Literature DB >> 15193620

Delayed myelination in children with developmental delay detected by volumetric MRI.

Jesús Pujol1, Anna López-Sala, Núria Sebastián-Gallés, Joan Deus, Narcís Cardoner, Carles Soriano-Mas, Angel Moreno, Anna Sans.   

Abstract

Delayed acquisition of developmental motor and cognitive milestones is a common clinical expression of many etiological processes. Imaging exams of developmentally delayed children often show no structural brain alterations despite suspicion of brain maturation delay. MRI studies increasingly suggest that white matter myelination finely reflects the progression in functional brain maturation. In this volumetric MRI study, we sought to evaluate whether developmental delay in children with normal conventional MRI exams is associated with reduced myelinated white matter. A total of 100 children (mean age, 4.4 years) with developmental delay and 50 normally developing age-matched control children underwent 3-D MRI to measure the volume of myelinated white matter. Patients showed a significant reduction in the relative content of myelinated white matter (accounting for 19.8% of brain volume in patients and 21.4% in control subjects, P = 0.005). The observed difference was equivalent to a 3.2-year myelination delay. Although the whole hemispheres were invariably symmetrical, the volume of myelinated white matter was asymmetrical in 30% of patients and 10% of control subjects (P = 0.006). We conclude that volumetric assessment of white matter may reveal a reduction in brain myelination beyond early childhood in developmentally delayed children showing normal brain appearance. This finding further emphasizes the view of white matter myelination as an indicator of functional brain maturation.

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Year:  2004        PMID: 15193620     DOI: 10.1016/j.neuroimage.2004.01.029

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  17 in total

Review 1.  Development of structure and function in the infant brain: implications for cognition, language and social behaviour.

Authors:  Sarah J Paterson; Sabine Heim; Jennifer Thomas Friedman; Naseem Choudhury; April A Benasich
Journal:  Neurosci Biobehav Rev       Date:  2006-08-04       Impact factor: 8.989

2.  Normal volumetric and T1 relaxation time values at 1.5 T in segmented pediatric brain MRI using a MP2RAGE acquisition.

Authors:  Baptiste Morel; Gian Franco Piredda; Jean-Philippe Cottier; Clovis Tauber; Christophe Destrieux; Tom Hilbert; Dominique Sirinelli; Jean-Philippe Thiran; Bénédicte Maréchal; Tobias Kober
Journal:  Eur Radiol       Date:  2020-09-03       Impact factor: 5.315

3.  Longitudinal atlas for normative human brain development and aging over the lifespan using quantitative susceptibility mapping.

Authors:  Yuyao Zhang; Hongjiang Wei; Matthew J Cronin; Naying He; Fuhua Yan; Chunlei Liu
Journal:  Neuroimage       Date:  2018-01-08       Impact factor: 6.556

4.  Quantification of myelin in children using multiparametric quantitative MRI: a pilot study.

Authors:  Hyun Gi Kim; Won-Jin Moon; JinJoo Han; Jin Wook Choi
Journal:  Neuroradiology       Date:  2017-08-01       Impact factor: 2.804

5.  Substance use and mothers' neural responses to infant cues.

Authors:  Amanda F Lowell; Angela N Maupin; Nicole Landi; Marc N Potenza; Linda C Mayes; Helena J V Rutherford
Journal:  Infant Ment Health J       Date:  2020-02-14

6.  Developmental trajectories of brain structure in adolescents with 22q11.2 deletion syndrome: a longitudinal study.

Authors:  Doron Gothelf; Lauren Penniman; Eugene Gu; Stephan Eliez; Allan L Reiss
Journal:  Schizophr Res       Date:  2007-09-04       Impact factor: 4.939

7.  Structural brain differences in school-age children with residual speech sound errors.

Authors:  Jonathan L Preston; Peter J Molfese; W Einar Mencl; Stephen J Frost; Fumiko Hoeft; Robert K Fulbright; Nicole Landi; Elena L Grigorenko; Ayumi Seki; Susan Felsenfeld; Kenneth R Pugh
Journal:  Brain Lang       Date:  2013-12-15       Impact factor: 2.381

8.  Sparse multiple factor analysis to integrate genetic data, neuroimaging features, and attention-deficit/hyperactivity disorder domains.

Authors:  Natàlia Vilor-Tejedor; Silvia Alemany; Alejandro Cáceres; Mariona Bustamante; Marion Mortamais; Jesús Pujol; Jordi Sunyer; Juan R González
Journal:  Int J Methods Psychiatr Res       Date:  2018-08-14       Impact factor: 4.035

9.  Brain differences in infants at differential genetic risk for late-onset Alzheimer disease: a cross-sectional imaging study.

Authors:  Douglas C Dean; Beth A Jerskey; Kewei Chen; Hillary Protas; Pradeep Thiyyagura; Auttawat Roontiva; Jonathan O'Muircheartaigh; Holly Dirks; Nicole Waskiewicz; Katie Lehman; Ashley L Siniard; Mari N Turk; Xue Hua; Sarah K Madsen; Paul M Thompson; Adam S Fleisher; Matthew J Huentelman; Sean C L Deoni; Eric M Reiman
Journal:  JAMA Neurol       Date:  2014-01       Impact factor: 18.302

10.  Myelination as assessed by conventional MR imaging is normal in young children with idiopathic developmental delay.

Authors:  S M Maricich; P Azizi; J Y Jones; M C Morriss; J V Hunter; E O Smith; G Miller
Journal:  AJNR Am J Neuroradiol       Date:  2007-09       Impact factor: 3.825

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