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Fronto-Parietal and White Matter Haemodynamics Predict Cognitive Outcome in Children with Moyamoya Independent of Stroke

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Abstract

Moyamoya disease is a major arteriopathy characterised by progressive steno-occlusion of the arteries of the circle of Willis. Studies in adults with moyamoya suggest an association between abnormal fronto-parietal and white matter regional haemodynamics and cognitive impairments, even in the absence of focal infarction. However, these associations have not been investigated in children with moyamoya. We examined the relationship between regional haemodynamics and ratings of intellectual ability and executive function, using hypercapnic challenge blood oxygen level–dependent magnetic resonance imaging of cerebrovascular reactivity in a consecutive cohort of children with confirmed moyamoya. Thirty children were included in the final analysis (mean age: 12.55 ± 3.03 years, 17 females, 15 idiopathic moyamoya and 15 syndromic moyamoya). Frontal haemodynamics were abnormal in all regardless of stroke history and comorbidity, but occipital lobe haemodynamics were also abnormal in children with syndromic moyamoya. Executive function deficits were noted in both idiopathic and syndromic moyamoya, whereas intellectual ability was impaired in syndromic moyamoya, even in the absence of stroke. Analysis of the relative effect of regional abnormal haemodynamics on cognitive outcomes demonstrated that executive dysfunction was predominantly explained by right parietal and white matter haemodynamics independent of stroke and comorbidity, while posterior circulation haemodynamics predicted intellectual ability. These results suggest that parietal and posterior haemodynamics play a compensatory role in overcoming frontal vulnerability and cognitive impairment.

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Availability of Data and Material

The datasets of the current study are not publicly available due to privacy and ethical concerns but are available from the corresponding author on reasonable request.

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References

  1. Ikezaki K, Matsushima T, Kuwabara Y, Suzuki S, Nomura T, Fukui M. Cerebral circulation and oxygen metabolism in childhood moyamoya disease: a perioperative positron emission tomography study. J Neurosurg. 1994;81:843–50.

    Article  CAS  PubMed  Google Scholar 

  2. Grant DA, Franzini C, Wild J, Eede KJ, Walker AM. Autoregulation of the cerebral circulation during sleep in newborn lambs. J Physiol. 2005;564:923–30 (John Wiley & Sons, Ltd).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Derdeyn CP, Shaibani A, Moran CJ, Cross DT, Grubb RL, Powers WJ. Lack of correlation between pattern of collateralization and misery perfusion in patients with carotid occlusion. Stroke Lippincott Williams and Wilkins. 1999;30:1025–32.

    CAS  Google Scholar 

  4. Derdeyn C, Videen T, Yundt K, Fritsch S, Carpenter D, Grubb R, et al. Variability of cerebral blood volume and oxygen extraction: stages of cerebral haemodynamic impairment revisited. Brain. 2002;125:595–607.

    Article  PubMed  Google Scholar 

  5. Baron JC, Bousser MG, Rey A, Guillard A, Comar D, Castaigne P. Reversal of focal “misery-perfusion syndrome” by extra-intracranial arterial bypass in hemodynamic cerebral ischemia. A case study with 15O positron emission tomography. Stroke. 1981;12:454–9.

    Article  CAS  PubMed  Google Scholar 

  6. Ohtaki M, Uede T, Morimoto S, Nonaka T, Tanabe S, Hashi K. Intellectual functions and regional cerebral haemodynamics after extensive omental transplantation spread over both frontal lobes in childhood moyamoya disease. Acta Neurochir (Wien). 1998;140:1043–53 (Springer).

    Article  CAS  PubMed  Google Scholar 

  7. Williams TS, Westmacott R, Dlamini N, Granite L, Dirks P, Askalan R, et al. Intellectual ability and executive function in pediatric moyamoya vasculopathy. Dev Med Child Neurol. 2012;54:30–7.

    Article  PubMed  Google Scholar 

  8. Isono M, Ishii K, Kamida T, Inoue R, Fujiki M, Kobayashi H. Long-term outcomes of pediatric moyamoya disease treated by encephalo-duro-arterio-synangiosis. Pediatr Neurosurg. 2002;36:14–21.

    Article  PubMed  Google Scholar 

  9. Hogan AM, Kirkham FJ, Isaacs EB, Wade AM, Vargha-Khadem F. Intellectual decline in children with moyamoya and sickle cell anaemia. Dev Med Child Neurol. 2005;47:824–9.

    Article  CAS  PubMed  Google Scholar 

  10. Ishii R, Takeuchi S, Tanaka R (1984) Intelligence in children with moyamoya disease: evaluation after surgical treatments with special reference to changes in cerebral blood flow. Stroke

  11. Imaizumi T, Hayashi K, Saito K, Osawa M, Fukuyama Y. Long-term outcomes of pediatric moyamoya disease monitored to adulthood. Pediatr Neurol. 1998;18:321–5.

    Article  CAS  PubMed  Google Scholar 

  12. Imaizumi C, Imaizumi T, Osawa M, Fukuyama Y, Takeshita M. Serial intelligence test scores in pediatric moyamoya disease. Neuropediatrics. 1999;30:294–9.

    Article  CAS  PubMed  Google Scholar 

  13. Lee JY, Phi JH, Wang K-C, Cho B-K, Shin M-S, Kim S-K. Neurocognitive profiles of children with moyamoya disease before and after surgical intervention. Cerebrovasc Dis. 2011;31:230–7.

    Article  PubMed  Google Scholar 

  14. Matsushima Y, Aoyagi M, Nariai T, … YT-C neurology and, 1997 U. Long-term intelligence outcome of post-encephalo-duro-arterio-synangiosis childhood moyamoya patients. Clin Neurol Neurosurg. 1997;99:S147–50.

  15. Matsushima Y, Aoyagi M, Masaoka H, Suzuki R, Ohno K. Mental outcome following encephaloduroarteriosynangiosis in children with moyamoya disease with the onset earlier than 5 years of age. Childs Nerv Syst. 1990;6:440–3.

    Article  CAS  PubMed  Google Scholar 

  16. Bowen M, Marks MP, Steinberg GK. Neuropsychological recovery from childhood moyamoya disease. Brain Dev Elsevier. 1998;20:119–23.

    Article  CAS  Google Scholar 

  17. Karzmark P, Zeifert PD, Tan S, Dorfman LJ, Bell-Stephens TE, Steinberg GK. Effect of moyamoya disease on neuropsychological functioning in adults. Neurosurgery. 2008;62:1048–51.

    Article  PubMed  Google Scholar 

  18. Ibrahim AFA, Montojo CA, Haut KM, Karlsgodt KH, Hansen L, Congdon E, et al. Spatial working memory in neurofibromatosis 1: altered neural activity and functional connectivity. NeuroImage Clin. 2017;15:801–11 (Elsevier Inc.).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Payne JM, Hyman SL, Shores EA, North KN. Assessment of executive function and attention in children with neurofibromatosis type 1: relationships between cognitive measures and real-world behavior. Child Neuropsychol. 2011;17:313–29.

    Article  PubMed  Google Scholar 

  20. Hijmans CT, Fijnvandraat K, Grootenhuis MA, van Geloven N, Heijboer H, Peters M, et al. Neurocognitive deficits in children with sickle cell disease: a comprehensive profile. Pediatr Blood Cancer. 2011;56:783–8 (John Wiley & Sons, Ltd).

    Article  PubMed  Google Scholar 

  21. Karzmark P, Zeifert PD, Bell-Stephens TE, Steinberg GK, Dorfman LJ. Neurocognitive impairment in adults with moyamoya disease without stroke. Neurosurgery Oxford University Press (OUP). 2012;70:634–8.

    Google Scholar 

  22. Quon JL, Kim LH, MacEachern SJ, Maleki M, Steinberg GK, Madhugiri V, et al. Early diffusion magnetic resonance imaging changes in normal-appearing brain in pediatric moyamoya disease. Neurosurgery Oxford University Press. 2020;86:530–7.

    Google Scholar 

  23. Dlamini N, Shah-Basak P, Leung J, Kirkham F, Shroff M, Kassner A, et al. Breath-hold blood oxygen level-dependent MRI: a tool for the assessment of cerebrovascular reserve in children with moyamoya disease. Am J Neuroradiol. 2018;39:1717–23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Spano VR, Mandell DM, Poublanc J, Sam K, Battisti-Charbonney A, Pucci O, et al. CO2 blood oxygen level-dependent MR mapping of cerebrovascular reserve in a clinical population: safety, tolerability, and technical feasibility. Radiology. 2013;266:592–8.

    Article  PubMed  Google Scholar 

  25. Pillai JJ, Mikulis DJ. Cerebrovascular reactivity mapping: an evolving standard for clinical functional imaging. Am. J. Neuroradiol. American Society of Neuroradiology; 2015. p. 7–13.

  26. Gupta A, Chazen JL, Hartman M, Delgado D, Anumula N, Shao H, et al. Cerebrovascular reserve and stroke risk in patients with carotid stenosis or occlusion: a systematic review and meta-analysis. Stroke. 2012. p. 2884–91.

  27. Jackman K, Iadecola C. Neurovascular regulation in the ischemic brain. Antioxidants Redox Signal. Mary Ann Liebert Inc.; 2015. p. 149–60.

  28. Yonas H, Pindzola RR, Meltzer CC, Sasser H. Qualitative versus quantitative assessment of cerebrovascular reserves. Neurosurgery Lippincott Williams and Wilkins. 1998;42:1005–12.

    CAS  Google Scholar 

  29. Ogasawara K, Okuguchi T, Sasoh M, Kobayashi M, Yukawa H, Terasaki K, et al. Qualitative versus quantitative assessment of cerebrovascular reactivity to acetazolamide using iodine-123-N-isopropyl-p-iodoamphetamine SPECT in patients with unilateral major cerebral artery occlusive disease. AJNR Am J Neuroradiol. 2003;24:1090–5.

    PubMed  PubMed Central  Google Scholar 

  30. Dlamini N, Slim M, Kirkham F, Shroff M, Dirks P, Moharir M, et al. Predicting Ischemic Risk Using Blood Oxygen Level-Dependent MRI in Children with Moyamoya. Am J Neuroradiol. 2020;41:160–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Heyn C, Poublanc J, Crawley A, Mandell D, Han JS, Tymianski M, et al. Quantification of cerebrovascular reactivity by blood oxygen level-dependent mr imaging and correlation with conventional angiography in patients with moyamoya disease. Am J Neuroradiol. 2010;

  32. Han JS, Mikulis DJ, Mardimae A, Kassner A, Poublanc J, Crawley AP, et al. Measurement of cerebrovascular reactivity in pediatric patients with cerebral vasculopathy using blood oxygen level-dependent MRI. Stroke. 2011;42:1261–9.

    Article  CAS  PubMed  Google Scholar 

  33. Dlamini N, Yau I, Westmacott R, Shroff M, Armstrong D, Logan W, et al. Cerebrovascular reactivity and intellectual outcome in childhood stroke with transient cerebral arteriopathy. Pediatr Neurol Elsevier. 2017;69:71–8.

    Article  Google Scholar 

  34. Hashimoto N, Tominaga T, Miyamoto S, Nagata I, Houkin K, Suzuki N, et al. Guidelines for diagnosis and treatment of moyamoya disease (spontaneous occlusion of the circle of Willis). Neurol Med Chir (Tokyo). Japan Neurosurgical Society; 2012;52:245–66.

  35. Rafay MF, Armstrong D, Dirks P, MacGregor DL, DeVeber G. Patterns of cerebral ischemia in children with moyamoya. Pediatr Neurol Elsevier. 2015;52:65–72.

    Article  Google Scholar 

  36. Suzuki J, Takaku A. Cerebrovascular moyamoya disease: Disease showing abnormal net-like vessels in base of brain. Arch Neurol American Medical Association. 1969;20:288–99.

    Article  CAS  Google Scholar 

  37. Wechsler D. Wechsler intelligence scale for children. 3rd ed. San Antonio, TX: The Psychological Corporation; 1991.

    Google Scholar 

  38. Wechsler D. Wechsler intelligence scale for children (WISC). 4th edn. San Antonio, TX: Harcourt Assessment; 2004.

  39. Wechsler D. The Wechsler adult intelligence scale. 3rd ed. San Antonio, TX: The Psychological Corporation; 1997.

    Google Scholar 

  40. Gioia G, Isquith P, Guy S, Kenworthy L. BRIEF: behavior rating inventory of executive function professional manual. Lutz, FL: Psychological Assessment Resources, Inc; 2000.

    Google Scholar 

  41. Mugikura S, Takahashi S, Higano S, Shirane R, Sakurai Y, Yamada S. Predominant involvement of ipsilateral anterior and posterior circulations in moyamoya disease. Stroke. 2002;33:1497–500.

    Article  PubMed  Google Scholar 

  42. Tomasi D, Volkow ND. Resting functional connectivity of language networks: characterization and reproducibility. Mol Psychiatry Nature Publishing Group. 2012;17:841–54.

    Article  CAS  Google Scholar 

  43. Kang CG, Chun MH, Kang JA, Do KH, Choi SJ. Neurocognitive dysfunction according to hypoperfusion territory in patients with moyamoya disease. Ann Rehabil Med. Korean Academy of Rehabilitation Medicine; 2017;41:1–8.

  44. Calviere L, Catalaa I, Marlats F, Viguier A, Bonneville F, Cognard C, et al. Correlation between cognitive impairment and cerebral hemodynamic disturbances on perfusion magnetic resonance imaging in European adults with moyamoya disease. J Neurosurg. 2010;113:753–9.

    Article  PubMed  Google Scholar 

  45. Su J Bin, Xi S Da, Zhou SY, Zhang X, Jiang SH, Xu B, et al. Microstructural damage pattern of vascular cognitive impairment: a comparison between moyamoya disease and cerebrovascular atherosclerotic disease. Neural Regen Res. Wolters Kluwer Medknow Publications; 2019;14:858–67.

  46. Fiske A, Holmboe K. Neural substrates of early executive function development. Dev. Rev. Mosby Inc.; 2019. p. 42–62.

  47. Kalpakidou AK, Allin MPG, Walshe M, Giampietro V, McGuire PK, Rifkin L, et al. Functional neuroanatomy of executive function after neonatal brain injury in adults who were born very preterm. PLoS One. Public Library of Science; 2014;9.

  48. Woodward LJ, Clark CAC, Pritchard VE, Anderson PJ, Inder TE. Neonatal white matter abnormalities predict global executive function impairment in children born very preterm. Dev Neuropsychol Taylor & Francis Group. 2011;36:22–41.

    Article  Google Scholar 

  49. Wang Q, Cheung C, Deng W, Li M, Huang C, Ma X, et al. Fronto-parietal white matter microstructural deficits are linked to performance IQ in a first-episode schizophrenia Han Chinese sample. Psychol Med Psychol Med. 2013;43:2047–56.

    Article  CAS  PubMed  Google Scholar 

  50. Ohtani T, Nestor PG, Bouix S, Newell D, Melonakos ED, McCarley RW, et al. Exploring the neural substrates of attentional control and human intelligence: diffusion tensor imaging of prefrontal white matter tractography in healthy cognition. Neuroscience Elsevier Ltd. 2017;341:52–60.

    CAS  Google Scholar 

  51. Burgess PW, Stuss DT. Fifty years of prefrontal cortex research: impact on assessment. J Int Neuropsychol Soc. Cambridge University Press; 2017;23:755–67.

  52. Ohtani T, Nestor PG, Bouix S, Saito Y, Hosokawa T, Kubicki M. Medial frontal white and gray matter contributions to general intelligence. PLoS One. Public Library of Science; 2014;9.

  53. Goh S, Bansal R, Xu D, Hao X, Liu J, Peterson BS. Neuroanatomical correlates of intellectual ability across the life span. Dev Cogn Neurosci Elsevier. 2011;1:305–12.

    Article  Google Scholar 

  54. Sasagawa A, Mikami T, Hirano T, Akiyama Y, Mikuni N. Characteristics of cerebral hemodynamics assessed by CT perfusion in moyamoya disease. J Clin Neurosci Churchill Livingstone. 2018;47:183–9.

    Article  Google Scholar 

  55. Robinson H, Calamia M, Gläscher J, Bruss J, Tranel D. Neuroanatomical correlates of executive functions: a neuropsychological approach using the EXAMINER battery. J Int Neuropsychol Soc. Cambridge University Press; 2014;20:52–63.

  56. Hampshire A, Chamberlain SR, Monti MM, Duncan J, Owen AM. The role of the right inferior frontal gyrus: inhibition and attentional control. Neuroimage Academic Press. 2010;50:1313–9.

    Article  Google Scholar 

  57. Spagna A, Kim TH, Wu T, Fan J. Right hemisphere superiority for executive control of attention. Cortex Masson SpA. 2020;122:263–76.

    Article  Google Scholar 

  58. Luders E, Narr KL, Thompson PM, Toga AW. Neuroanatomical correlates of intelligence. Intelligence NIH Public Access. 2009;37:156–63.

    Google Scholar 

  59. Wechsler D. The measurement of adult intelligence. Meas. adult Intell. (3rd ed.). Williams & Wilkins Co; 2007.

  60. Damasio A, Anderson S. The frontal lobes. In: Heilman K, Valenstein E, editors. Clin Neuropsychol. Oxford University Press; 2010. p. 404–46.

    Google Scholar 

  61. Ardila A, Pineda D, Rosselli M. Correlation between intelligence test scores and executive function measures. Arch Clin Neuropsychol. 2000;15:31–6.

    Article  CAS  PubMed  Google Scholar 

  62. Ehrler M, Latal B, Kretschmar O, von Rhein M, O’Gorman Tuura R. Altered frontal white matter microstructure is associated with working memory impairments in adolescents with congenital heart disease: a diffusion tensor imaging study. NeuroImage Clin. Elsevier Inc.; 2020;25.

  63. Kazumata K, Tha KK, Narita H, Kusumi I, Shichinohe H, Ito M, et al. Chronic ischemia alters brain microstructural integrity and cognitive performance in adult moyamoya disease. Stroke Lippincott Williams and Wilkins. 2015;46:354–60.

    CAS  Google Scholar 

  64. Stotesbury H, Kirkham FJ, Kölbel M, Balfour P, Clayden JD, Sahota S, et al. White matter integrity and processing speed in sickle cell anemia. Neurology Neurology. 2018;90:E2042–50.

    Article  PubMed  Google Scholar 

  65. Krukow P, Jonak K, Karakuła-Juchnowicz H, Podkowiński A, Jonak K, Borys M, et al. Disturbed functional connectivity within the left prefrontal cortex and sensorimotor areas predicts impaired cognitive speed in patients with first-episode schizophrenia. Psychiatry Res - Neuroimaging. 2018;275:28–35 (Elsevier Ireland Ltd).

    Article  PubMed  Google Scholar 

  66. Gayda M, Gremeaux V, Bherer L, Juneau M, Drigny J, Dupuy O, et al. Cognitive function in patients with stable coronary heart disease: related cerebrovascular and cardiovascular responses. PLoS One. Public Library of Science; 2017;12.

  67. Gläscher J, Tranel D, Paul LK, Rudrauf D, Rorden C, Hornaday A, et al. Lesion mapping of cognitive abilities linked to intelligence. Neuron Neuron. 2009;61:681–91.

    Article  PubMed  CAS  Google Scholar 

  68. Lee M, Zaharchuk G, Guzman R, Achrol A, Bell-Stephens T, Steinberg GK. Quantitative hemodynamic studies in moyamoya disease. Neurosurg Focus. Journal of Neurosurgery Publishing Group (JNSPG); 2009;26:E5.

  69. Baltsavias G, Khan N, Valavanis A. The collateral circulation in pediatric moyamoya disease. Child’s Nerv Syst Springer Verlag. 2015;31:389–98.

    Article  Google Scholar 

  70. Suzuki J, Takaku A. Cerebrovascular, “moyamoya” disease: disease showing abnormal net-like vessels in base of brain. Arch Neurol. 1969;20:288–99.

    Article  CAS  PubMed  Google Scholar 

  71. Wiesman AI, Wilson TW. The impact of age and sex on the oscillatory dynamics of visuospatial processing. Neuroimage. 2019;185:513–20 (Academic Press Inc.).

    Article  PubMed  Google Scholar 

  72. Billingsley RL, Jackson EF, Slopis JM, Swank PR, Mahankali S, Moore BD. Functional MRI of visual-spatial processing in neurofibromatosis, type I. Neuropsychologia Elsevier Ltd. 2004;42:395–404.

    Article  Google Scholar 

  73. Clements-Stephens AM, Rimrodt SL, Gaur P, Cutting LE. Visuospatial processing in children with neurofibromatosis type 1. Neuropsychologia NIH Public Access. 2008;46:690–7.

    Article  Google Scholar 

  74. Yeom KW, Lober RM, Barnes PD, Campen CJ. Reduced cerebral arterial spin-labeled perfusion in children with neurofibromatosis type 1. Am J Neuroradiol. American Society of Neuroradiology; 2013. p. 1823–8.

  75. Hyman SL, Shores A, North KN. The nature and frequency of cognitive deficits in children with neurofibromatosis type 1. Neurology Lippincott Williams and Wilkins. 2005;65:1037–44.

    Google Scholar 

  76. Vogel AC, Gutmann DH, Morris SM. Neurodevelopmental disorders in children with neurofibromatosis type 1. Dev Med Child Neurol. 2017;59:1112–6 (Blackwell Publishing Ltd).

    Article  PubMed  Google Scholar 

  77. Moses WW. Fundamental limits of spatial resolution in PET. Nucl Instrum Methods Phys Res A. NIH Public Access; 2011;648 Supplement 1:S236.

  78. Purkayastha S, Sorond F. Transcranial Doppler ultrasound: technique and application. Semin Neurol Thieme Medical Publishers. 2012;32:411–20.

    Article  Google Scholar 

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Funding

We thank the Auxilium Foundation and Brain Canada for their support. Study funders were not involved in the study design, data analysis, or publication decisions. The findings are solely the responsibility of the authors and do not represent the Auxilium Foundation. Image processing and analysis was supported by the Stroke Imaging Laboratory for Children, The Hospital for Sick Children, Toronto.

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Authors and Affiliations

  1. Neurosciences and Mental Health Program, Stroke Imaging Laboratory for Children, The Hospital for Sick Children, Toronto, ON, Canada

    Eun Jung Choi, Amanda Robertson & Nomazulu Dlamini

  2. Department of Neuropsychology, The Hospital for Sick Children, Toronto, ON, Canada

    Robyn Westmacott & Tricia Williams

  3. Developmental Neurosciences and Biomedical Research Centre, University College London Great Ormond Street Institute of Child Health, London, UK

    Fenella J. Kirkham

  4. Stroke Program, Division of Neurology, Department of Paediatrics, The Hospital for Sick Children, Toronto, ON, Canada

    Amanda Robertson, Mahendranath Moharir, Daune MacGregor, Elizabeth Pulcine, Ishvinder Bhathal, Matsanga Leyila Kaseka, William Logan, Gabrielle deVeber & Nomazulu Dlamini

  5. Child Health Evaluative Sciences Program, The Hospital for Sick Children, Toronto, ON, Canada

    Amanda Robertson, Mahmoud Slim, Gabrielle deVeber & Nomazulu Dlamini

  6. Diagnostic Imaging, The Hospital for Sick Children, ON, Toronto, Canada

    Prakash Muthusami & Manohar Shroff

  7. Medical Imaging, University of Toronto, ON, Toronto, Canada

    Prakash Muthusami, Manohar Shroff & Andrea Kassner

  8. Department of Neurosurgery, The Hospital for Sick Children, Toronto, ON, Canada

    Peter Dirks

  9. Department of Translational Medicine, The Hospital for Sick Children, Peter Gilgan Centre for Research & Learning, ON, Toronto, Canada

    Andrea Kassner

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  1. Eun Jung Choi
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  18. Nomazulu Dlamini
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Contributions

The study concept and design were developed by Nomazulu Dlamini, William Logan, Gabrielle deVeber and Fenella J. Kirkham. The imaging and clinical data were collected by Nomazulu Dlamini, Prakash Muthusami, Mahendranath Moharir, Elizabeth Pulcine, Manohar Shroff, Peter Dirks, Daune MacGregor, Gabrielle deVeber, Matsanga Leyila Kaseka, Amanda Robertson and Ishvinder Bhathal. The clinical information was coded and analysed by Nomazulu Dlamini and Matsanga Leyila Kaseka. The neuropsychological data were collected by Robyn Westmacott and Tricia Williams. Eun Jung Choi analysed the data and wrote the paper. Mahmoud Slim reviewed the statistical methods. Nomazulu Dlamini, Fenella Kirkham, Robyn Westmacott, Prakash Muthusami, Mahendranath Moharir, Tricia Williams, Mahmoud Slim, Matsanga Leyila Kaseka, Elizabeth Pulcine, Andrea Kassner and William Logan reviewed and edited the paper.

Corresponding author

Correspondence to Nomazulu Dlamini.

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Not applicable.

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Choi, E.J., Westmacott, R., Kirkham, F.J. et al. Fronto-Parietal and White Matter Haemodynamics Predict Cognitive Outcome in Children with Moyamoya Independent of Stroke. Transl. Stroke Res. 13, 757–773 (2022). https://doi.org/10.1007/s12975-022-01003-w

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