An optimised tract-based spatial statistics protocol for neonates: applications to prematurity and chronic lung disease

Abstract

Preterm birth is associated with altered white matter microstructure, defined by metrics derived from diffusion tensor imaging (DTI). Tract-based spatial statistics (TBSS) is a useful tool for investigating developing white matter using DTI, but standard TBSS protocols have limitations for neonatal studies. We describe an optimised TBSS protocol for neonatal DTI data, in which registration errors are reduced. As chronic lung disease (CLD) is an independent risk factor for abnormal white matter development, we investigate the effect of this condition on white matter anisotropy and diffusivity using the optimised protocol in a proof of principle experiment. DTI data were acquired from 93 preterm infants (48 male) with a median gestational age at birth of 28(+5) (23(+4)-35(+2))weeks at a median postmenstrual age at scan of 41(+4) (38(+1)-46(+6))weeks. Nineteen infants developed CLD, defined as requiring supplemental oxygen at 36weeks postmenstrual age. TBSS was modified to include an initial low degrees-of-freedom linear registration step and a second registration to a population-average FA map. The additional registration steps reduced global misalignment between neonatal fractional anisotropy (FA) maps. Infants with CLD had significantly increased radial diffusivity (RD) and significantly reduced FA within the centrum semiovale, corpus callosum and inferior longitudinal fasciculus (p<0.05) compared to their peers, controlling for degree of prematurity and age at scan. The optimised TBSS protocol improved reliability for neonatal DTI analysis. These data suggest that potentially modifiable respiratory morbidity is associated with widespread altered white matter microstructure in preterm infants at term-equivalent age.