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A Network-Based Analysis of the Preterm Adolescent Brain Using PCA and Graph Theory

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Computational Diffusion MRI

Abstract

The global increase in the rate of premature birth is of great concern since it is associated with an increase in a wide spectrum of neurologic and cognitive disorders. Neuroimaging analyses have been focused on white matter alterations in preterm subjects and findings have linked neurodevelopment impairment to white matter damage linked to premature birth. However, the trajectory of brain development into childhood and adolescence is less well described. Neuroimaging studies of extremely preterm born subjects in their adulthood are now available to investigate the long-term structural alterations of disrupted neurodevelopment. In this paper, we examine white matter pathways in the preterm adolescent brain by combining state-of-the-art diffusion techniques with graph theory and principal component analysis (PCA). Our results suggest that the pattern of connectivity is altered and differences in connectivity patterns result in more vulnerable premature brain network.

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Acknowledgments

We acknowledge the EPSRC-funded UCL Centre for Doctoral Training in Medical Imaging (EP/L016478/1), the National Institute for Health Research (NIHR) and the MRC (MR/J01107X/1).

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Correspondence to Hassna Irzan .

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Irzan, H. et al. (2020). A Network-Based Analysis of the Preterm Adolescent Brain Using PCA and Graph Theory. In: Bonet-Carne, E., Hutter, J., Palombo, M., Pizzolato, M., Sepehrband, F., Zhang, F. (eds) Computational Diffusion MRI. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-030-52893-5_15

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