Anatomical characterization of athetotic and spastic cerebral palsy using an atlas-based analysis

J Magn Reson Imaging. 2013 Aug;38(2):288-98. doi: 10.1002/jmri.23931. Epub 2013 Jun 4.

Abstract

Purpose: To analyze diffusion tensor imaging (DTI) in two types of cerebral palsy (CP): the athetotic-type and the spastic-type, using an atlas-based anatomical analysis of the entire brain, and to investigate whether these images have unique anatomical characteristics that can support functional diagnoses.

Materials and methods: We retrospectively analyzed the DTI of seven children with athetotic-type, 11 children with spastic-type, and 20 healthy control children, all age-matched. The severity of motor dysfunction was evaluated with the Gross Motor Function Classification System (GMFCS). The images were normalized using a linear transformation, followed by large deformation diffeomorphic metric mapping. For 205 parcellated brain areas, the volume, fractional anisotropy, and mean diffusivity were measured. Principal component analysis (PCA) was performed for the Z-scores of these parameters.

Results: The GMFCS scores in athetotic-type were significantly higher than those in spastic-type (P < 0.001). PCA extracted anatomical components that comprised the two types of CP, as well as the severity of motor dysfunction. In the athetotic group, the abnormalities were more severe than in the spastic group. In the spastic group, significant changes were concentrated in the lateral ventricle and periventricular structures.

Conclusion: Our results quantitatively delineated anatomical characteristics that reflected the functional findings in two types of CP.

Keywords: atlas-based analysis; cerebral palsy; diffusion tensor imaging; principal component analysis.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adolescent
  • Algorithms
  • Brain / pathology*
  • Cerebral Palsy / classification*
  • Cerebral Palsy / pathology*
  • Child
  • Child, Preschool
  • Diagnosis, Differential
  • Diffusion Tensor Imaging / methods*
  • Female
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods*
  • Male
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Signal Processing, Computer-Assisted
  • Subtraction Technique*