Baseline Structural Connectomics Data of Healthy Brain Development Assessed with Multi-Modal Magnetic Resonance Imaging

Author:

Mattie David12ORCID,Fang Zihang3,Takahashi Emi3456,Peña Castillo Lourdes2ORCID,Levman Jacob167ORCID

Affiliation:

1. Department of Computer Science, St. Francis Xavier University, Antigonish, NS B2G 2W5, Canada

2. Department of Computer Science, Memorial University of Newfoundland, St. John’s, NL A1C 5S7, Canada

3. Division of Newborn Medicine, Department of Medicine, Boston Children’s Hospital, Boston, MA 02115, USA

4. Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA

5. Department of Radiology, Harvard Medical School, Boston, MA 02115, USA

6. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA

7. Research Affiliate, Nova Scotia Health Authority—Research, Innovation and Discovery Center for Clinical Research, Halifax, NS B3J 0EB, Canada

Abstract

Diffusion magnetic resonance imaging (MRI) tractography is a powerful tool for non-invasively studying brain architecture and structural integrity by inferring fiber tracts based on water diffusion profiles. This study provided a thorough set of baseline data of structural connectomics biomarkers for 809 healthy participants between the ages of 1 and 35 years. The data provided can help to identify potential biomarkers that may be helpful in characterizing physiological and anatomical neurodevelopmental changes linked with healthy brain maturation and can be used as a baseline for comparing abnormal and pathological development in future studies. Our results demonstrate statistically significant differences between the sexes, representing a potentially important baseline from which to establish healthy growth trajectories. Biomarkers that correlated with age, potentially representing useful methods for assessing brain development, are also presented. This baseline information may facilitate studies that identify abnormal brain development associated with a variety of pathological conditions as departures from healthy sex-specific age-dependent neural development. Our findings are the result of combining the use of mainstream analytic methods with in-house-developed open-source software to help facilitate reproducible analyses, inclusive of many potential biomarkers that cannot be derived from existing software packages. Assessing relationships between our identified regional tract measurements produced by our technology and participant characteristics/phenotypic data in future analyses has tremendous potential for the study of human neurodevelopment.

Funder

National Institutes of Health

Canada Foundation for Innovation

Nova Scotia Research and Innovation Trust

St. Francis Xavier University research startup

Compute Canada Resource Allocation

Publisher

MDPI AG

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