Abstract
Neonatal white matter undergoes rapid, spatially heterogeneous maturation, yet current connectome pipelines model it with a single anisotropic response function and summarise each connection as a single scalar weight. Although neonatal connectomes already carry streamline count or microstructural edge weights, to our knowledge no pipeline propagates a younger ($Y$) versus older ($O$) white-matter decomposition to individual connectome edges. We separate the neonatal diffusion signal into younger and older anisotropic components using multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD) with published neonatal response functions, and carry this decomposition through tractography so that each edge receives a maturation-sensitive index $M$ alongside its connection strength. We evaluate the framework on 205 neonates from the Developing Human Connectome Project (dHCP) against two comparison pipelines that discard the two-component distinction at different stages. The resulting per-edge index $M$ captures regionally specific developmental patterns consistent with the established posterior-to-anterior order of white-matter maturation: it declines from posterior to anterior cortex (Spearman $\rho=-0.40$) and carries spatial information unavailable from connection strength or fractional anisotropy (FA) alone.
Links to Paper and Supplementary Materials
Main Paper (Open Access Version): https://papers.miccai.org/miccai-2026-sat/paper/PIPPI_010.pdf
SharedIt Link: Not yet available
SpringerLink (DOI): Not yet available
Supplementary Material: Not Submitted
Link to Open Review
BibTex
@InProceedings{RusJal_Mapping_MICCAISAT2026,
author = { Rustamov, Jaloliddin AND Leysen, Siebe AND Radwan, Ahmed AND Christiaens, Daan AND Damseh, Rafat},
title = { { Mapping Structural Connectivity in the Neonatal Developing Brain using Multi-Component Tissue Modelling } },
booktitle = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2026 Workshops and Challenges},
year = {2026},
publisher = {Springer Nature Switzerland},
volume = {LNCS 17257},
month = {pending},
page = {pending}
}