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Magnetic resonance imaging pattern recognition in hypomyelinating disorders

Steenweg, Marjan E. ; Vanderver, Adeline ; Blaser, Susan ; Bizzi, Alberto ; De Koning, Tom J. LU ; Mancini, Grazia M.S. ; Van Wieringen, Wessel N. ; Barkhof, Frederik ; Wolf, Nicole I. and Van Der Knaap, Marjo S. (2010) In Brain 133(10). p.2971-2982
Abstract

Hypomyelination is observed in the context of a growing number of genetic disorders that share clinical characteristics. The aim of this study was to determine the possible role of magnetic resonance imaging pattern recognition in distinguishing different hypomyelinating disorders, which would facilitate the diagnostic process. Only patients with hypomyelination of known cause were included in this retrospective study. A total of 112 patients with Pelizaeus-Merzbacher disease, hypomyelination with congenital cataract, hypomyelination with hypogonadotropic hypogonadism and hypodontia, Pelizaeus-Merzbacher-like disease, infantile GM1 and GM2 gangliosidosis, Salla disease and fucosidosis were included. The brain scans were rated using a... (More)

Hypomyelination is observed in the context of a growing number of genetic disorders that share clinical characteristics. The aim of this study was to determine the possible role of magnetic resonance imaging pattern recognition in distinguishing different hypomyelinating disorders, which would facilitate the diagnostic process. Only patients with hypomyelination of known cause were included in this retrospective study. A total of 112 patients with Pelizaeus-Merzbacher disease, hypomyelination with congenital cataract, hypomyelination with hypogonadotropic hypogonadism and hypodontia, Pelizaeus-Merzbacher-like disease, infantile GM1 and GM2 gangliosidosis, Salla disease and fucosidosis were included. The brain scans were rated using a standard scoring list; the raters were blinded to the diagnoses. Grouping of the patients was based on cluster analysis. Ten clusters of patients with similar magnetic resonance imaging abnormalities were identified. The most important discriminating items were early cerebellar atrophy, homogeneity of the white matter signal on T2-weighted images, abnormal signal intensity of the basal ganglia, signal abnormalities in the pons and additional T2 lesions in the deep white matter. Eight clusters each represented mainly a single disorder (i.e. Pelizaeus-Merzbacher disease, hypomyelination with congenital cataract, hypomyelination with hypogonadotropic hypogonadism and hypodontia, infantile GM1 and GM2 gangliosidosis, Pelizaeus-Merzbacher-like disease and fucosidosis); only two clusters contained multiple diseases. Pelizaeus-Merzbacher-like disease was divided between two clusters and Salla disease did not cluster at all. This study shows that it is possible to separate patients with hypomyelination disorders of known cause in clusters based on magnetic resonance imaging abnormalities alone. In most cases of Pelizaeus-Merzbacher disease, hypomyelination with congenital cataract, hypomyelination with hypogonadotropic hypogonadism and hypodontia, Pelizaeus-Merzbacher-like disease, infantile GM1 and GM2 gangliosidosis and fucosidosis, the imaging pattern gives clues for the diagnosis.

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author
publishing date
type
Contribution to journal
publication status
published
subject
keywords
hypomyelination, leukodystrophy, magnetic resonance imaging, pattern recognition
in
Brain
volume
133
issue
10
pages
12 pages
publisher
Oxford University Press
external identifiers
  • scopus:77957688535
  • pmid:20881161
ISSN
0006-8950
DOI
10.1093/brain/awq257
language
English
LU publication?
no
id
0cf07e4e-f7de-426e-b991-b799fae1a5c0
date added to LUP
2020-02-26 10:23:52
date last changed
2020-05-26 05:40:25
@article{0cf07e4e-f7de-426e-b991-b799fae1a5c0,
  abstract     = {<p>Hypomyelination is observed in the context of a growing number of genetic disorders that share clinical characteristics. The aim of this study was to determine the possible role of magnetic resonance imaging pattern recognition in distinguishing different hypomyelinating disorders, which would facilitate the diagnostic process. Only patients with hypomyelination of known cause were included in this retrospective study. A total of 112 patients with Pelizaeus-Merzbacher disease, hypomyelination with congenital cataract, hypomyelination with hypogonadotropic hypogonadism and hypodontia, Pelizaeus-Merzbacher-like disease, infantile GM1 and GM2 gangliosidosis, Salla disease and fucosidosis were included. The brain scans were rated using a standard scoring list; the raters were blinded to the diagnoses. Grouping of the patients was based on cluster analysis. Ten clusters of patients with similar magnetic resonance imaging abnormalities were identified. The most important discriminating items were early cerebellar atrophy, homogeneity of the white matter signal on T2-weighted images, abnormal signal intensity of the basal ganglia, signal abnormalities in the pons and additional T2 lesions in the deep white matter. Eight clusters each represented mainly a single disorder (i.e. Pelizaeus-Merzbacher disease, hypomyelination with congenital cataract, hypomyelination with hypogonadotropic hypogonadism and hypodontia, infantile GM1 and GM2 gangliosidosis, Pelizaeus-Merzbacher-like disease and fucosidosis); only two clusters contained multiple diseases. Pelizaeus-Merzbacher-like disease was divided between two clusters and Salla disease did not cluster at all. This study shows that it is possible to separate patients with hypomyelination disorders of known cause in clusters based on magnetic resonance imaging abnormalities alone. In most cases of Pelizaeus-Merzbacher disease, hypomyelination with congenital cataract, hypomyelination with hypogonadotropic hypogonadism and hypodontia, Pelizaeus-Merzbacher-like disease, infantile GM1 and GM2 gangliosidosis and fucosidosis, the imaging pattern gives clues for the diagnosis.</p>},
  author       = {Steenweg, Marjan E. and Vanderver, Adeline and Blaser, Susan and Bizzi, Alberto and De Koning, Tom J. and Mancini, Grazia M.S. and Van Wieringen, Wessel N. and Barkhof, Frederik and Wolf, Nicole I. and Van Der Knaap, Marjo S.},
  issn         = {0006-8950},
  language     = {eng},
  month        = {01},
  number       = {10},
  pages        = {2971--2982},
  publisher    = {Oxford University Press},
  series       = {Brain},
  title        = {Magnetic resonance imaging pattern recognition in hypomyelinating disorders},
  url          = {http://dx.doi.org/10.1093/brain/awq257},
  doi          = {10.1093/brain/awq257},
  volume       = {133},
  year         = {2010},
}