A framework for multi-component analysis of diffusion MRI data over the neonatal period.

Area of Science:

• Neuroimaging
• Developmental Neuroscience
• Computational Biology

Background:

• Developing a comprehensive understanding of early brain development is crucial.
• Advanced diffusion imaging techniques are needed to capture microstructural changes.
• Existing methods for creating brain templates have limitations in capturing developmental trajectories.

Purpose of the Study:

• To present a novel framework for generating time-resolved group average templates of the developing brain.
• To utilize multi-shell high angular resolution diffusion imaging (MS-HARDI) data for enhanced brain analysis.
• To support applications such as group voxel/fixel-wise analysis, atlas-building, and studying white matter maturation.

Main Methods:

• Employed multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD) to decompose diffusion signals.
• Estimated response functions from cerebrospinal fluid and white matter in infant groups.
• Developed an orientationally-resolved template from 113 infants (33-44 weeks postmenstrual age) from the Developing Human Connectome Project.
• Extended a non-linear diffeomorphic registration framework to align orientation density functions (ODFs) using multi-tissue contrasts for superior alignment.

Main Results:

• Successfully built weekly group average templates of brain tissue components.
• Demonstrated superior alignment using the extended registration framework.
• Facilitated investigations into the age-related evolution of brain microstructure components.
• Generated a multi-tissue atlas providing insights into brain development.

Conclusions:

• The developed framework enables the creation of accurate, time-resolved brain templates for infants.
• This atlas serves as a foundation for future longitudinal studies on healthy and pathological brain maturation.
• The methodology offers enhanced insights into the evolving microstructure of the developing human brain.