Holoprosencephaly in children: diffusion tensor MR imaging of white matter tracts of the brainstem--initial experience

Radiology. 2002 Jun;223(3):645-51. doi: 10.1148/radiol.2233011197.

Abstract

Purpose: To evaluate the dimensions of specific white matter tracts in the brainstems (region of brain thought to be least affected) of children with holoprosencephaly by using diffusion tensor magnetic resonance (MR) imaging and to correlate these abnormalities with forebrain malformation severity and neurologic deficit severity.

Materials and methods: Thirteen patients with holoprosencephaly underwent diffusion tensor MR imaging, with which white matter color maps were generated. Type of holoprosencephaly was correlated with presence or absence of specific brainstem white matter tracts. Furthermore, patient rank based on cortico-ponto-spinal tract (CPST) and middle cerebellar peduncle (MCP) dimensions was correlated with holoprosencephaly type and neurodevelopmental score by using Spearman rank correlation analysis.

Results: Two patients had alobar holoprosencephaly, five had the semilobar type, one had the lobar type, and one had the middle-hemisphere-variant type. Four patients were excluded from analysis. In the two patients with alobar holoprosencephaly, the CPSTs were absent bilaterally. In all of the remaining patients except one, who had semilobar holoprosencephaly in which the CPSTs could not be identified at the level of the medulla oblongata, all tracts were present bilaterally. Holoprosencephaly type and neurodevelopmental score correlated strongly with CPST and MCP dimensions (P <.01) over and above the effect of age.

Conclusion: In vivo identification of brainstem white matter tract abnormalities in patients with holoprosencephaly can be achieved by performing diffusion tensor MR imaging.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain Mapping
  • Brain Stem / pathology*
  • Case-Control Studies
  • Child
  • Child, Preschool
  • Female
  • Holoprosencephaly / pathology*
  • Humans
  • Image Processing, Computer-Assisted
  • Infant
  • Infant, Newborn
  • Magnetic Resonance Imaging / methods*
  • Male
  • Statistics, Nonparametric