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Differential myelination maturation across cortical regions and white matter tracts during infancy
Ruolin Li1,2, Wentao Wu1,2, Sovesh Mohapatra1,2, Kay L. Sindabizera1, Ziqin Zhang1,2, Cheng En Lee1, Minhui Ouyang1,3, and Hao Huang1,3
1Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States, 2Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States, 3Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States

Synopsis

Keywords: Normal Development, Screening, Myelination, Infant Brain, Early Development, Structural MRI

Motivation: While myelination is known to progress rapidly in the infant brain, the specific myelination progression in finer cortical regions and white matter (WM) tracts remain elusive. The precise effects of environmental impacts on infant brain myelination maturation require further investigation.

Goal(s): Our goal was to delineate differential myelination maturation trajectories across cortical and WM regions during infancy and explore their associations with environmental factors.

Approach: T1-weighted and T2-weighted images were used to map myelin content and analyzed with generalized additive models.

Results: Differential myelination processes were found across cortical and white matter regions, with significant correlations to socioeconomic status and parental stress.

Impact: This research advances understanding of complicated yet organized patterns in the early developing brain, informing pediatric care strategies. It enables targeted interventions for at-risk groups based on environmental impacts, potentially improving long-term cognitive outcomes. Further studies could investigate intervention efficacy.

Introduction

Myelin is essential for efficient neural communication1，2 and its maturation3 is crucial during the first two years of life, a period of the most dynamic brain development4-6. Although it's known that myelination occurs in stages, with primary regions developing before associative regions7,8, the specific infant brain myelination progression in finer cortical regions and white matter (WM) tracts is unclear. Additionally, while factors like parental stress (PSS) and socioeconomic status (SES) are believed to impact brain structure development in childhood9,10, their specific relationships with myelination in infants remain unexplored. Here, we measured the longitudinal trajectories of the myelination across cortex regions and WM tracts from 1-24 months using structural MRI images and further examined its correlation with environmental influences through behavioral analysis.

Methods

Data acquisition: In this study, 293 infants aged 1-24 months were recruited. Among them, 93 infants underwent complete T1-weighted and T2-weighted scans with a 3.0T Siemens Prisma MRI scanner. We acquired T1-weighted images with MPRAGE (TR/TE = 2400/2.24 ms, 0.8 mm isotropic) and T2-weighted images with SPACE (TR/TE = 3200/564 ms, 0.8 mm isotropic), both with a field of view (FOV) of 166.4 × 240 × 2563 and an acquisition matrix of 208 x 300 x 320.
Data processing: All infants' T1-weighted and T2-weighted MRI scans are processed through a pipeline involving brain extraction, linear alignment of T1 to T2 images with FSL's FLIRT11, and registration to a 10-month template with antsRegistrationSyN using cross-correlation as optimization metric12. Following preprocessing and visual inspection, two images were discarded for poor quality. We produced T1/T2 myelin maps by dividing the aligned T1 by T2 images, which mathematically cancels the signal intensity bias13.
Measurements of myelin maturation and their associations with SES and PSS: The 1-year-old Penn-CHOP atlas was utilized to identify 45 regions of interest (ROIs) in the infant's brain, covering 4 lobes (19 cortical regions) and 5 WM tract groups (26 WM tracts)14,15. Hemispheric averages were calculated for each ROI, and data extraction was carried out using MATLAB. We used R's generalized additive models (GAMs)16 to model myelination maturation across all regions, with each model formulated as T1w/T2w ratio ~ s (Age, k = 3). Parents of 51 infants provided SES, which is calculated using education and occupation, and PSS data, which reflects stress levels over the past month via questionnaires. GAMs was applied to analyze the impact of SES and PSS on myelination, with the model: T1w/T2w ratio ~ s (Age, k = 3) + SES + PSS.

Results

Fig. 1 illustrates the structural images of the developing brain at milestone ages during human infancy. The increase in myelin content across the developmental period is readily appreciated in the T1w/T2w ratio maps. Heterogeneous myelin distribution across the cortex and white matter regions can also be demonstrated. Fig. 2 details the significant and differential cortical myelination changes in all cortical regions for 1-24 months. Notably, the maturation obeys a particular pattern, with the frontal lobe exhibiting the highest ratio followed by the parietal, temporal, and occipital lobes, respectively. Within the occipital lobe, ROIs show a consistent rise in T1w/T2w ratios, suggesting a uniform pattern of myelination across the visual processing regions. Trajectories of the precentral and postcentral gyri serve as valuable benchmarks to better recognize different maturation levels. Fig. 3 delineates the progression of WM myelination, indicating significant age-related increases in major WM tract groups over months. The maturation of WM follows the sequence of limbic, commissural, brainstem, projection, and association tract groups. Moreover, WM tract groups exhibit accelerated maturation rates within the initial ten-month period, with the commissural tracts maturing most rapidly within the first five months. Furthermore, we explored the associations between myelination maturation and environmental factors. For cortex structures, the average of the frontal lobe and SMG correlate positively with SES (Fig. 4A), while PHG and SMG correlate negatively with PSS (Fig. 4B). For WM structures, the average of whole WM, cc, and the average of commissural tract group exhibit significant positive relationships with SES. Concomitantly, cc is also positively associated with the increasing PSS, as shown in Fig. 5A and B.

Conclusion

We presented comprehensive and differential trajectories of myelination maturation in 1-24 months infants. Distinctive patterns were shown across cortical and WM regions. Frontal lobe myelination is the highest, followed by parietal, temporal, and occipital lobes. WM matures in a limbic-to-association-tract gradient, with a notable acceleration in the first 10 months. Additionally, the examined relationships between myelination and socioeconomic and stress status provide invaluable insight into the significant impact of environmental effects on infants’ brain development.

Acknowledgements

This study is funded by NIH R01MH092535, R01MH125333, R01EB031284, R01MH129981, R21MH123930 and P50HD105354.

References

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Figures

Figure 1. Structural images of the developing brain. From top to bottom, T1 weighted, T2 weighted, and T1w/T2w ratio images of representative subjects at milestone ages during human infancy. Shown are infants of 3 months (m), 6 m, 9 m, 13 m, 16 m, and 23 m. In the T1w/T2w ratio images, higher values (indicated by warm colors), respond to more mature myelination of brain areas.

Figure 2. Differential trajectories of myelination across cortex measured with T1w/T2w ratio. From left to right: cortex, frontal lobe, parietal lobe, temporal lobe, and occipital lobe. Solid lines illustrate the average myelination trend for each lobe, and every region within the lobe is indicated by gradient monochromatic dashed lines. PrCG and PoCG are presented as gray reference benchmarks. Scattered triangular points across the graphs depict individual measurements.

Figure 3. Differential trajectories of myelination across all major white matter tracts and tract groups measured with T1w/T2w ratio. The groups include limbic, commissural, brainstem, projection, and association tracts. Solid lines illustrate the average myelination trend of each tract group and every tract in the group was indicated by gradient monochromatic dashed lines. Scattered triangular points across the graphs depict individual measurements.

Figure 4. Association of SES and PSS with cortex structures. Higher SES scores indicate lower social status and higher PSS scores indicate more stress. (A) The trajectories for the average of FL and SMG exhibit a significant positive correlation with SES. (B) The trajectories for SMG and PHG show a significantly negative link with PSS. The surrounding light-colored shading shows a 95% confidence interval. (C) The table provides estimate coefficients (β) and p-values for each cortex lobe as well as significant cortex regions.

Figure 5. Association of SES and PSS with white matter structures. (A) The trajectories for the average of whole brain white matter, cc, and the average of commissural tracts group exhibit a significant positive correlation with SES. (B) The trajectory of cc shows a significantly positive link with PSS. The surrounding light-colored shading shows a 95% confidence interval. (C) The table provides estimate coefficients (β) and p-values for each white matter group as well as significant tracts.

Proc. Intl. Soc. Mag. Reson. Med. 32 (2024)
0831
DOI: https://doi.org/10.58530/2024/0831