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

Area of Science:

• Neonatal neuroscience
• Medical imaging analysis
• Developmental brain science

Background:

• Preterm birth can lead to altered white matter microstructure, impacting neurodevelopment.
• Diffusion tensor imaging (DTI) and tract-based spatial statistics (TBSS) are key tools for studying white matter, but standard TBSS has limitations for neonatal data.
• Chronic lung disease (CLD) is an independent risk factor for abnormal white matter development in preterm infants.

Purpose of the Study:

• To describe an optimized TBSS protocol for neonatal DTI data, reducing registration errors.
• To investigate the effect of CLD on white matter anisotropy and diffusivity in preterm infants using the optimized protocol.

Main Methods:

• Developed an optimized TBSS protocol for neonatal DTI, including low degrees-of-freedom linear registration and population-average FA map registration.
• Acquired DTI data from 93 preterm infants (median gestational age 28 weeks).
• Analyzed DTI data from 19 infants with CLD (requiring oxygen at 36 weeks) and compared them to peers.

Main Results:

• The optimized TBSS protocol reduced global misalignment in neonatal fractional anisotropy (FA) maps.
• Infants with CLD showed significantly increased radial diffusivity (RD) and reduced FA in key white matter tracts (centrum semiovale, corpus callosum, inferior longitudinal fasciculus) (p<0.05).
• Findings were controlled for prematurity and scan age, indicating CLD's independent effect.

Conclusions:

• The optimized TBSS protocol enhances the reliability of neonatal DTI analysis.
• Potentially modifiable respiratory morbidity, such as CLD, is associated with widespread alterations in white matter microstructure in preterm infants at term-equivalent age.
• This suggests that interventions targeting respiratory health may positively influence white matter development in this vulnerable population.