Multi-parametric evaluation of the white matter maturation

Area of Science:

• Neuroscience
• Medical Imaging

Background:

• Evaluating in vivo brain white matter maturation in infants is challenging due to the lack of established gold standards.
• Existing univariate approaches may not fully capture the complex maturational processes.

Purpose of the Study:

• To propose and validate an original multi-parametric MRI approach for assessing early white matter bundle maturation in infants.
• To investigate maturational asynchrony across different white matter tracts.

Main Methods:

• Utilized a multi-parametric approach comparing infant and adult groups using Mahalanobis distance.
• Computed Mahalanobis distance from quantitative T1 and T2 relaxation times and diffusion tensor imaging parameters (longitudinal and transverse diffusivities).
• Analyzed 18 white matter bundles in 17 healthy infants aged 3-21 weeks.

Main Results:

• Confirmed significant maturational asynchrony across white matter bundles, identifying tracts with advanced (e.g., spinothalamic tract, optic radiations) and delayed maturation (e.g., superior longitudinal fasciculus).
• The multi-parametric approach demonstrated higher reliability than univariate methods, revealing more maturational relationships and respecting a priori assumptions.
• Mahalanobis distances showed an exponential decrease with age, indicating rapid maturation in the first year, with variations attributed to different maturation onsets.

Conclusions:

• The proposed multi-parametric MRI method effectively evaluates early white matter maturation and its asynchronous development across different brain tracts.
• This approach provides a more comprehensive understanding of brain development compared to traditional univariate methods.
• Maturation differences across bundles and the rapid changes within the first postnatal year are highlighted.