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Neuroimaging biomarkers of preterm brain injury: toward developing the preterm connectome

  • Advances in Fetal and Neonatal Imaging
  • Published:
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Abstract

For typically developing infants, the last trimester of fetal development extending into the first post-natal months is a period of rapid brain development. Infants who are born premature face significant risk of brain injury (e.g., intraventricular or germinal matrix hemorrhage and periventricular leukomalacia) from complications in the perinatal period and also potential long-term neurodevelopmental disabilities because these early injuries can interrupt normal brain maturation. Neuroimaging has played an important role in the diagnosis and management of the preterm infant. Both cranial US and conventional MRI techniques are useful in diagnostic and prognostic evaluation of preterm brain development and injury. Cranial US is highly sensitive for intraventricular hemorrhage (IVH) and provides prognostic information regarding cerebral palsy. Data are limited regarding the utility of MRI as a routine screening instrument for brain injury for all preterm infants. However, MRI might provide diagnostic or prognostic information regarding PVL and other types of preterm brain injury in the setting of specific clinical indications and risk factors. Further development of advanced MR techniques like volumetric MR imaging, diffusion tensor imaging, metabolic imaging (MR spectroscopy) and functional connectivity are necessary to provide additional insight into the molecular, cellular and systems processes that underlie brain development and outcome in the preterm infant. The adult concept of the “connectome” is also relevant in understanding brain networks that underlie the preterm brain. Knowledge of the preterm connectome will provide a framework for understanding preterm brain function and dysfunction, and potentially even a roadmap for brain plasticity. By combining conventional imaging techniques with more advanced techniques, neuroimaging findings will likely be used not only as diagnostic and prognostic tools, but also as biomarkers for long-term neurodevelopmental outcomes, instruments to assess the efficacy of neuroprotective agents and maneuvers in the NICU, and as screening instruments to appropriately select infants for longitudinal developmental interventions.

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References

  1. Stoll BJ, Hansen NI, Bell EF et al (2010) Neonatal outcomes of extremely preterm infants from the NICHD Neonatal Research Network. Pediatrics 126:443–456

    Article  PubMed  Google Scholar 

  2. EXPRESS Group (2010) Incidence of and risk factors for neonatal morbidity after active perinatal care: extremely preterm infants study in Sweden (EXPRESS). Acta Paediatr 99:978–992

    Article  Google Scholar 

  3. Lemons JA, Bauer CR, Oh W et al (2001) Very low birth weight outcomes of the National Institute of Child Health and Human Development Neonatal Research Network, January 1995 through December 1996. NICHD Neonatal Research Network. Pediatrics 107:E1

    Article  PubMed  CAS  Google Scholar 

  4. Aarnoudse-Moens CS, Weisglas-Kuperus N, van Goudoever JB et al (2009) Meta-analysis of neurobehavioral outcomes in very preterm and/or very low birth weight children. Pediatrics 124:717–728

    Article  PubMed  Google Scholar 

  5. Saigal S, Hoult LA, Streiner DL et al (2000) School difficulties at adolescence in a regional cohort of children who were extremely low birth weight. Pediatrics 105:325–331

    Article  PubMed  CAS  Google Scholar 

  6. Hack M (2006) Young adult outcomes of very-low-birth-weight children. Semin Fetal Neonatal Med 11:127–137

    Article  PubMed  Google Scholar 

  7. Sie LT, van der Knaap MS, van Wezel-Meijler G et al (2000) Early MR features of hypoxic-ischemic brain injury in neonates with periventricular densities on sonograms. AJNR 21:852–861

    PubMed  CAS  Google Scholar 

  8. Maalouf EF, Duggan PJ, Counsell SJ et al (2001) Comparison of findings on cranial ultrasound and magnetic resonance imaging in preterm neonates. Pediatrics 107:719–727

    Article  PubMed  CAS  Google Scholar 

  9. Miller SP, Cozzio EE, Goldstein RB et al (2003) Comparing the diagnosis of white matter injury in premature newborns with serial MR imaging and transfontanel ultrasonography findings. AJNR 24:1661–1669

    PubMed  Google Scholar 

  10. Inder TE, Anderson NJ, Spencer C et al (2003) White matter injury in the premature infant: a comparison between serial cranial sonographic and MR findings at term. AJNR 24:805–809

    PubMed  Google Scholar 

  11. Childs A-M, Cornette L, Ramenghi LA et al (2001) Magnetic resonance and cranial ultrasound characteristics of periventricular white matter abnormalities in newborn infants. Clin Radiol 56:647–655

    Article  PubMed  CAS  Google Scholar 

  12. Hagmann P, Cammoun L, Gigandet X et al (2010) MR connectomics: principles and challenges. J Neurosci Methods 194(1):34–45

    Article  PubMed  Google Scholar 

  13. Sporns O (2011) The human connectome: a complex network. Ann NY Acad Sci 1224(1):109–125

    Article  PubMed  Google Scholar 

  14. Jensen FE (2011) Epilepsy as a spectrum disorder: implications from novel clinical and basic neuroscience. Epilepsia 52(Suppl 1):1–6

    Article  PubMed  Google Scholar 

  15. Rubinov M, Bassett DS (2011) Emerging evidence of connectomic abnormalities in schizophrenia. J Neurosci 31(17):6263–6265

    Article  PubMed  CAS  Google Scholar 

  16. Ment LR, Hirtz D, Hüppi PS (2009) Imaging biomarkers of outcome in the developing preterm brain. Lancet Neurol 8(11):1042–1055

    Article  PubMed  Google Scholar 

  17. Volpe JJ, Kinney HC, Jensen FE et al (2011) The developing oligodendrocyte: key cellular target in brain injury in the premature infant. Int J Dev Neurosci 29(4):423–440

    Article  PubMed  CAS  Google Scholar 

  18. Volpe JJ (2009) Brain injury in premature infants: a complex amalgam of destructive and developmental disturbances. Lancet Neurol 8(1):110–124

    Article  PubMed  Google Scholar 

  19. Hill A, Melson GL, Clark HB et al (1982) Hemorrhagic periventricular leukomalacia: diagnosis by real time ultrasound and correlation with autopsy findings. Pediatrics 69:282–284

    PubMed  CAS  Google Scholar 

  20. Manger MN, Feldman RC, Brown WJ et al (1984) Intracranial ultrasound diagnosis of neonatal periventricular leukomalacia. J Ultrasound Med 3:59–63

    PubMed  CAS  Google Scholar 

  21. Fawer CL, Calame A, Perentes E et al (1985) Periventricular leukomalacia: a correlation study between real-time ultrasound and autopsy findings. Periventricular leukomalacia in the neonate. Neuroradiology 27:292–300

    Article  PubMed  CAS  Google Scholar 

  22. Correa F, Enriquez G, Rossello J et al (2004) Posterior fontanelle sonography: an acoustic window into the neonatal brain. AJNR 25:1274–1282

    PubMed  Google Scholar 

  23. Luna JA, Goldstein RB (2000) Sonographic visualization of neonatal posterior fossa abnormalities through the posterolateral fontanelle. AJR 174:561–567

    PubMed  CAS  Google Scholar 

  24. Anderson N, Allan R, Darlow B et al (1994) Diagnosis of intraventricular hemorrhage in the newborn: value of sonography via the posterior fontanelle. AJR 163:893–896

    PubMed  CAS  Google Scholar 

  25. O’Shea TM, Allred EN, Dammann O et al (2009) ELGAN study of the brain and related disorders in extremely low gestational age newborns. Early Hum Dev 85(11):719–725

    Article  PubMed  Google Scholar 

  26. Hintz SR, Slovis T, Bulas D et al (2007) Interobserver reliability and accuracy of cranial ultrasound scanning interpretation in premature infants. J Pediatr 150(6):592–596

    Article  PubMed  Google Scholar 

  27. Barkovich AJ (2006) MR imaging of the neonatal brain. Neuroimaging Clin N Am 16:117–135

    Article  PubMed  CAS  Google Scholar 

  28. Blüml S, Friedlich P, Erberich S et al (2004) MR imaging of newborns by using an MR-compatible incubator with integrated radiofrequency coils: initial experience. Radiology 231(2):594–601

    Article  PubMed  Google Scholar 

  29. Wilson-Costello D, Friedman H, Minich N et al (2005) Improved survival rates with increased neurodevelopmental disability for extremely low birth weight infants in the 1990s. Pediatrics 115(4):997–1003

    Article  PubMed  Google Scholar 

  30. Papile LA, Burstein J, Burstein R et al (1978) Incidence and evolution of subependymal and intraventricular hemorrhage: a study of infants with birth weight less than 1,500 gm. J Pediatr 92:529–534

    Article  PubMed  CAS  Google Scholar 

  31. Vohr BR, Wright LL, Poole WK et al (2005) Neurodevelopmental outcomes of extremely low birth weight infants <32 weeks’ gestation between 1993 and 1998. Pediatrics 116(3):635–643

    Article  PubMed  Google Scholar 

  32. Marlow N, Wolke D, Bracewell MA et al (2005) Neurologic and developmental disability at six years of age after extremely preterm birth. N Engl J Med 352(1):9–19

    Article  PubMed  CAS  Google Scholar 

  33. Hack M, Wilson-Costello D, Friedman H et al (2000) Neurodevelopment and predictors of outcomes of children with birth weights of less than 1,000 g: 1992–1995. Arch Pediatr Adolesc Med 154(7):725–731

    PubMed  CAS  Google Scholar 

  34. Patra K, Wilson-Costello D, Taylor HG et al (2006) Grades I-II intraventricular hemorrhage in extremely low birth weight infants: effects on neurodevelopment. J Pediatr 149(2):169–173

    Article  PubMed  Google Scholar 

  35. Leijser LM, Srinivasan L, Rutherford MA et al (2007) Structural linear measurements in the newborn brain: accuracy of cranial ultrasound compared to MRI. Pediatr Radiol 37:640–648

    Article  PubMed  Google Scholar 

  36. Horsch S, Bengtsson J, Nordell A et al (2009) Lateral ventricular size in extremely premature infants: 3D MRI confirms 2D ultrasound measurements. Ultrasound Med Biol 35:360–366

    Article  PubMed  Google Scholar 

  37. Levene MI, Starte DR (1981) A longitudinal study of post-haemorrhagic ventricular dilatation in the newborn. Arch Dis Child 56:905–910

    Article  PubMed  CAS  Google Scholar 

  38. London DA, Carroll BA, Enzmann DR (1980) Sonography of ventricular size and germinal matrix hemorrhage in premature infants. AJR 135:559–564

    PubMed  CAS  Google Scholar 

  39. Grasby DC, Esterman A, Marshall P (2003) Ultrasound grading of cerebral ventricular dilatation in preterm neonates. J Paediatr Child Health 39:186–190

    Article  PubMed  CAS  Google Scholar 

  40. Maunu J, Lehtonen L, Lapinleimu H et al (2011) Ventricular dilatation in relation to outcome at 2 years of age in very preterm infants: a prospective Finnish cohort study. Dev Med Child Neurol 53:48–54

    Article  PubMed  Google Scholar 

  41. El-Dib M, Massaro AN, Bulas D et al (2010) Neuroimaging and neurodevelopmental outcome of premature infants. Am J Perinatol 27:803–818

    Article  PubMed  Google Scholar 

  42. Del Bigio MR (1993) Neuropathological changes caused by hydrocephalus. Acta Neuropathol 85:573–585

    Article  PubMed  Google Scholar 

  43. Del Bigio MR (2001) Pathophysiologic consequences of hydrocephalus. Neurosurg Clin N Am 12:639–649

    PubMed  Google Scholar 

  44. Del Bigio MR, da Silva MC, Drake JM et al (1994) Acute and chronic cerebral white matter damage in neonatal hydrocephalus. Can J Neurol Sci 21:299–305

    PubMed  Google Scholar 

  45. Kuban KC, Allred EN, O’Shea TM et al (2009) Cranial ultrasound lesions in the NICU predict cerebral palsy at age 2 years in children born at extremely low gestational age. J Child Neurol 24:63–72

    Article  PubMed  Google Scholar 

  46. Skranes JS, Vik T, Nilsen G et al (1993) Cerebral magnetic resonance imaging (MRI) and mental and motor function of very low birth weight infants at one year of corrected age. Neuropediatrics 24:256–262

    Article  PubMed  CAS  Google Scholar 

  47. Dyet LE, Kennea N, Counsell SJ et al (2006) Natural history of brain lesions in extremely preterm infants studied with serial magnetic resonance imaging from birth and neurodevelopmental assessment. Pediatrics 118:536–548

    Article  PubMed  Google Scholar 

  48. Volpe JJ (2005) Encephalopathy of prematurity includes neuronal abnormalities. Pediatrics 116(1):221–225

    Article  PubMed  Google Scholar 

  49. de Vries LS, Eken P, Dubowitz LM (1992) The spectrum of leukomalacia using cranial ultrasound. Behav Brain Res 49:1–6

    Article  PubMed  Google Scholar 

  50. Nanba Y, Matsui K, Aida N et al (2007) Magnetic resonance imaging regional T1 abnormalities at term accurately predict motor outcome in preterm infants. Pediatrics 120:e10–e19

    Article  PubMed  Google Scholar 

  51. Aida N, Nishimura G, Hachiya Y et al (1998) MR imaging of perinatal brain damage: comparison of clinical outcome with initial and follow-up MR findings. AJNR 19:1909–1921

    PubMed  CAS  Google Scholar 

  52. Olsen P, Paakko E, Vainionpaa L et al (1997) Magnetic resonance imaging of periventricular leukomalacia and its clinical correlation in children. Ann Neurol 41:754–761

    Article  PubMed  CAS  Google Scholar 

  53. Rutherford MA, Supramaniam V, Ederies A et al (2010) Magnetic resonance imaging of white matter diseases of prematurity. Neuroradiology 52(6):505–521

    Article  PubMed  Google Scholar 

  54. Niwa T, de Vries LS, Benders MJ et al (2011) Punctate white matter lesions in infants: new insights using susceptibility-weighted imaging. Neuroradiology 53(9):669–679 [May 7 Epub ahead of print]

    Article  PubMed  Google Scholar 

  55. Ramenghi LA, Fumagalli M, Righini A et al (2007) Magnetic resonance imaging assessment of brain maturation in preterm neonates with punctate white matter lesions. Neuroradiology 49(2):161–167

    Article  PubMed  Google Scholar 

  56. Bassi L, Chew A, Merchant N et al (2011) Diffusion tensor imaging in preterm infants with punctate white matter lesions. Pediatr Res 69(6):561–566

    Article  PubMed  Google Scholar 

  57. Cornette LG, Tanner SF, Ramenghi LA et al (2002) Magnetic resonance imaging of the infant brain: anatomical characteristics and clinical significance of punctate lesions. Arch Dis Child Fetal Neonatal Ed 86(3):F171–F177

    Article  PubMed  CAS  Google Scholar 

  58. Miller SP, Ferriero DM, Leonard C et al (2005) Early brain injury in premature newborns detected with magnetic resonance imaging is associated with adverse early neurodevelopmental outcome. J Pediatr 147(5):609–616

    Article  PubMed  Google Scholar 

  59. Volpe JJ (2003) Cerebral white matter injury of the premature infant – more common than you think. Pediatrics 112:176–180

    Article  PubMed  Google Scholar 

  60. Domizio S, Barbante E, Puglielli C et al (2005) Excessively high magnetic resonance signal in preterm infants and neuropsychobehavioural follow-up at 2 years. Int J Immunopathol Pharmacol 18:365–375

    PubMed  CAS  Google Scholar 

  61. Skiöld B, Horsch S, Hallberg B et al (2010) White matter changes in extremely preterm infants, a population-based diffusion tensor imaging study. Acta Paediatr 99(6):842–849

    Article  PubMed  Google Scholar 

  62. Srinivasan L, Dutta R, Counsell SJ et al (2007) Quantification of deep gray matter in preterm infants at term-equivalent age using manual volumetry of 3-tesla magnetic resonance images. Pediatrics 119(4):759–765

    Article  PubMed  Google Scholar 

  63. Boardman JP, Counsell SJ, Rueckert D et al (2006) Abnormal deep grey matter development following preterm birth detected using deformation-based morphometry. Neuroimage 32(1):70–78

    Article  PubMed  Google Scholar 

  64. Hart AR, Smith MF, Rigby AS et al (2010) Appearances of diffuse excessive high signal intensity (DEHSI) on MR imaging following preterm birth. Pediatr Radiol 40:1390–1396

    Article  PubMed  Google Scholar 

  65. Skiöld B (2010) Brain imaging and outcome in extremely preterm infants. Arch Dis Child Fetal Neonatal Ed 95(5):F310–F314

    Article  PubMed  Google Scholar 

  66. Kim JH, Jeon TY, Yoo S-Y et al (2011) Neurodevelopmental outcomes in preterm infants wcbith diffuse excessive high signal intensity seen on MRI at near term-equivalent age. Pediatr Radiol 41(Suppl 1):S296, Abstract NE1-5

    Google Scholar 

  67. Kidokoro H, Anderson PJ, Doyle LW et al (2011) High signal intensity on T2-weighted MR imaging at term-equivalent age in preterm infants does not predict 2-year neurodevelopmental putcomes. AJNR. doi:10.3174/ajnr.A2703

  68. Counsell SJ, Allsop JM, Harrison MC et al (2003) Diffusion-weighted imaging of the brain in preterm infants with focal and diffuse white matter abnormality. Pediatrics 112:1–7

    Article  PubMed  Google Scholar 

  69. Krishnan ML, Dyet LE, Boardman JP et al (2007) Relationship between white matter apparent diffusion coefficients in preterm infants at term-equivalent age and developmental outcome at 2 years. Pediatrics 120:e604–e609

    Article  PubMed  Google Scholar 

  70. Inder TE, Warfield SK, Wang H et al (2005) Abnormal cerebral structure is present at term in premature infants. Pediatrics 115:286–294

    Article  PubMed  Google Scholar 

  71. Peterson BS, Anderson AW, Ehrenkranz R et al (2003) Regional brain volumes and their later neurodevelopmental correlates in term and preterm infants. Pediatrics 111:939–948

    Article  PubMed  Google Scholar 

  72. Rademaker KJ, Lam JN, Van Haastert IC et al (2004) Larger corpus callosum size with better motor performance in prematurely born children. Semin Perinatol 28:279–287

    Article  PubMed  CAS  Google Scholar 

  73. Iai M, Tanabe Y, Goto M et al (1994) A comparative magnetic resonance imaging study of the corpus callosum in neurologically normal children and children with spastic diplegia. Acta Paediatr 83:1086–1090

    Article  PubMed  CAS  Google Scholar 

  74. Panigrahy A, Barnes PD, Robertson RL et al (2005) Quantitative analysis of the corpus callosum in children with cerebral palsy and developmental delay: correlation with cerebral white matter volume. Pediatr Radiol 35:1199–1207

    Article  PubMed  Google Scholar 

  75. Nosarti C, Rushe TM, Woodruff PW et al (2004) Corpus callosum size and very preterm birth: relationship to neuropsychological outcome. Brain 127:2080–2089

    Article  PubMed  Google Scholar 

  76. Anderson NG, Laurent I, Cook N et al (2005) Growth rate of corpus callosum in very premature infants. AJNR 26:2685–2690

    PubMed  Google Scholar 

  77. Anderson NG, Laurent I, Woodward LJ et al (2006) Detection of impaired growth of the corpus callosum in premature infants. Pediatrics 118:951–960

    Article  PubMed  Google Scholar 

  78. Rose J, Butler EE, Lamont LE et al (2009) Neonatal brain structure on MRI and diffusion tensor imaging, sex, and neurodevelopment in very-low-birthweight preterm children. Dev Med Child Neurol 51:526–535

    Article  PubMed  Google Scholar 

  79. Counsell SJ, Edwards AD, Chew AT et al (2008) Specific relations between neurodevelopmental abilities and white matter microstructure in children born preterm. Brain 131:3201–3208

    Article  PubMed  Google Scholar 

  80. De Vries LS, Groenendaal F, van Haastert IC et al (1999) Asymmetrical myelination of the posterior limb of the internal capsule in infants with periventricular haemorrhagic infarction: an early predictor of hemiplegia. Neuropediatrics 30:314–319

    Article  PubMed  Google Scholar 

  81. Roelants-van Rijn AM, Groenendaal F, Beek FJ et al (2001) Parenchymal brain injury in the preterm infant: comparison of cranial ultrasound, MRI and neurodevelopmental outcome. Neuropediatrics 32:80–89

    Article  PubMed  CAS  Google Scholar 

  82. Arzoumanian Y, Mirmiran M, Barnes PD et al (2003) Diffusion tensor brain imaging findings at term-equivalent age may predict neurologic abnormalities in low birth weight preterm infants. AJNR 24:1646–1653

    PubMed  CAS  Google Scholar 

  83. Rose J, Mirmiran M, Butler EE et al (2007) Neonatal microstructural development of the internal capsule on diffusion tensor imaging correlates with severity of gait and motor deficits. Dev Med Child Neurol 49:745–750

    Article  PubMed  Google Scholar 

  84. Murakami A, Morimoto M, Yamada K et al (2008) Fiber-tracking techniques can predict the degree of neurologic impairment for periventricular leukomalacia. Pediatrics 122:500–506

    Article  PubMed  Google Scholar 

  85. O’Connor AR, Fielder AR (2007) Visual outcomes and perinatal adversity. Semin Fetal Neonatal Med 12:408–414

    Article  PubMed  Google Scholar 

  86. Shah DK, Guinane C, August P et al (2006) Reduced occipital regional volumes at term predict impaired visual function in early childhood in very low birth weight infants. Invest Ophthalmol Vis Sci 47:3366–3373

    Article  PubMed  Google Scholar 

  87. Berman JI, Glass HC, Miller SP et al (2009) Quantitative fiber tracking analysis of the optic radiation correlated with visual performance in premature newborns. AJNR 30:120–124

    Article  PubMed  CAS  Google Scholar 

  88. Bassi L, Ricci D, Volzone A et al (2008) Probabilistic diffusion tractography of the optic radiations and visual function in preterm infants at term equivalent age. Brain 131:573–582

    Article  PubMed  Google Scholar 

  89. Kapellou O, Counsell SJ, Kennea N et al (2006) Abnormal cortical development after premature birth shown by altered allometric scaling of brain growth. PLoS Med 3:e265

    Article  PubMed  Google Scholar 

  90. Nosarti C, Al-Asady MH, Frangou S et al (2002) Adolescents who were born very preterm have decreased brain volumes. Brain 125:1616–1623

    Article  PubMed  Google Scholar 

  91. Dubois J, Benders M, Borradori-Tolsa C et al (2008) Primary cortical folding in the human newborn: an early marker of later functional development. Brain 131:2028–2041

    Article  PubMed  CAS  Google Scholar 

  92. Soria-Pastor S, Padilla N, Zubiaurre-Elorza L et al (2009) Decreased regional brain volume and cognitive impairment in preterm children at low risk. Pediatrics 124:e1161–e1170

    Article  PubMed  Google Scholar 

  93. Peterson BS, Vohr B, Staib LH et al (2000) Regional brain volume abnormalities and long-term cognitive outcome in preterm infants. JAMA 284:1939–1947

    Article  PubMed  CAS  Google Scholar 

  94. Anderson P, Doyle LW (2003) Neurobehavioral outcomes of school-age children born extremely low birth weight or very preterm in the 1990s. JAMA 289:3264–3272

    Article  PubMed  Google Scholar 

  95. Woodward LJ, Edgin JO, Thompson D et al (2005) Object working memory deficits predicted by early brain injury and development in the preterm infant. Brain 128:2578–2587

    Article  PubMed  Google Scholar 

  96. Beauchamp MH, Thompson DK, Howard K et al (2008) Preterm infant hippocampal volumes correlate with later working memory deficits. Brain 131:2986–2994

    Article  PubMed  Google Scholar 

  97. Limperopoulos C, Bassan H, Gauvreau K et al (2007) Does cerebellar injury in premature infants contribute to the high prevalence of long-term cognitive, learning, and behavioral disability in survivors? Pediatrics 120:584–593

    Article  PubMed  Google Scholar 

  98. Limperopoulos C, Benson CB, Bassan H et al (2005) Cerebellar hemorrhage in the preterm infant: ultrasonographic findings and risk factors. Pediatrics 116:717–724

    Article  PubMed  Google Scholar 

  99. Bednarek N, Akhavi A, Pietrement C et al (2008) Outcome of cerebellar injury in very low birth-weight infants: 6 case reports. J Child Neurol 23:906–911

    Article  PubMed  Google Scholar 

  100. Tam EW, Rosenbluth G, Rogers EE et al (2011) Cerebellar hemorrhage on magnetic resonance imaging in preterm newborns associated with abnormal neurologic outcome. J Pediatri 158:245–250

    Article  Google Scholar 

  101. Ecury-Goossen GM, Dudink J, Lequin M et al (2010) The clinical presentation of preterm cerebellar haemorrhage. Eur J Pediatr 169:1249–1253

    Article  PubMed  Google Scholar 

  102. Merrill JD, Piecuch RE, Fell SC et al (1998) A new pattern of cerebellar hemorrhages in preterm infants. Pediatrics 102:E62

    Article  PubMed  CAS  Google Scholar 

  103. Steggerda SJ, Leijser LM, Wiggers-de Bruine FT et al (2009) Cerebellar injury in preterm infants: incidence and findings on US and MR images. Radiology 252:190–199

    Article  PubMed  Google Scholar 

  104. Shah DK, Anderson PJ, Carlin JB et al (2006) Reduction in cerebellar volumes in preterm infants: relationship to white matter injury and neurodevelopment at two years of age. Pediatr Res 60:97–102

    Article  PubMed  Google Scholar 

  105. Srinivasan L, Allsop J, Counsell SJ et al (2006) Smaller cerebellar volumes in very preterm infants at term-equivalent age are associated with the presence of supratentorial lesions. AJNR 27:573–579

    PubMed  CAS  Google Scholar 

  106. Lind A, Parkkola R, Lehtonen L et al (2011) Associations between regional brain volumes at term-equivalent age and development at 2 years of age in preterm children. Pediatr Radiol 41:953–961

    Article  PubMed  Google Scholar 

  107. Tam EW, Miller SP, Studholme C et al (2011) Differential effects of intraventricular hemorrhage and white matter injury on cerebellar growth. J Pediatr 158(3):366–371

    Article  PubMed  Google Scholar 

  108. Limperopoulos C, Chilingaryan G, Gulzard N et al (2010) Cerebellar injury in the premature infant is associated with impaired growth of specific cerebral regions. Pediatr Res 68(2):145–150

    Article  PubMed  Google Scholar 

  109. Woodward LJ, Anderson PJ, Austin NC et al (2006) Neonatal MRI to predict neurodevelopmental outcomes in preterm infants. N Engl J Med 355:685–694

    Article  PubMed  CAS  Google Scholar 

  110. Valkama AM, Paakko EL, Vainionpaa LK et al (2000) Magnetic resonance imaging at term and neuromotor outcome in preterm infants. Acta Paediatr 89:348–355

    Article  PubMed  CAS  Google Scholar 

  111. Kreis R, Hofmann L, Kuhlmann B et al (2002) Brain metabolite composition during early human brain development as measured by quantitative in vivo 1H magnetic resonance spectroscopy. Magn Reson Med 48:949–958

    Article  PubMed  CAS  Google Scholar 

  112. Leth H, Toft PB, Pryds O et al (1995) Brain lactate in preterm and growth-retarded neonates. Acta Paediatr 84:495–499

    Article  PubMed  CAS  Google Scholar 

  113. Wang ZJ, Vigneron DB, Miller SP et al (2008) Brain metabolite levels assessed by lactate-edited MR spectroscopy in premature neonates with and without pentobarbital sedation. AJNR 29:798–801

    Article  PubMed  CAS  Google Scholar 

  114. Roelants-van Rijn AM, van der Grond J, Stigter RH et al (2004) Cerebral structure and metabolism and long-term outcome in small-for-gestational-age preterm neonates. Pediatr Res 56:285–290

    Article  PubMed  Google Scholar 

  115. Augustine EM, Spielman DM, Barnes PD et al (2008) Can magnetic resonance spectroscopy predict neurodevelopmental outcome in very low birth weight preterm infants? J Perinatol 28:611–618

    Article  PubMed  CAS  Google Scholar 

  116. Bode H, Wais U (1988) Age dependence of flow velocities in basal cerebral arteries. Arch Dis Child 63:606–611

    Article  PubMed  CAS  Google Scholar 

  117. Kehrer M, Krageloh-Mann I, Goelz R et al (2003) The development of cerebral perfusion in healthy preterm and term neonates. Neuropediatrics 34:281–286

    Article  PubMed  CAS  Google Scholar 

  118. Perlman JM, McMenamin JB, Volpe JJ (1983) Fluctuating cerebral blood-flow velocity in respiratory-distress syndrome. Relation to the development of intraventricular hemorrhage. N Engl J Med 309:204–209

    Article  PubMed  CAS  Google Scholar 

  119. Julkunen M, Parviainen T, Janas M et al (2008) End-diastolic block in cerebral circulation may predict intraventricular hemorrhage in hypotensive extremely-low-birth-weight infants. Ultrasound Med Biol 34:538–545

    Article  PubMed  Google Scholar 

  120. Westra SJ, Lazareff J, Curran JG et al (1998) Transcranial Doppler ultrasonography to evaluate need for cerebrospinal fluid drainage in hydrocephalic children. J Ultrasound Med 17:561–569

    PubMed  CAS  Google Scholar 

  121. Taylor GA, Madsen JR (1996) Neonatal hydrocephalus: hemodynamic response to fontanelle compression – correlation with intracranial pressure and need for shunt placement. Radiology 201:685–689

    PubMed  CAS  Google Scholar 

  122. Nguyen The Tich S, Anderson PJ, Shimony JS (2009) A novel quantitative simple brain metric using MR imaging for preterm infants. AJNR 30(1):125–131

    Article  PubMed  CAS  Google Scholar 

  123. Tich SN, Anderson PJ, Hunt RW et al (2011) Neurodevelopmental and perinatal correlates of simple brain metrics in very preterm infants. Arch Pediatr Adolesc Med 165(3):216–222

    Article  PubMed  Google Scholar 

  124. Biswal B, Yetkin FZ, Haughton VM et al (1995) Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 34:537–541

    Article  PubMed  CAS  Google Scholar 

  125. Lowe MJ, Mock BJ, Sorenson JA (1998) Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations. Neuroimage 7:119–132

    Article  PubMed  CAS  Google Scholar 

  126. Beckmann CF, DeLuca M, Devlin JT et al (2005) Investigations into resting-state connectivity using independent component analysis. Philos Trans R Soc Lond B Biol Sci 360:1001–1013

    Article  PubMed  Google Scholar 

  127. Fox MD, Snyder AZ, Vincent JL et al (2005) The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci USA 102:9673–9678

    Article  PubMed  CAS  Google Scholar 

  128. Fransson P, Skiold B, Horsch S et al (2007) Resting-state networks in the infant brain. Proc Natl Acad Sci USA 104:15531–15536

    Article  PubMed  CAS  Google Scholar 

  129. Smyser CD, Inder TE, Shimony JS et al (2010) Longitudinal analysis of neural network development in preterm infants. Cereb Cortex 20:2852–2862

    Article  PubMed  Google Scholar 

  130. Doria V, Beckmann CF, Arichi T et al (2010) Emergence of resting state networks in the preterm human brain. Proc Natl Acad Sci USA 107(46):20015–20020

    Article  PubMed  CAS  Google Scholar 

  131. Kostovic I, Jovanov-Milosevic N (2006) The development of cerebral connections during the first 20–45 weeks’ gestation. Semin Fetal Neonatal Med 11:415–422

    Article  PubMed  Google Scholar 

  132. Damaraju E, Phillips JR, Lowe JR et al (2010) Resting-state functional connectivity differences in premature children. Front Syst Neuro 4:23

    Google Scholar 

  133. de Vries LS, Cowan FM (2007) Should cranial MRI screening of preterm infants become routine? Nat Clin Pract Neurol 3(10):532–533

    Article  PubMed  Google Scholar 

  134. Hintz SR, O’Shea M (2008) Neuroimaging and neurodevelopmental outcomes in preterm infants. Semin Perinatol 32(1):11–19

    Article  PubMed  Google Scholar 

  135. Hart AR, Whitby EW, Griffiths PD et al (2008) Magnetic resonance imaging and developmental outcome following preterm birth: review of current evidence. Dev Med Child Neurol 50(9):655–663

    Article  PubMed  Google Scholar 

  136. Ment LR, Bada HS, Barnes P et al (2002) Practice parameter: neuroimaging of the neonate. Report of the quality standards subcommittee of the American academy of neurology and the practice committee of the child neurology society. Neurology 58:1726–1738

    PubMed  CAS  Google Scholar 

  137. Nosarti C, Walshe M, Rushe TM et al (2011) Neonatal ultrasound results following very preterm birth predict adolescent behavioral and cognitive outcome. Dev Neuropsychol 36(1):118–135

    Article  PubMed  CAS  Google Scholar 

  138. Clark CA, Woodward LJ (2010) Neonatal cerebral abnormalities and later verbal and visuospatial working memory abilities of children born very preterm. Dev Neuropsychol 35(6):622–642

    Article  PubMed  Google Scholar 

  139. Woodward LJ, Clark CA, Pritchard VE et al (2011) Neonatal white matter abnormalities predict global executive function impairment in children born very preterm. Dev Neuropsychol 36(1):22–41

    Article  PubMed  Google Scholar 

  140. Munck P, Haataja L, Maunu J et al (2010) Cognitive outcome at 2 years of age in Finnish infants with very low birth weight born between 2001 and 2006. Acta Paediatr 99(3):359–366

    Article  PubMed  CAS  Google Scholar 

  141. Horsch S, Skiold B, Hallberg B et al (2009) Cranial ultrasound and MRI at term age in extremely preterm infants. Arch Dis Child Fetal Neonatal Ed 95:19

    Google Scholar 

  142. Kinney HC (2006) The near term (late preterm) human brain and risk for periventricular leukomalacia: a review. Semin Perinatol 30(2):81–88

    Article  PubMed  Google Scholar 

  143. O’Shea TM, Klinepeter KL, Dillard RG (1998) Prenatal events and the risk of cerebral palsy in very low birth weight infants. Am J Epidemiol 147:362–369

    PubMed  Google Scholar 

  144. Laptook AR, O’Shea TM, Shankaran S et al (2005) Adverse neurodevelopmental outcomes among extremely low birth weight infants with a normal head ultrasound: prevalence and antecedents. Pediatrics 115:673–680

    Article  PubMed  Google Scholar 

  145. Wood NS, Costeloe K, Gibson AT et al (2005) The EPICure study: associations and antecedents of neurological and developmental disability at 30 months of age following extremely preterm birth. Arch Dis Child Fetal Neonatal Ed 90:F134–F140

    Article  PubMed  CAS  Google Scholar 

  146. Shah DK, Doyle LW, Anderson PJ et al (2008) Adverse neurodevelopment in preterm infants with postnatal sepsis or necrotizing enterocolitis is mediated by white matter abnormalities on magnetic resonance imaging at term. J Pediatr 153:170–175

    Article  PubMed  Google Scholar 

  147. Glass HC, Bonifacio SL, Chau V et al (2008) Recurrent postnatal infections are associated with progressive white matter injury in premature infants. Pediatrics 122:299–305

    Article  PubMed  Google Scholar 

  148. Chau V, Poskitt KJ, McFadden DE et al (2009) Effect of chorioamnionitis on brain development and injury in premature newborns. Ann Neurol 66:155–164

    Article  PubMed  Google Scholar 

  149. Doyle LW, Cheong J, Hunt RW (2010) Caffeine and brain development in very preterm infants. Ann Neurol 68(5):734–742

    Article  PubMed  CAS  Google Scholar 

  150. Murphy BP, Inder TE, Huppi PS et al (2001) Impaired cerebral cortical gray matter growth after treatment with dexamethasone for neonatal chronic lung disease. Pediatrics 107(2):217–221

    Article  PubMed  CAS  Google Scholar 

  151. Als H, Duffy FH, McAnulty GB et al (2004) Early experience alters brain function and structure. Pediatrics 113(4):846–857

    Article  PubMed  Google Scholar 

  152. Milgrom J, Newnham C, Anderson PJ et al (2010) Early sensitivity training for parents of preterm infants: impact on the developing brain. Pediatric Res 67(3):330–335

    Article  Google Scholar 

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Acknowledgments

The authors thank Dr. Susan Hintz (Stanford) for comments and edits of the manuscript. The authors thank Julie Castro, Arabhi Nagasunder, Anita Hamilton, Hesham Mahmoud and Sandra Figueroa (Children’s Los Angeles) and Rafael Ceschin and Fern Wasco (Pittsburgh Children’s) and the MR technologists at Children’s Los Angeles and Children’s Pittsburgh for their commitment toward the multisite perinatal white matter injury project. We acknowledge Anita Hamilton for helping with the development of the preterm neuropsychological battery. We would also like to acknowledge Dr. Bharat Biswal for the functional connectivity collaboration and analysis and Dr. Yalin Wang for the collaboration and analysis with the surface base morphometric analysis. We also thank Drs. Hannah Kinney, Robin Haynes, Hanna Damasio, Marvin Nelson and Floyd Gilles for insight and advice. We thank Melanie Gierltowski for manuscript preparation. This study is funded by: K23NS063371 (AP), P50NS01962 (JLW), and Rudi Schulte Foundation (SB), R21EB012177 (NL) and USC-CHLA CTSI grant 1UL1RR031986 (AP, JLW, LP).

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The supplement this article is part of is not sponsored by the industry. Dr. Panigrahy, Dr. Wisnowski, Dr. Furtado, Dr. Lepore, Dr. Paquette, and Dr. Bluml have no financial interest, investigational or off-label uses to disclose.

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Panigrahy, A., Wisnowski, J.L., Furtado, A. et al. Neuroimaging biomarkers of preterm brain injury: toward developing the preterm connectome. Pediatr Radiol 42 (Suppl 1), 33–61 (2012). https://doi.org/10.1007/s00247-011-2239-4

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  • DOI: https://doi.org/10.1007/s00247-011-2239-4

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