Precise Individualized Infant brain atlas
Presented During:
Friday, June 27, 2025: 11:30 AM - 12:45 PM
Brisbane Convention & Exhibition Centre
Room:
M3 (Mezzanine Level)
Poster No:
1807
Submission Type:
Abstract Submission
Authors:
meizhen han1, Tengda Zhao2, Yong He2
Institutions:
1Beijing Normal University, Beijing, AK, 2Beijing Normal University, Beijing, Beijing
First Author:
Co-Author(s):
Introduction:
The infancy stage (0-2 years old) is a critical period for brain development. The precise pediatric brain atlas could serve as fundamental tools for understanding the intricate developmental regulation of the pediatric brain during first several years in life. However, majority of pediatric atlases have been derived by warping adult atlases or manually delineated single subject's atlas into pediatric brain spaces, which does not account for the distinct characteristics of infant brain data. While recent years have seen the emergence of atlases constructed from pediatric brain imaging databases, these efforts often fall short in fine age resolution, spatial continuity across different age points and individualized brain mapping technique. Therefore, in this study, we aim to propose a novel individualized infant brain atlas mapping technique and constructed precise infant brain atlas in individual-level and age-specific population-level infant atlases.
Methods:
In this study, 464 diffusion MRI scans from 241 infants (83 of whom had longitudinal data) were obtained from the BCP database (figure 1a). Densely sampled time points of the developmental infant atlas are 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 18, 21, 24-month. We adopted a sliding window strategy (figure 1b), and window size=3 for 0-12 months, and window size=5 for 15-24 months.
The individualized infant atlas construction technique (figure 1c) consists of these steps: initial seed masks definition, probabilistic diffusion tractography, construct connectivity matrix and similarity matrix, connectivity-based parcellation through spectral clustering, determination of the optimal clustering solution, construct probability atlas with 464 infant data, individual-group interactive iterative algorithm, and the iteration stops when meet the convergence criteria.
Within-region homogeneity, reproducibility, inter-baby variability and development trajectory of the infant atlas was estimated.
The individualized infant atlas construction technique (figure 1c) consists of these steps: initial seed masks definition, probabilistic diffusion tractography, construct connectivity matrix and similarity matrix, connectivity-based parcellation through spectral clustering, determination of the optimal clustering solution, construct probability atlas with 464 infant data, individual-group interactive iterative algorithm, and the iteration stops when meet the convergence criteria.
Within-region homogeneity, reproducibility, inter-baby variability and development trajectory of the infant atlas was estimated.
Results:
The infant brain atlas was found to consist of 154 subregions, with 77 subregions in each brain hemisphere, comprising 61 cortical and 16 subcortical regions. The atlas, derived from longitudinal data, exhibited good spatio-temporal continuity throughout the development (figure 1d). Individualized infant atlas yielded brain regions with higher within-region homogeneity in connectivity (figure 2a), with statistically significant difference demonstrated by ANOVA across all monthly age groups. Sensitivity analysis showed that the reproducibility (i.e. spatial similarity, measured Dice coefficient) of individual atlas reached over 88% with only 10 samples available, while the reproducibility of group atlas is less than 80%, indicating the individualized atlas technique requires fewer brain samples as prior information and shows higher reproducibility. Inter-baby variability (figure 2c) was particularly high in the lateral prefrontal lobe and the temporal–parietal junction, while being minimal in the insula, motor, visual, and medial cortical areas. The development trajectory of subregion size and size ratio (figure 2d) demonstrated a heterogeneous non-linear development pattern across the entire brain. Subregions exhibited different rapid-developmental time windows, potentially related with the development of multiple cognitive functions in infants.
Conclusions:
This study proposed a novel individualized infant brain atlas mapping technique in the form of iterative individual-group interaction, and highlighted the superiority of individualized atlases over group-level ones in connectivity homogeneity and spatial reproducibility. Furthermore, we revealed the inter-baby variability in brain topography and the distinct developmental heterogeneous maturation trajectories of each precise subregions in individualized infant atlas.
·Figure 1. The novel individualized infant brain atlas mapping technique.
·Figure 2. The validation analysis and development trajectoryies of the individualized infant atlas.
Lifespan Development:
Normal Brain Development: Fetus to Adolescence 2
Modeling and Analysis Methods:
Methods Development
Segmentation and Parcellation
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Anatomy and Brain Mapping
Neuroinformatics and Data Sharing:
Brain Atlases 1
Keywords:
Atlasing
Development
MRI
PEDIATRIC
Tractography
1|2Indicates the priority used for review
Abstract Information
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Provide references using APA citation style.
Han, M. (2020). Individualized Cortical Parcellation Based on Diffusion MRI Tractography. Cerebral Cortex, 30, 3198–3208.
Howell, B. R. (2019). The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development. NeuroImage, 185, 891–905.
Fan, L. (2016). The human brainnetome atlas: A new brain atlas based on connectional architecture. Cerebral Cortex, 26, 3508–3526.