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

Gareth Ball, Serena J Counsell, Mustafa Anjari, Nazakat Merchant, Tomoki Arichi, Valentina Doria, Mary A Rutherford, A David Edwards, Daniel Rueckert, James P Boardman

Research output: Contribution to journalArticlepeer-review

150 Citations (Scopus)

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
Original languageEnglish
Pages (from-to)94-102
Number of pages9
JournalNeuroImage
Volume53
Issue number1
DOIs
Publication statusPublished - 15 Oct 2010

Fingerprint

Dive into the research topics of 'An optimised tract-based spatial statistics protocol for neonates: applications to prematurity and chronic lung disease'. Together they form a unique fingerprint.

Cite this