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Developmental score of the infant brain: characterizing diffusion MRI in term- and preterm-born infants

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Abstract

Large-scale longitudinal neuroimaging studies of the infant brain allow us to map the spatiotemporal development of the brain in its early phase. While the postmenstrual age (PMA) is commonly used as a time index to analyze longitudinal MRI data, the nonlinear relationship between PMA and MRI data imposes challenges for downstream analyses. We propose a mathematical model that provides a Developmental Score (DevS) as a data-driven time index to characterize the brain development based on MRI features. 319 diffusion tensor imaging (DTI) datasets were collected from 87 term-born and 66 preterm-born infants at multiple visits, which were automatically segmented based on the JHU neonatal atlas. The mean diffusivity (MD) and fractional anisotropy (FA) in 126 brain parcels were used in the model to derive DevS. We demonstrate that transforming the time index from PMA to DevS improves the linearity of the longitudinal changes in MD and FA in both gray and white matter structures. More importantly, regional developmental differences in DTI metrics between preterm- and term-born infants were identified more clearly using DevS, e.g. 79 structures showed significantly different regression patterns in MD between preterm- and term-born infants, compared to only 27 structures that showed group differences using PMA as the index. Therefore, the DevS model facilitates linear analyses of DTI metrics in the infant brain, and provides a useful tool to characterize altered brain development due to preterm-birth.

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Acknowledgement

We would like to thank Dr. Murat Bilgel at the National Institute for Aging for the important discussions of the mathematical model and the optimization procedures, Dr. Steven Buchthal for the MRI data acquisition and image quality control, and Dr. Doris Lin, a board-certified Neuroradiologist, for MRI reading. This grant is made possible by the following funding supports: Ministry of Science and Technology of the People’s Republic of China (2018YFE0114600, DW), National Natural Science Foundation of China (61801424 and 81971606, DW) and National Institutes of Health (R01HD065955, KO; U54NS056889 and 2K24DA16170, LC). None of the authors has a conflict of interest to declare.

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Authors and Affiliations

  1. Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China

    Dan Wu

  2. Departments of Diagnostic Radiology and Nuclear Medicine, and Neurology, University of Maryland School of Medicine, Baltimore, MD, USA

    Linda Chang

  3. Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Linda Chang

  4. Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA

    Thomas M. Ernst

  5. Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA

    Brian S. Caffo

  6. Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Traylor 217, 720 Rutland Ave, Baltimore, MD, 21215, USA

    Kenichi Oishi

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Wu, D., Chang, L., Ernst, T.M. et al. Developmental score of the infant brain: characterizing diffusion MRI in term- and preterm-born infants. Brain Struct Funct 225, 2431–2445 (2020). https://doi.org/10.1007/s00429-020-02132-4

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