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White matter alterations in adult with autism spectrum disorder evaluated using diffusion kurtosis imaging

  • Diagnostic Neuroradiology
  • Published:
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Abstract

Purpose

Autism spectrum disorder (ASD) is related to impairment in various white matter (WM) pathways. Utility of the recently developed two-compartment model of diffusion kurtosis imaging (DKI) to analyse axial diffusivity of WM is restricted by several limitations. The present study aims to validate the utility of model-free DKI in the evaluation of WM alterations in ASD and analyse the potential relationship between DKI-evident WM alterations and personality scales.

Methods

Overall, 15 participants with ASD and 15 neurotypical (NT) controls were scanned on a 3 T magnetic resonance (MR) scanner, and scores for autism quotient (AQ), systemising quotient (SQ) and empathising quotient (EQ) were obtained for both groups. Multishell diffusion-weighted MR data were acquired using two b-values (1000 and 2000 s/mm2). Differences in mean kurtosis (MK), radial kurtosis (RK) and axial kurtosis (AK) between the groups were evaluated using tract-based spatial statistics (TBSS). Finally, the relationships between the kurtosis indices and personality quotients were examined.

Results

The ASD group demonstrated significantly lower AK in the body and splenium of corpus callosum than the NT group; however, no other significant differences were identified. Negative correlations were found between AK and AQ or SQ, predominantly in WM areas related to social–emotional processing such as uncinate fasciculus, inferior fronto-occipital fasciculus, and inferior and superior longitudinal fasciculi.

Conclusions

Model-free DKI and its indices may represent a novel, objective method for detecting the disease severity and WM alterations in patients with ASD.

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References

  1. Wise EA, Smith MD, Rabins PV (2017) Aging and autism spectrum disorder: a naturalistic, longitudinal study of the comorbidities and behavioral and neuropsychiatric symptoms in adults with ASD. J Autism Dev Disord 47(6):1708–1715. https://doi.org/10.1007/s10803-017-3095-3

    Article  PubMed  Google Scholar 

  2. American Psychiatric Association., American Psychiatric Association. DSM-5 Task Force (2013) Diagnostic and statistical manual of mental disorders: DSM-5. 5th edn. American Psychiatric Association, Washington, D.C

    Book  Google Scholar 

  3. Clemm von Hohenberg C, Wigand MC, Kubicki M, Leicht G, Giegling I, Karch S, Hartmann AM, Konte B, Friedl M, Ballinger T, Eckbo R, Bouix S, Jager L, Shenton ME, Rujescu D, Mulert C (2013) CNTNAP2 polymorphisms and structural brain connectivity: a diffusion-tensor imaging study. J Psychiatr Res 47(10):1349–1356. https://doi.org/10.1016/j.jpsychires.2013.07.002

    Article  PubMed  Google Scholar 

  4. McFadden K, Minshew NJ (2013) Evidence for dysregulation of axonal growth and guidance in the etiology of ASD. Front Hum Neurosci 7:671. https://doi.org/10.3389/fnhum.2013.00671

    Article  PubMed  PubMed Central  Google Scholar 

  5. Basser PJ, Mattiello J, LeBihan D (1994) MR diffusion tensor spectroscopy and imaging. Biophys J 66(1):259–267. https://doi.org/10.1016/S0006-3495(94)80775-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Ikuta T, Shafritz KM, Bregman J, Peters BD, Gruner P, Malhotra AK, Szeszko PR (2014) Abnormal cingulum bundle development in autism: a probabilistic tractography study. Psychiatry Res 221(1):63–68. https://doi.org/10.1016/j.pscychresns.2013.08.002

    Article  PubMed  Google Scholar 

  7. Libero LE, Burge WK, Deshpande HD, Pestilli F, Kana RK (2016) White matter diffusion of major fiber tracts implicated in autism spectrum disorder. Brain Connect 6(9):691–699. https://doi.org/10.1089/BrainConnect.2016.0442

  8. McGrath J, Johnson K, O'Hanlon E, Garavan H, Leemans A, Gallagher L (2013) Abnormal functional connectivity during visuospatial processing is associated with disrupted organisation of white matter in autism. Front Hum Neurosci 7:434. https://doi.org/10.3389/fnhum.2013.00434

    Article  PubMed  PubMed Central  Google Scholar 

  9. Travers BG, Tromp do PM, Adluru N, Lange N, Destiche D, Ennis C, Nielsen JA, Froehlich AL, Prigge MB, Fletcher PT, Anderson JS, Zielinski BA, Bigler ED, Lainhart JE, Alexander AL (2015) Atypical development of white matter microstructure of the corpus callosum in males with autism: a longitudinal investigation. Mol Autism 6:15. https://doi.org/10.1186/s13229-015-0001-8

    Article  Google Scholar 

  10. Jou RJ, Reed HE, Kaiser MD, Voos AC, Volkmar FR, Pelphrey KA (2016) White matter abnormalities in autism and unaffected siblings. J Neuropsychiatr Clin Neurosci 28(1):49–55. https://doi.org/10.1176/appi.neuropsych.15050109

    Article  Google Scholar 

  11. Pugliese L, Catani M, Ameis S, Dell'Acqua F, Thiebaut de Schotten M, Murphy C, Robertson D, Deeley Q, Daly E, Murphy DG (2009) The anatomy of extended limbic pathways in Asperger syndrome: a preliminary diffusion tensor imaging tractography study. Neuroimage 47(2):427–434. https://doi.org/10.1016/j.neuroimage.2009.05.014

    Article  PubMed  Google Scholar 

  12. Thomas C, Humphreys K, Jung KJ, Minshew N, Behrmann M (2011) The anatomy of the callosal and visual-association pathways in high-functioning autism: a DTI tractography study. Cortex 47(7):863–873. https://doi.org/10.1016/j.cortex.2010.07.006

    Article  PubMed  Google Scholar 

  13. Pardini M, Elia M, Garaci FG, Guida S, Coniglione F, Krueger F, Benassi F, Emberti Gialloreti L (2012) Long-term cognitive and behavioral therapies, combined with augmentative communication, are related to uncinate fasciculus integrity in autism. J Autism Dev Disord 42(4):585–592. https://doi.org/10.1007/s10803-011-1281-2

    Article  PubMed  Google Scholar 

  14. Aoki Y, Yoncheva YN, Chen B, Nath T, Sharp D, Lazar M, Velasco P, Milham MP, Di Martino A (2017) Association of white matter structure with autism spectrum disorder and attention-deficit/hyperactivity disorder. JAMA Psychiatry 74(11):1120–1128. https://doi.org/10.1001/jamapsychiatry.2017.2573

    Article  Google Scholar 

  15. Catani M, Jones DK, Daly E, Embiricos N, Deeley Q, Pugliese L, Curran S, Robertson D, Murphy DG (2008) Altered cerebellar feedback projections in Asperger syndrome. Neuroimage 41(4):1184–1191. https://doi.org/10.1016/j.neuroimage.2008.03.041

    Article  PubMed  Google Scholar 

  16. Cooper M, Thapar A, Jones DK (2015) ADHD severity is associated with white matter microstructure in the subgenual cingulum. Neuroimage Clin 7:653–660. https://doi.org/10.1016/j.nicl.2015.02.012

    Article  Google Scholar 

  17. Ke X, Tang T, Hong S, Hang Y, Zou B, Li H, Zhou Z, Ruan Z, Lu Z, Tao G, Liu Y (2009) White matter impairments in autism, evidence from voxel-based morphometry and diffusion tensor imaging. Brain Res 1265:171–177. https://doi.org/10.1016/j.brainres.2009.02.013

    Article  CAS  PubMed  Google Scholar 

  18. Langen M, Leemans A, Johnston P, Ecker C, Daly E, Murphy CM, Dell’acqua F, Durston S, Consortium A, Murphy DG (2012) Fronto-striatal circuitry and inhibitory control in autism: findings from diffusion tensor imaging tractography. Cortex 48(2):183–193. https://doi.org/10.1016/j.cortex.2011.05.018

    Article  PubMed  Google Scholar 

  19. Basser PJ, Jones DK (2002) Diffusion-tensor MRI: theory, experimental design and data analysis - a technical review. NMR Biomed 15(7–8):456–467. https://doi.org/10.1002/nbm.783

    Article  PubMed  Google Scholar 

  20. Chung AW, Seunarine KK, Clark CA (2016) NODDI reproducibility and variability with magnetic field strength: a comparison between 1.5 T and 3 T. Hum Brain Mapp 37(12):4550–4565. https://doi.org/10.1002/hbm.23328

    Article  PubMed  Google Scholar 

  21. 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. https://doi.org/10.1002/hbm.23628

  22. Fieremans E, Jensen JH, Helpern JA (2011) White matter characterization with diffusional kurtosis imaging. Neuroimage 58(1):177–188. https://doi.org/10.1016/j.neuroimage.2011.06.006

    Article  PubMed  PubMed Central  Google Scholar 

  23. Alexander AL, Lee JE, Lazar M, Field AS (2007) Diffusion tensor imaging of the brain. Neurotherapeutics 4(3):316–329. https://doi.org/10.1016/j.nurt.2007.05.011

    Article  PubMed  PubMed Central  Google Scholar 

  24. Hui ES, Cheung MM, Qi L, Wu EX (2008) Towards better MR characterization of neural tissues using directional diffusion kurtosis analysis. NeuroImage 42(1):122–134. https://doi.org/10.1016/j.neuroimage.2008.04.237

    Article  PubMed  Google Scholar 

  25. Jensen JH, Helpern JA, Ramani A, Lu H, Kaczynski K (2005) Diffusional kurtosis imaging: the quantification of non-Gaussian water diffusion by means of magnetic resonance imaging. Magn Reson Med 53(6):1432–1440. https://doi.org/10.1002/mrm.20508

    Article  PubMed  Google Scholar 

  26. Zhu J, Zhuo C, Qin W, Wang D, Ma X, Zhou Y, Yu C (2015) Performances of diffusion kurtosis imaging and diffusion tensor imaging in detecting white matter abnormality in schizophrenia. Neuroimage Clin 7:170–176. https://doi.org/10.1016/j.nicl.2014.12.008

    Article  Google Scholar 

  27. Fieremans E, Benitez A, Jensen JH, Falangola MF, Tabesh A, Deardorff RL, Spampinato MV, Babb JS, Novikov DS, Ferris SH, Helpern JA (2013) Novel white matter tract integrity metrics sensitive to Alzheimer disease progression. AJNR Am J Neuroradiol 34(11):2105–2112. https://doi.org/10.3174/ajnr.A3553

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Steven AJ, Zhuo J, Melhem ER (2014) Diffusion kurtosis imaging: an emerging technique for evaluating the microstructural environment of the brain. AJR Am J Roentgenol 202(1):W26–W33. https://doi.org/10.2214/AJR.13.11365

    Article  PubMed  Google Scholar 

  29. Das SK, Wang JL, Bing L, Bhetuwal A, Yang HF (2017) Regional values of diffusional kurtosis estimates in the healthy brain during normal aging. Clin Neuroradiol 27(3):283–298. https://doi.org/10.1007/s00062-015-0490-z

    Article  CAS  PubMed  Google Scholar 

  30. Davenport EM, Apkarian K, Whitlow CT, Urban JE, Jensen JH, Szuch E, Espeland MA, Jung Y, Rosenbaum DA, Gioia GA, Powers AK, Stitzel JD, Maldjian JA (2016) Abnormalities in diffusional kurtosis metrics related to head impact exposure in a season of high school varsity football. J Neurotrauma 33(23):2133–2146. https://doi.org/10.1089/neu.2015.4267

    Article  PubMed  PubMed Central  Google Scholar 

  31. Duchene G, Peeters F, Peeters A, Duprez T (2017) A comparative study of the sensitivity of diffusion-related parameters obtained from diffusion tensor imaging, diffusional kurtosis imaging, q-space analysis and bi-exponential modelling in the early disease course (24 h) of hyperacute (6 h) ischemic stroke patients. MAGMA 30(4):375–385. https://doi.org/10.1007/s10334-017-0612-5

    Article  PubMed  Google Scholar 

  32. Gao J, Feng ST, Wu B, Gong N, Lu M, Wu PM, Wang H, He X, Huang B (2015) Microstructural brain abnormalities of children of idiopathic generalized epilepsy with generalized tonic-clonic seizure: a voxel-based diffusional kurtosis imaging study. J Magn Reson Imaging 41(4):1088–1095. https://doi.org/10.1002/jmri.24647

    Article  PubMed  Google Scholar 

  33. Qi XX, Shi DF, Ren SX, Zhang SY, Li L, Li QC, Guan LM (2018) Histogram analysis of diffusion kurtosis imaging derived maps may distinguish between low and high grade gliomas before surgery. Eur Radiol 28(4):1748–1755. https://doi.org/10.1007/s00330-017-5108-1

    Article  PubMed  Google Scholar 

  34. Kamiya K, Okada N, Sawada K, Watanabe Y, Irie R, Hanaoka S, Suzuki Y, Koike S, Mori H, Kunimatsu A, Hori M, Aoki S, Kasai K, Abe O (2018) Diffusional kurtosis imaging and white matter microstructure modeling in a clinical study of major depressive disorder. NMR Biomed 31(7):e3938. https://doi.org/10.1002/nbm.3938

    Article  PubMed  PubMed Central  Google Scholar 

  35. Kamagata K, Tomiyama H, Hatano T, Motoi Y, Abe O, Shimoji K, Kamiya K, Suzuki M, Hori M, Yoshida M, Hattori N, Aoki S (2014) A preliminary diffusional kurtosis imaging study of Parkinson disease: comparison with conventional diffusion tensor imaging. Neuroradiology 56(3):251–258. https://doi.org/10.1007/s00234-014-1327-1

    Article  PubMed  Google Scholar 

  36. Kamagata K, Tomiyama H, Motoi Y, Kano M, Abe O, Ito K, Shimoji K, Suzuki M, Hori M, Nakanishi A, Kuwatsuru R, Sasai K, Aoki S, Hattori N (2013) Diffusional kurtosis imaging of cingulate fibers in Parkinson disease: comparison with conventional diffusion tensor imaging. Magn Reson Imaging 31(9):1501–1506. https://doi.org/10.1016/j.mri.2013.06.009

    Article  PubMed  Google Scholar 

  37. Gong NJ, Chan CC, Leung LM, Wong CS, Dibb R, Liu C (2017) Differential microstructural and morphological abnormalities in mild cognitive impairment and Alzheimer’s disease: evidence from cortical and deep gray matter. Hum Brain Mapp 38(5):2495–2508. https://doi.org/10.1002/hbm.23535

    Article  PubMed  Google Scholar 

  38. Lazar M, Miles LM, Babb JS, Donaldson JB (2014) Axonal deficits in young adults with high functioning autism and their impact on processing speed. Neuroimage Clin 4:417–425. https://doi.org/10.1016/j.nicl.2014.01.014

    Article  Google Scholar 

  39. Sui YV, Donaldson J, Miles L, Babb JS, Castellanos FX, Lazar M (2018) Diffusional kurtosis imaging of the corpus callosum in autism. Mol Autism 9:62. https://doi.org/10.1186/s13229-018-0245-1

  40. Alexander DC, Dyrby TB, Nilsson M, Zhang H (2017) Imaging brain microstructure with diffusion MRI: practicality and applications. NMR Biomed 32:e3841. https://doi.org/10.1002/nbm.3841

    Article  PubMed  Google Scholar 

  41. Wakabayashi A, Tojo Y, Baron-Cohen S, Wheelwright S (2004) The autism-Spectrum quotient (AQ) Japanese version: evidence from high-functioning clinical group and normal adults. Shinrigaku Kenkyu 75(1):78–84

    Article  Google Scholar 

  42. Baron-Cohen S, Richler J, Bisarya D, Gurunathan N, Wheelwright S (2003) The systemizing quotient: an investigation of adults with Asperger syndrome or high-functioning autism, and normal sex differences. Philos Trans R Soc Lond Ser B Biol Sci 358(1430):361–374. https://doi.org/10.1098/rstb.2002.1206

    Article  Google Scholar 

  43. Baron-Cohen S, Wheelwright S (2004) The empathy quotient: an investigation of adults with Asperger syndrome or high functioning autism, and normal sex differences. J Autism Dev Disord 34(2):163–175

    Article  Google Scholar 

  44. Andersson JL, Sotiropoulos SN (2016) An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage 125:1063–1078. https://doi.org/10.1016/j.neuroimage.2015.10.019

    Article  PubMed  PubMed Central  Google Scholar 

  45. Tabesh A, Jensen JH, Ardekani BA, Helpern JA (2011) Estimation of tensors and tensor-derived measures in diffusional kurtosis imaging. Magn Reson Med 65(3):823–836. https://doi.org/10.1002/mrm.22655

    Article  PubMed  Google Scholar 

  46. Basser PJ, Mattiello J, LeBihan D (1994) Estimation of the effective self-diffusion tensor from the NMR spin echo. J Magn Reson B 103(3):247–254

    Article  CAS  Google Scholar 

  47. Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, Watkins KE, Ciccarelli O, Cader MZ, Matthews PM, Behrens TE (2006) Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31(4):1487–1505. https://doi.org/10.1016/j.neuroimage.2006.02.024

    Article  Google Scholar 

  48. Jenkinson M, Beckmann CF, Behrens TE, Woolrich MW, Smith SM (2012) Fsl. Neuroimage 62(2):782–790. https://doi.org/10.1016/j.neuroimage.2011.09.015

    Article  PubMed  Google Scholar 

  49. Mori S, Wakana S, Van Zijl PCM (2005) MRI atlas of human white matter. 1st edn. Elsevier, Amsterdam

    Google Scholar 

  50. Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE (2014) Permutation inference for the general linear model. Neuroimage 92:381–397. https://doi.org/10.1016/j.neuroimage.2014.01.060

    Article  PubMed  PubMed Central  Google Scholar 

  51. Smith SM, Nichols TE (2009) Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage 44(1):83–98. https://doi.org/10.1016/j.neuroimage.2008.03.061

    Article  PubMed  Google Scholar 

  52. Follin C, Svard D, van Westen D, Bjorkman-Burtscher IM, Sundgren PC, Fjalldal S, Latt J, Nilsson M, Johanson A, Erfurth EM (2019) Microstructural white matter alterations associated to neurocognitive deficits in childhood leukemia survivors treated with cranial radiotherapy - a diffusional kurtosis study. Acta Oncol:1–8. https://doi.org/10.1080/0284186X.2019.1571279

    Article  CAS  Google Scholar 

  53. Cheng JX, Zhang HY, Peng ZK, Xu Y, Tang H, Wu JT, Xu J (2018) Divergent topological networks in Alzheimer's disease: a diffusion kurtosis imaging analysis. Transl Neurodegener 7:10. https://doi.org/10.1186/s40035-018-0115-y

    Article  PubMed  PubMed Central  Google Scholar 

  54. Veraart J, Poot DH, Van Hecke W, Blockx I, Van der Linden A, Verhoye M, Sijbers J (2011) More accurate estimation of diffusion tensor parameters using diffusion kurtosis imaging. Magn Reson Med 65(1):138–145. https://doi.org/10.1002/mrm.22603

    Article  Google Scholar 

  55. Jensen JH, Helpern JA (2010) MRI quantification of non-Gaussian water diffusion by kurtosis analysis. NMR Biomed 23(7):698–710. https://doi.org/10.1002/nbm.1518

    Article  PubMed  PubMed Central  Google Scholar 

  56. Hui ES, Fieremans E, Jensen JH, Tabesh A, Feng W, Bonilha L, Spampinato MV, Adams R, Helpern JA (2012) Stroke assessment with diffusional kurtosis imaging. Stroke 43(11):2968–2973. https://doi.org/10.1161/STROKEAHA.112.657742

    Article  PubMed  PubMed Central  Google Scholar 

  57. Raab P, Hattingen E, Franz K, Zanella FE, Lanfermann H (2010) Cerebral gliomas: diffusional kurtosis imaging analysis of microstructural differences. Radiology 254(3):876–881. https://doi.org/10.1148/radiol.09090819

    Article  PubMed  Google Scholar 

  58. Wu EX, Cheung MM (2010) MR diffusion kurtosis imaging for neural tissue characterization. NMR Biomed 23(7):836–848. https://doi.org/10.1002/nbm.1506

    Article  PubMed  Google Scholar 

  59. Falangola MF, Guilfoyle DN, Tabesh A, Hui ES, Nie X, Jensen JH, Gerum SV, Hu C, LaFrancois J, Collins HR, Helpern JA (2014) Histological correlation of diffusional kurtosis and white matter modeling metrics in cuprizone-induced corpus callosum demyelination. NMR Biomed 27(8):948–957. https://doi.org/10.1002/nbm.3140

    Article  PubMed  PubMed Central  Google Scholar 

  60. Hu VW, Nguyen A, Kim KS, Steinberg ME, Sarachana T, Scully MA, Soldin SJ, Luu T, Lee NH (2009) Gene expression profiling of lymphoblasts from autistic and nonaffected sib pairs: altered pathways in neuronal development and steroid biosynthesis. PLoS One 4(6):e5775. https://doi.org/10.1371/journal.pone.0005775

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Anitha A, Nakamura K, Yamada K, Suda S, Thanseem I, Tsujii M, Iwayama Y, Hattori E, Toyota T, Miyachi T, Iwata Y, Suzuki K, Matsuzaki H, Kawai M, Sekine Y, Tsuchiya K, Sugihara G, Ouchi Y, Sugiyama T, Koizumi K, Higashida H, Takei N, Yoshikawa T, Mori N (2008) Genetic analyses of roundabout (ROBO) axon guidance receptors in autism. Am J Med Genet B Neuropsychiatr Genet 147B(7):1019–1027. https://doi.org/10.1002/ajmg.b.30697

    Article  CAS  PubMed  Google Scholar 

  62. Sbacchi S, Acquadro F, Calo I, Cali F, Romano V (2010) Functional annotation of genes overlapping copy number variants in autistic patients: focus on axon pathfinding. Current genomics 11(2):136–145. https://doi.org/10.2174/138920210790886880

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Melin M, Carlsson B, Anckarsater H, Rastam M, Betancur C, Isaksson A, Gillberg C, Dahl N (2006) Constitutional downregulation of SEMA5A expression in autism. Neuropsychobiology 54(1):64–69. https://doi.org/10.1159/000096040

  64. Kalkman HO (2012) A review of the evidence for the canonical Wnt pathway in autism spectrum disorders. Mol Autism 3(1):10. https://doi.org/10.1186/2040-2392-3-10

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Hussman JP, Chung RH, Griswold AJ, Jaworski JM, Salyakina D, Ma D, Konidari I, Whitehead PL, Vance JM, Martin ER, Cuccaro ML, Gilbert JR, Haines JL, Pericak-Vance MA (2011) A noise-reduction GWAS analysis implicates altered regulation of neurite outgrowth and guidance in autism. Mol Autism 2(1):1. https://doi.org/10.1186/2040-2392-2-1

    Article  Google Scholar 

  66. Morgan JT, Chana G, Pardo CA, Achim C, Semendeferi K, Buckwalter J, Courchesne E, Everall IP (2010) Microglial activation and increased microglial density observed in the dorsolateral prefrontal cortex in autism. Biol Psychiatry 68(4):368–376. https://doi.org/10.1016/j.biopsych.2010.05.024

    Article  Google Scholar 

  67. Zikopoulos B, Barbas H (2010) Changes in prefrontal axons may disrupt the network in autism. J Neurosci 30(44):14595–14609. https://doi.org/10.1523/JNEUROSCI.2257-10.2010

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Travers BG, Adluru N, Ennis C, Tromp do PM, Destiche D, Doran S, Bigler ED, Lange N, Lainhart JE, Alexander AL (2012) Diffusion tensor imaging in autism spectrum disorder: a review. Autism Res 5(5):289–313. https://doi.org/10.1002/aur.1243

    Article  PubMed  PubMed Central  Google Scholar 

  69. Hardan AY, Pabalan M, Gupta N, Bansal R, Melhem NM, Fedorov S, Keshavan MS, Minshew NJ (2009) Corpus callosum volume in children with autism. Psychiatry Res 174(1):57–61. https://doi.org/10.1016/j.pscychresns.2009.03.005

    Article  PubMed  PubMed Central  Google Scholar 

  70. Wolff JJ, Gerig G, Lewis JD, Soda T, Styner MA, Vachet C, Botteron KN, Elison JT, Dager SR, Estes AM, Hazlett HC, Schultz RT, Zwaigenbaum L, Piven J, Network I (2015) Altered corpus callosum morphology associated with autism over the first 2 years of life. Brain 138(Pt 7):2046–2058. https://doi.org/10.1093/brain/awv118

    Article  PubMed  PubMed Central  Google Scholar 

  71. Meyza KZ, Defensor EB, Jensen AL, Corley MJ, Pearson BL, Pobbe RL, Bolivar VJ, Blanchard DC, Blanchard RJ (2013) The BTBR T+ tf/J mouse model for autism spectrum disorders-in search of biomarkers. Behav Brain Res 251:25–34. https://doi.org/10.1016/j.bbr.2012.07.021

    Article  CAS  PubMed  Google Scholar 

  72. Aylward EH, Minshew NJ, Field K, Sparks BF, Singh N (2002) Effects of age on brain volume and head circumference in autism. Neurology 59(2):175–183

    Article  CAS  Google Scholar 

  73. Gibbard CR, Ren J, Seunarine KK, Clayden JD, Skuse DH, Clark CA (2013) White matter microstructure correlates with autism trait severity in a combined clinical-control sample of high-functioning adults. Neuroimage Clin 3:106–114. https://doi.org/10.1016/j.nicl.2013.07.007

    Article  PubMed  PubMed Central  Google Scholar 

  74. Roine U, Salmi J, Roine T, Wendt TN, Leppamaki S, Rintahaka P, Tani P, Leemans A, Sams M (2015) Constrained spherical deconvolution-based tractography and tract-based spatial statistics show abnormal microstructural organization in Asperger syndrome. Mol Autism 6:4. https://doi.org/10.1186/2040-2392-6-4

    Article  Google Scholar 

  75. Wheelwright S, Baron-Cohen S, Goldenfeld N, Delaney J, Fine D, Smith R, Weil L, Wakabayashi A (2006) Predicting autism Spectrum quotient (AQ) from the systemizing quotient-revised (SQ-R) and empathy quotient (EQ). Brain Res 1079(1):47–56. https://doi.org/10.1016/j.brainres.2006.01.012

    Article  CAS  Google Scholar 

  76. Lundqvist LO, Lindner H (2017) Is the autism-spectrum quotient a valid measure of traits associated with the autism spectrum? A Rasch validation in adults with and without autism spectrum disorders. J Autism Dev Disord 47(7):2080–2091. https://doi.org/10.1007/s10803-017-3128-y

    Article  PubMed  PubMed Central  Google Scholar 

  77. Beacher FD, Minati L, Baron-Cohen S, Lombardo MV, Lai MC, Gray MA, Harrison NA, Critchley HD (2012) Autism attenuates sex differences in brain structure: a combined voxel-based morphometry and diffusion tensor imaging study. AJNR 33(1):83–89. https://doi.org/10.3174/ajnr.A2880

    Article  CAS  PubMed  Google Scholar 

  78. Sotiropoulos SN, Jbabdi S, Xu J, Andersson JL, Moeller S, Auerbach EJ, Glasser MF, Hernandez M, Sapiro G, Jenkinson M, Feinberg DA, Yacoub E, Lenglet C, Van Essen DC, Ugurbil K, Behrens TE, WU-MH C (2013) Advances in diffusion MRI acquisition and processing in the Human Connectome Project. Neuroimage 80:125–143. https://doi.org/10.1016/j.neuroimage.2013.05.057

    Article  PubMed  PubMed Central  Google Scholar 

  79. Ameis SH, Fan J, Rockel C, Voineskos AN, Lobaugh NJ, Soorya L, Wang AT, Hollander E, Anagnostou E (2011) Impaired structural connectivity of socio-emotional circuits in autism spectrum disorders: a diffusion tensor imaging study. PLoS One 6(11):e28044. https://doi.org/10.1371/journal.pone.0028044

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Billeci L, Calderoni S, Tosetti M, Catani M, Muratori F (2012) White matter connectivity in children with autism spectrum disorders: a tract-based spatial statistics study. BMC Neurol 12:148. https://doi.org/10.1186/1471-2377-12-148

    Article  PubMed  PubMed Central  Google Scholar 

  81. Itahashi T, Yamada T, Nakamura M, Watanabe H, Yamagata B, Jimbo D, Shioda S, Kuroda M, Toriizuka K, Kato N, Hashimoto R (2015) Linked alterations in gray and white matter morphology in adults with high-functioning autism spectrum disorder: a multimodal brain imaging study. Neuroimage Clin 7:155–169. https://doi.org/10.1016/j.nicl.2014.11.019

    Article  PubMed  Google Scholar 

  82. Bakhtiari R, Zurcher NR, Rogier O, Russo B, Hippolyte L, Granziera C, Araabi BN, Nili Ahmadabadi M, Hadjikhani N (2012) Differences in white matter reflect atypical developmental trajectory in autism: a tract-based spatial statistics study. Neuroimage Clin 1(1):48–56. https://doi.org/10.1016/j.nicl.2012.09.001

    Article  Google Scholar 

  83. Kamagata K, Motoi Y, Tomiyama H, Abe O, Ito K, Shimoji K, Suzuki M, Hori M, Nakanishi A, Sano T, Kuwatsuru R, Sasai K, Aoki S, Hattori N (2013) Relationship between cognitive impairment and white-matter alteration in Parkinson’s disease with dementia: tract-based spatial statistics and tract-specific analysis. Eur Radiol 23(7):1946–1955. https://doi.org/10.1007/s00330-013-2775-4

    Article  Google Scholar 

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Acknowledgements

We thank Yuki Takenaka and Mana Kuramochi for their research assistance.

Funding

This work was supported by JSPS KAKENHI Grant Number JP16H06280, the MEXT-Supported Program for the Private University Research Branding Project and ImPACT Program of Council for Science, Technology and Innovation (Cabinet Office, Government of Japan).

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Correspondence to Koji Kamagata.

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Supplementary Table 1

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Supplementary Fig. 1

Comparison of AK between the ASD and NT groups using uncorrected P-value of 0.05. TBSS analyses show significantly decreased AK in three clusters of white matter in the ASD group compared with the NT group. In TBSS, blue-light blue voxels represent lower AK, and arrows show the peak of each cluster. The FA skeleton with an FA > 0.2 is shown in green. To facilitate visualisation, the results are thickened using the fill script implemented in FSL. AK axial kurtosis, ASD autism spectrum disorder, FA fractional anisotropy, FSL FMRIB software library, NT neurotypical control, PFWE family-wise error-corrected P value, ROI range of interest, TBSS tract-based spatial statistic (PNG 235 kb)

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Hattori, A., Kamagata, K., Kirino, E. et al. White matter alterations in adult with autism spectrum disorder evaluated using diffusion kurtosis imaging. Neuroradiology 61, 1343–1353 (2019). https://doi.org/10.1007/s00234-019-02238-5

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  • DOI: https://doi.org/10.1007/s00234-019-02238-5

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