/10.1038/ng1194-221

    Article  CAS  PubMed  Google Scholar 

  2. Nakano K, Spence A, Dawson D (1972) Machado disease. Neurology 22:49–55. https://doi.org/10.1212/WNL.22.1.49

    Article  CAS  PubMed  Google Scholar 

  3. Rosenberg RN, Fowler HL, de Magalhães J et al (1977) Azorean disease of the nervous system. N Engl J Med 297:729–730. https://doi.org/10.1056/NEJM197709292971318

    Article  Google Scholar 

  4. Dürr A, Stevanin G, Cancel G et al (1996) Spinocerebellar ataxia 3 and Machado-Joseph disease: clinical, molecular, and neuropathological features. Ann Neurol 39:490–499. https://doi.org/10.1002/ana.410390411

    Article  PubMed  Google Scholar 

  5. Pedroso JL, França MC, Braga-Neto P et al (2013) Nonmotor and extracerebellar features in Machado-Joseph disease: a review. Mov Disord 28:1200–1208. https://doi.org/10.1002/mds.25513

    Article  PubMed  Google Scholar 

  6. Riess O, Rüb U, Pastore A, Bauer P, Schöls L (2008) SCA3: neurological features, pathogenesis and animal models. Cerebellum 7:125–137. https://doi.org/10.1007/s12311-008-0013-4

    Article  CAS  PubMed  Google Scholar 

  7. Rüb U, Brunt ER, Deller T (2008) New insights into the pathoanatomy of spinocerebellar ataxia type 3 (Machado-Joseph disease). Curr Opin Neurol 21:111–116. https://doi.org/10.1097/WCO.0b013e3282f7673d

    Article  PubMed  Google Scholar 

  8. de Rezende TJR, D’Abreu A, Guimarães RP et al (2015) Cerebral cortex involvement in Machado-Joseph disease. Eur J Neurol 22:277–283. https://doi.org/10.1111/ene.12559

    Article  PubMed  Google Scholar 

  9. Murata Y, Yamaguchi S, Kawakami H, Imon Y, Maruyama H, Sakai T, Kazuta T, Ohtake T, Nishimura M, Saida T, Chiba S, Oh-i T, Nakamura S (1998) Characteristic magnetic resonance imaging findings in Machado-Joseph disease. Arch Neurol 55:33–37. https://doi.org/10.1001/archneur.55.1.33

    Article  CAS  PubMed  Google Scholar 

  10. Onodera O, Idezuka J, Igarashi S, Takiyama Y, Endo K, Takano H, Oyake M, Tanaka H, Inuzuka T, Hayashi T, Yuasa T, Ito J, Miyatake T, Tsuji S (1998) Progressive atrophy of cerebellum and brainstem as a function of age and the size of the expanded CAG repeats in the MJD1 gene in Machado-Joseph disease. Ann Neurol 43:288–296. https://doi.org/10.1002/ana.410430305

    Article  CAS  PubMed  Google Scholar 

  11. Peng H, Liang X, Long Z, Chen Z, Shi Y, Xia K, Meng L, Tang B, Qiu R, Jiang H (2019) Gene-related cerebellar neurodegeneration in SCA3/MJD: a case-controlled imaging-genetic study. Front Neurol 10:1–10. https://doi.org/10.3389/fneur.2019.01025

    Article  Google Scholar 

  12. Farrar MA, Vucic S, Nicholson G, Kiernan MC (2016) Motor cortical dysfunction develops in spinocerebellar ataxia type 3. Clin Neurophysiol 127:3418–3424. https://doi.org/10.1016/j.clinph.2016.09.005

    Article  PubMed  Google Scholar 

  13. Jhunjhunwala K, Prashanth DK, Netravathi M, Jain S, Purushottam M, Pal PK (2013) Alterations in cortical excitability and central motor conduction time in spinocerebellar ataxias 1, 2 and 3: a comparative study. Parkinsonism Relat Disord 19:306–311. https://doi.org/10.1016/j.parkreldis.2012.11.002

    Article  PubMed  Google Scholar 

  14. Wu X, Liao X, Zhan Y, Cheng C, Shen W, Huang M, Zhou Z, Wang Z, Qiu Z, Xing W, Liao W, Tang B, Shen L (2017) Microstructural alterations in asymptomatic and symptomatic patients with spinocerebellar ataxia type 3: a tract-based spatial statistics study. Front Neurol 8:1–9. https://doi.org/10.3389/fneur.2017.00714

    Article  Google Scholar 

  15. Rezende TJR, de Paiva JLR, Martinez ARM, Lopes-Cendes I, Pedroso JL, Barsottini OGP, Cendes F, França MC Jr (2018) Structural signature of SCA3: from presymptomatic to late disease stages. Ann Neurol 84:401–408. https://doi.org/10.1002/ana.25297

    Article  PubMed  Google Scholar 

  16. Schmitz-Hübsch T, du Montcel ST, Baliko L, Berciano J, Boesch S, Depondt C, Giunti P, Globas C, Infante J, Kang JS, Kremer B, Mariotti C, Melegh B, Pandolfo M, Rakowicz M, Ribai P, Rola R, Schöls L, Szymanski S, van de Warrenburg B, Dürr A, Klockgether T, Fancellu R (2006) Scale for the assessment and rating of ataxia: development of a new clinical scale. Neurology 66:1717–1720. https://doi.org/10.1212/01.wnl.0000219042.60538.92

    Article  PubMed  Google Scholar 

  17. Zhuang J, Hrabe J, Kangarlu A, Xu D, Bansal R, Branch CA, Peterson BS (2006) Correction of eddy-current distortions in diffusion tensor images using the known directions and strengths of diffusion gradients. J Magn Reson Imaging 24:1188–1193. https://doi.org/10.1002/jmri.20727

    Article  PubMed  PubMed Central  Google Scholar 

  18. Woods RP, Grafton ST, Holmes CJ, Cherry SR, Mazziotta JC (1998) Automated image registration: I. General methods and intrasubject, intramodality validation. J Comput Assist Tomogr 22:139–152. https://doi.org/10.1097/00004728-199801000-00027

    Article  CAS  PubMed  Google Scholar 

  19. Tang X, Yoshida S, Hsu J, Huisman TAGM, Faria AV, Oishi K, Kutten K, Poretti A, Li Y, Miller MI, Mori S (2014) Multi-contrast multi-atlas parcellation of diffusion tensor imaging of the human brain. PLoS One 9:e96985. https://doi.org/10.1371/journal.pone.0096985

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Towns J, Cockerill T, Dahan M, Foster I, Gaither K, Grimshaw A, Hazlewood V, Lathrop S, Lifka D, Peterson GD, Roskies R, Scott JR, Wilkins-Diehr N (2014) XSEDE: Accelerating scientific discovery. Comput Sci Eng 16:62–74. https://doi.org/10.1109/MCSE.2014.80

    Article  CAS  Google Scholar 

  21. Qin W, Yu CS, Zhang F et al (2009) Effects of echo time on diffusion quantification of brain white matter at 1.5 T and 3.0 T. Magn Reson Med 61:755–760. https://doi.org/10.1002/mrm.21920

    Article  PubMed  Google Scholar 

  22. Chou MC, Kao EF, Mori S (2013) Effects of b-value and echo time on magnetic resonance diffusion tensor imaging-derived parameters at 1.5 t: a voxel-wise study. J Med Biol Eng 33:45–50. https://doi.org/10.5405/jmbe.1126

    Article  Google Scholar 

  23. Chung AW, Thomas DL, Ordidge RJ, Clark CA (2013) Diffusion tensor parameters and principal eigenvector coherence: Relation to b-value intervals and field strength. Magn Reson Imaging 31:742–747. https://doi.org/10.1016/j.mri.2012.11.014

    Article  PubMed  Google Scholar 

  24. Paulson HL, Das SS, Crino PB, Perez MK, Patel SC, Gotsdiner D, Fischbeck KH, Pittman RN (1997) Machado-Joseph disease gene product is a cytoplasmic protein widely expressed in brain. Ann Neurol 41:453–462. https://doi.org/10.1002/ana.410410408

    Article  CAS  PubMed  Google Scholar 

  25. Wu Y, Peng Y, Wang Y (2014) An insight into advances in the pathogenesis and therapeutic strategies of spinocerebellar ataxia type 3. Rev Neurosci 26:95–104. https://doi.org/10.1515/revneuro-2014-0040

    Article  CAS  Google Scholar 

  26. D’Abreu A, França M, Appenzeller S et al (2009) Axonal dysfunction in the deep white matter in Machado-Joseph disease. J Neuroimaging 19:9–12. https://doi.org/10.1111/j.1552-6569.2008.00260.x

    Article  PubMed  Google Scholar 

  27. Jardim LB, Pereira ML, Silveira I, Ferro A, Sequeiros J, Giugliani R (2001) Neurologic findings in Machado-Joseph disease. Arch Neurol 58:899. https://doi.org/10.1001/archneur.58.6.899

    Article  CAS  PubMed  Google Scholar 

  28. Pulido-Valdeolivas I, Gómez-Andrés D, Sanz-Gallego I, Rausell E, Arpa J (2016) Patterns of motor signs in spinocerebellar ataxia type 3 at the start of follow-up in a reference unit. Cerebellum Ataxias 3:1–10. https://doi.org/10.1186/s40673-016-0042-6

    Article  Google Scholar 

  29. Guang WY, Du J, Ling WJ et al (2009) Six cases of SCA3/MJD patients that mimic hereditary spastic paraplegia in clinic. J Neurol Sci 285:121–124. https://doi.org/10.1016/j.jns.2009.06.027

    Article  Google Scholar 

  30. Song Y, Liu Y, Zhang N, Long L (2015) Spinocerebellar ataxia type 3/machado-joseph disease manifested as spastic paraplegia: a clinical and genetic study. Exp Ther Med 9:417–420. https://doi.org/10.3892/etm.2014.2136

    Article  CAS  PubMed  Google Scholar 

  31. Song SK, Yoshino J, Le TQ et al (2005) Demyelination increases radial diffusivity in corpus callosum of mouse brain. Neuroimage 26:132–140. https://doi.org/10.1016/j.neuroimage.2005.01.028

    Article  PubMed  Google Scholar 

  32. Song SK, Sun SW, Ju WK, Lin SJ, Cross AH, Neufeld AH (2003) Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. Neuroimage 20:1714–1722. https://doi.org/10.1016/j.neuroimage.2003.07.005

    Article  PubMed  Google Scholar 

  33. 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 55:302–308. https://doi.org/10.1002/mrm.20774

    Article  PubMed  Google Scholar 

  34. Karlsborg M, Rosenbaum S, Wiegell MR, Simonsen H, Larsson HBW, Werdelin LM, Gredal O (2004) Corticospinal tract degeneration and possible pathogenesis in ALS evaluated by MR diffusion tensor imaging. Amyotroph Lateral Scler Other Mot Neuron Disord 5:136–140. https://doi.org/10.1080/14660820410018982

    Article  Google Scholar 

  35. Fischer LR, Culver DG, Tennant P, Davis AA, Wang M, Castellano-Sanchez A, Khan J, Polak MA, Glass JD (2004) Amyotrophic lateral sclerosis is a distal axonopathy: evidence in mice and man. Exp Neurol 185:232–240. https://doi.org/10.1016/j.expneurol.2003.10.004

    Article  PubMed  Google Scholar 

  36. Yabe I, Matsushima M, Soma H, Basri R, Sasaki H (2008) Usefulness of the scale for assessment and rating of ataxia (SARA). J Neurol Sci 266:164–166. https://doi.org/10.1016/j.jns.2007.09.021

    Article  PubMed  Google Scholar 

  37. Bürk K, Sival DA (2018) Scales for the clinical evaluation of cerebellar disorders. Handb Clin Neurol 154:329–339. https://doi.org/10.1016/B978-0-444-63956-1.00020-5

    Article  PubMed  Google Scholar 

  38. Schmitz-Hübsch T, Fimmers R, Rakowicz M et al (2010) Responsiveness of different rating instruments in spinocerebellar ataxia patients. Neurology 74:678–684. https://doi.org/10.1212/WNL.0b013e3181d1a6c9

    Article  PubMed  Google Scholar 

  39. Paap BK, Roeske S, Durr A, Schöls L, Ashizawa T, Boesch S, Bunn LM, Delatycki MB, Giunti P, Lehéricy S, Mariotti C, Melegh J, Pandolfo M, Tallaksen CME, Timmann D, Tsuji S, Schulz JB, van de Warrenburg BP, Klockgether T (2016) Standardized assessment of hereditary ataxia patients in clinical studies. Mov Disord Clin Pract 3:230–240. https://doi.org/10.1002/mdc3.12315

    Article  PubMed  PubMed Central  Google Scholar 

  40. Kang JS, Klein JC, Baudrexel S, Deichmann R, Nolte D, Hilker R (2014) White matter damage is related to ataxia severity in SCA3. J Neurol 261:291–299. https://doi.org/10.1007/s00415-013-7186-6

    Article  CAS  PubMed  Google Scholar 

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Funding

No funding was received for this study.

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Authors and Affiliations

  1. Division of General Neurology and Ataxia Unit, Department of Neurology, Federal University of São Paulo (UNIFESP), São Paulo, Brazil

    Bruno Shigueo Yonekura Inada, Fernando Vieira Pereira, Orlando Graziani Povoas Barsottini & José Luiz Pedroso

  2. Department of Neuroradiology, Hospital Beneficência Portuguesa, São Paulo, Brazil

    Bruno Shigueo Yonekura Inada

  3. Department of Neurology, State University of Campinas (UNICAMP), São Paulo, Brazil

    Thiago Junqueira Ribeiro Rezende & Marcondes Cavalcante França Jr

  4. Department of Neuroradiology, University of São Paulo (USP), São Paulo, Brazil

    Lucas Ávila Lessa Garcia

  5. Department of Neuroradiology, Santa Casa de São Paulo School of Medical Sciences, São Paulo, Brazil

    Antônio José da Rocha

  6. Department of Clinical Medicine, Universidade Federal do Ceará, Ceará, Brazil

    Pedro Braga Neto

  7. Center of Health Sciences, Universidade Estadual do Ceará, Ceará, Brazil

    Pedro Braga Neto

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  1. Bruno Shigueo Yonekura Inada
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Correspondence to Bruno Shigueo Yonekura Inada.

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Inada, B.S.Y., Rezende, T.J.R., Pereira, F.V. et al. Corticospinal tract involvement in spinocerebellar ataxia type 3: a diffusion tensor imaging study. Neuroradiology 63, 217–224 (2021). https://doi.org/10.1007/s00234-020-02528-3

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  • DOI: https://doi.org/10.1007/s00234-020-02528-3

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