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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

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Published on: November 8, 2012

Comparative analysis of brain age prediction using structural and diffusion MRIs in neonates.

Zhicong Fang¹, Ningning Pan¹, Shujuan Liu¹

¹School of Information Science and Engineering, Shandong Normal University, Shandong, China.

|August 27, 2024

Summary

Predicting infant brain age using T2-weighted (T2w) and fractional anisotropy (FA) MRI shows similar accuracy. However, FA images reveal significant differences in age prediction bias related to gender and brain asymmetry, unlike T2w images.

Keywords:

Brain age prediction Fractional anisotropy image Neonates Neural network interpretability T2-weighted image

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Area of Science:

Neuroscience
Medical Imaging
Machine Learning

Background:

Brain age prediction using machine learning is a key biomarker for assessing neurodevelopment.
Structural magnetic resonance imaging (sMRI) and diffusion magnetic resonance imaging (dMRI) are primary modalities, but their distinct contributions to infant age prediction are understudied.

Purpose of the Study:

To investigate the differential impact of sMRI (T2w) and dMRI (FA) on predicting infant brain age.
To explore how factors like prematurity, gender, and hemispherical asymmetry influence age prediction across these modalities.

Main Methods:

Machine learning models were used to predict infant age from T2-weighted (T2w) and fractional anisotropy (FA) MRI data.
Mean absolute errors (MAE) were compared between T2w and FA predictions.
Exploratory analyses identified key brain regions contributing to age prediction for each modality.
Statistical tests examined the influence of prematurity, gender, and hemispherical asymmetry on prediction biases.

Main Results:

Both T2w and FA images yielded similar mean absolute errors in infant age prediction.
T2w images emphasized the cerebral cortex and ventricles, while FA images highlighted the cerebral cortex and white matter tracts.
FA images showed significant age prediction biases related to gender and hemispherical asymmetry (p<0.05), unlike T2w images.

Conclusions:

T2w and FA MRI offer complementary information for infant brain age prediction, reflecting macrostructural and microstructural development, respectively.
FA-based age prediction is more sensitive to variations in gender and brain asymmetry, suggesting distinct developmental trajectories.
These findings provide novel insights into infant neurodevelopmental assessment and tracking.