In the published article there was an error in the reference list as published. The reference list was submitted in the incorrect order. The revised reference list appears below.
The authors apologize for the above-mentioned errors and state that it does not affect the conclusions of the article in any way. The original version of this article has been updated.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
1.
RuanoLMeloCSilvaMCCoutinhoP. The global epidemiology of hereditary ataxia and spastic paraplegia: a systematic review of prevalence studies. Neuroepidemiology. (2014) 42:174–83. 10.1159/000358801
2.
SullivanRYauWYO'ConnorEHouldenH. Spinocerebellar ataxia: an update. J Neurol. (2019) 266:533–44. 10.1007/s00415-018-9076-4
3.
ScholsLAmoiridisGButtnerTPrzuntekHEpplenJTRiessO. Autosomal dominant cerebellar ataxia: phenotypic differences in genetically defined subtypes?Ann Neurol. (1997) 42:924–32. 10.1002/ana.410420615
4.
SeidelKSiswantoSBruntERden DunnenWKorfHWRubU. Brain pathology of spinocerebellar ataxias. Acta Neuropathol. (2012) 124:1–21. 10.1007/s00401-012-1000-x
5.
RubUScholsLPaulsonHAuburgerGKermerPJenJCet al. Clinical features, neurogenetics and neuropathology of the polyglutamine spinocerebellar ataxias type 1, 2, 3, 6 and 7. Prog Neurobiol. (2013) 104:38–66. 10.1016/j.pneurobio.2013.01.001
6.
OrrHTChungMYBanfiSKwiatkowski TJJrServadioABeaudetALet al. Expansion of an unstable trinucleotide CAG repeat in spinocerebellar ataxia type 1. Nat Genet. (1993) 4:221–6. 10.1038/ng0793-221
7.
RubUBurkKTimmannDden DunnenWSeidelKFarragKet al. Spinocerebellar ataxia type 1 (SCA1): new pathoanatomical and clinico-pathological insights. Neuropathol Appl Neurobiol. (2012) 38:665–80. 10.1111/j.1365-2990.2012.01259.x
8.
ArmstrongJBonaventuraIRojoAGonzalezGCorralJNadalNet al. Spinocerebellar ataxia type 2 (SCA2) with white matter involvement. Neurosci Lett. (2005) 381:247–51. 10.1016/j.neulet.2005.02.063
9.
RiessORubUPastoreABauerPScholsL. SCA3: neurological features, pathogenesis and animal models. Cerebellum. (2008) 7:125–37. 10.1007/s12311-008-0013-4
10.
IshikawaKWatanabeMYoshizawaKFujitaTIwamotoHYoshizawaTet al. Clinical, neuropathological, and molecular study in two families with spinocerebellar ataxia type 6 (SCA6). J Neurol Neurosurg Psychiatry. (1999) 67:86–9.
11.
GinestroniADella NaveRTessaCGiannelliMDe GrandisDPlasmatiRet al. Brain structural damage in spinocerebellar ataxia type 1: a VBM study. J Neurol. (2008) 255:1153–8. 10.1007/s00415-008-0860-4
12.
JungBCChoiSIDuAXCuzzocreoJLYingHSLandmanBAet al. MRI shows a region-specific pattern of atrophy in spinocerebellar ataxia type 2. Cerebellum. (2012) 11:272–9. 10.1007/s12311-011-0308-8
13.
RezendeTJRde PaivaJLRMartinezARMLopes-CendesIPedrosoJLBarsottiniOGPet al. Structural signature of SCA3: from presymptomatic to late disease stages. Ann Neurol. (2018) 84:401–8. 10.1002/ana.25297
14.
ReetzKCostaASMirzazadeSLehmannAJuzekARakowiczMet al. Genotype-specific patterns of atrophy progression are more sensitive than clinical decline in SCA1, SCA3 and SCA6. Brain. (2013) 136:905–17. 10.1093/brain/aws369
15.
OzGIltisIHutterDThomasWBusharaKOGomezCM. Distinct neurochemical profiles of spinocerebellar ataxias 1, 2, 6, and cerebellar multiple system atrophy. Cerebellum. (2011) 10:208–17. 10.1007/s12311-010-0213-6
16.
AdanyeguhIMHenryPGNguyenTMRinaldiDJauffretCValabregueRet al. In vivo neurometabolic profiling in patients with spinocerebellar ataxia types 1, 2, 3, and 7. Movement Disord. (2015) 30:662–70. 10.1002/mds.26181
17.
JoersJMDeelchandDKLyuTEmirUEHutterDGomezCMet al. Neurochemical abnormalities in premanifest and early spinocerebellar ataxias. Ann Neurol. (2018) 83:816–29. 10.1002/ana.25212
18.
MartinsCRMartinezARMVasconcelosIFde RezendeTJRCassebRFPedrosoJLet al. Structural signature in SCA1: clinical correlates, determinants and natural history. J Neurol. (2018) 265:2949–59. 10.1007/s00415-018-9087-1
19.
DeelchandDKJoersJMRavishankarALyuTEmirUEHutterDet al. Sensitivity of volumetric magnetic resonance imaging and magnetic resonance spectroscopy to progression of spinocerebellar ataxia type 1. Mov Disord Clin Pract. (2019) 6:549–58. 10.1002/mdc3.12804
20.
MandelliMLDe SimoneTMinatiLBruzzoneMGMariottiCFancelluRet al. Diffusion tensor imaging of spinocerebellar ataxias types 1 and 2. AJNR Am J Neuroradiol. (2007) 28:1996–2000. 10.3174/ajnr.A0716
21.
Della NaveRGinestroniATessaCSalvatoreEDe GrandisDPlasmatiRet al. Brain white matter damage in SCA1 and SCA2. An in vivo study using voxel-based morphometry, histogram analysis of mean diffusivity and tract-based spatial statistics. Neuroimage. (2008) 43:10–9. 10.1016/j.neuroimage.2008.06.036
22.
PrakashNHagemanNHuaXTogaAWPerlmanSLSalamonN. Patterns of fractional anisotropy changes in white matter of cerebellar peduncles distinguish spinocerebellar ataxia-1 from multiple system atrophy and other ataxia syndromes. Neuroimage. (2009) 47 (Suppl. 2):T72–81. 10.1016/j.neuroimage.2009.05.013
23.
AlcauterSBarriosFADiazRFernandez-RuizJ. Gray and white matter alterations in spinocerebellar ataxia type 7: an in vivo DTI and VBM study. Neuroimage. (2011) 55:1–7. 10.1016/j.neuroimage.2010.12.014
24.
KangJSKleinJCBaudrexelSDeichmannRNolteDHilkerR. White matter damage is related to ataxia severity in SCA3. J Neurol. (2014) 261:291–9. 10.1007/s00415-013-7186-6
25.
AdanyeguhIMPerlbargVHenryPGRinaldiDPetitEValabregueRet al. Autosomal dominant cerebellar ataxias: imaging biomarkers with high effect sizes. Neuroimage Clin. (2018) 19:858–67. 10.1016/j.nicl.2018.06.011
26.
FroelingMPullensPLeemansA. DTI analysis methods: region of interest analysis. In:Van HeckeWEmsellLand SunaertS, editors. Diffusion Tensor Imaging: A Practical Handbook. New York, NY: Springer New York (2016). p. 175–82. 10.1007/978-1-4939-3118-7_9
27.
FalconMIGomezCMChenEEShereenASolodkinA. Early cerebellar network shifting in spinocerebellar ataxia type 6. Cereb Cortex. (2016) 26:3205–18. 10.1093/cercor/bhv154
28.
SmithSMJenkinsonMJohansen-BergHRueckertDNicholsTEMackayCEet al. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage. (2006) 31:1487–505. 10.1016/j.neuroimage.2006.02.024
29.
TournierJDSmithRRaffeltDTabbaraRDhollanderTPietschMet al. MRtrix3: a fast, flexible and open software framework for medical image processing and visualisation. Neuroimage. (2019) 202:116137. 10.1016/j.neuroimage.2019.116137
30.
MascalchiMToschiNGiannelliMGinestroniADella NaveRNicolaiEet al. Progression of microstructural damage in spinocerebellar ataxia type 2: a longitudinal DTI study. AJNR Am J Neuroradiol. (2015) 36:1096–01. 10.3174/ajnr.A4343
31.
MascalchiMMarziCGiannelliMCiulliSBianchiAGinestroniAet al. Histogram analysis of DTI-derived indices reveals pontocerebellar degeneration and its progression in SCA2. PLoS ONE. (2018) 13:200258. 10.1371/journal.pone.0200258
32.
Schmitz-HubschTdu MontcelSTBalikoLBercianoJBoeschSDepondtCet al. Scale for the assessment and rating of ataxia: development of a new clinical scale. Neurology. (2006) 66:1717–20. 10.1212/01.wnl.0000219042.60538.92
33.
MaasRPvan GaalenJKlockgetherTvan de WarrenburgBP. The preclinical stage of spinocerebellar ataxias. Neurology. (2015) 85:96–103. 10.1212/WNL.0000000000001711
34.
du MontcelSTDurrARakowiczMNanettiLCharlesPSulekAet al. Prediction of the age at onset in spinocerebellar ataxia type 1, 2, 3 and 6. J Med Genet. (2014) 51:479–86. 10.1136/jmedgenet-2013-102200
35.
SubramonySHMayWLynchDGomezCFischbeckKHallettMet al. Measuring Friedreich ataxia: interrater reliability of a neurologic rating scale. Neurology. (2005) 64:1261–2. 10.1212/01.WNL.0000156802.15466.79
36.
PatelMIsaacsCJSeyerLBrigattiKGelbardSStrawserCet al. Progression of Friedreich ataxia: quantitative characterization over 5 years. Ann Clin Transl Neurol. (2016) 3:684–94. 10.1002/acn3.332
37.
JenkinsonMBeckmannCFBehrensTEWoolrichMWSmithSM. Fsl. Neuroimage. (2012) 62:782–90. 10.1016/j.neuroimage.2011.09.015
38.
HuaKZhangJWakanaSJiangHLiXReichDSet al. Tract probability maps in stereotaxic spaces: analyses of white matter anatomy and tract-specific quantification. Neuroimage. (2008) 39:336–47. 10.1016/j.neuroimage.2007.07.053
39.
KeihaninejadSZhangHRyanNSMaloneIBModatMCardosoMJet al. An unbiased longitudinal analysis framework for tracking white matter changes using diffusion tensor imaging with application to Alzheimer's disease. Neuroimage. (2013) 72:153–63. 10.1016/j.neuroimage.2013.01.044
40.
ZhangHAvantsBBYushkevichPAWooJHWangSMcCluskeyLFet al. High-dimensional spatial normalization of diffusion tensor images improves the detection of white matter differences: an example study using amyotrophic lateral sclerosis. IEEE Trans Med Imaging. (2007) 26:1585–97. 10.1109/TMI.2007.906784
41.
ParkYWJoersJMHutterDBusharaKOOzGLengletC. Improved sensitivity to longitudinal changes with advanced DTI analysis in a rare neurodegenerative disease. In: ISMRM 27th Annual Meeting and Exhibition. Montreal, QC (2019).
42.
RaffeltDATournierJDSmithREVaughanDNJacksonGRidgwayGRet al. Investigating white matter fibre density and morphology using fixel-based analysis. Neuroimage. (2017) 144 (Pt A):58–73. 10.1016/j.neuroimage.2016.09.029
43.
SchulzJBBorkertJWolfSSchmitz-HubschTRakowiczMMariottiCet al. Visualization, quantification and correlation of brain atrophy with clinical symptoms in spinocerebellar ataxia types 1, 3 and 6. Neuroimage. (2010) 49:158–68. 10.1016/j.neuroimage.2009.07.027
44.
DiedrichsenJ. A spatially unbiased atlas template of the human cerebellum. Neuroimage. (2006) 33:127–38. 10.1016/j.neuroimage.2006.05.056
45.
RomeroJECoupePGiraudRTaVTFonovVParkMTMet al. CERES: a new cerebellum lobule segmentation method. Neuroimage. (2017) 147:916–24. 10.1016/j.neuroimage.2016.11.003
46.
KinnunenKMGreenwoodRPowellJHLeechRHawkinsPCBonnelleVet al. White matter damage and cognitive impairment after traumatic brain injury. Brain. (2011) 134 (Pt 2):449–63. 10.1093/brain/awq347
47.
Della NaveRGinestroniADiciottiSSalvatoreESoricelliAMascalchiM. Axial diffusivity is increased in the degenerating superior cerebellar peduncles of Friedreich's ataxia. Neuroradiology. (2011) 53:367–72. 10.1007/s00234-010-0807-1
Summary
Keywords
SCA1, SCA2, SCA3, SCA6, diffusion MRI, Spinocerebeflar ataxias
Citation
Park YW, Joers JM, Guo B, Hutter D, Bushara K, Adanyeguh IM, Eberly LE, Öz G and Lenglet C (2022) Corrigendum: Assessment of cerebral and cerebellar white matter microstructure in spinocerebellar ataxias 1, 2, 3, and 6 using diffusion MRI. Front. Neurol. 13:1038298. doi: 10.3389/fneur.2022.1038298
Received
06 September 2022
Accepted
07 September 2022
Published
29 September 2022
Approved by
Frontiers Editorial Office, Frontiers Media SA, Switzerland
Volume
13 - 2022
Updates
Copyright
© 2022 Park, Joers, Guo, Hutter, Bushara, Adanyeguh, Eberly, Öz and Lenglet.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Young Woo Park park1556@umn.eduChristophe Lenglet clenglet@umn.edu
This article was submitted to Applied Neuroimaging, a section of the journal Frontiers in Neurology
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.