Surface Multivariate Tensor-based Morphometry on Premature Neonates: A Pilot Study

Prematurity is one of the leading causes of mental retardation in the United States. Finding the neuroanatomical correlates of prematurity is vital to understanding which structures are affected, and in designing treatments. Using brain structural MRI, we perform regional group comparisons of the surface anatomy of subcortical structures between healthy preterm and term-born neonates. We first reconstruct the surfaces of subcortical structure from manually segmented brain MR images and we then build parametric meshes on the surfaces by computing surface conformal parameterization with holomorphic 1-forms. Surfaces are registered by constrained harmonic maps on the parametric domains and statistical comparisons between the two groups are performed via multivariate tensor-based morphometry (mTBM).We have processed a total of 5 subcortical structures, the corpus collosum, thalamus, caudate nucleus, hippocampus and putamen, as well as the lateral ventricle and the 3rd ventricle. In this pilot study, we apply mTBM to analyze the thalamus, lateral ventricle and hippocampus in 10 term-born and 10 preterm neonates. We detect statistically significant morphological changes in the majority of the right ventricle as well as in the left pulvinar, a result that validates earlier whole volume analyses in this structure. The hippocampus results, while not significant, show a trend that may be become significant with a larger data set. Our mTBM analysis is also compared to the more commonly used medial axis distance (MAD) [21, 6], and to the combination of both methods. MTBM gives more powerful results than MAD, and the combination of both further improves detection power.