Sarah R Morris1,2,3, Richard Davis Holmes3, Adam V Dvorak1,2, Hanwen Liu1,2, Youngjin Yoo4, Irene M Vavasour3, Silvia Mazabel5, Burkhard Mädler6, Shannon H Kolind1,2,3,7, David K B Li3,7, Linda Siegel5, Christian Beaulieu8, Alex L MacKay1,3, Cornelia Laule1,2,3,9. 1. Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada. 2. International Collaboration on Repair Discoveries, Vancouver, BC, Canada. 3. Department of Radiology, University of British Columbia, Vancouver, BC, Canada. 4. Medical Imaging Technologies, Siemens Healthineers, Princeton, NJ. 5. Educational and Counseling Psychology, and Special Education, University of British Columbia, Vancouver, BC, Canada. 6. Phillips Healthcare, Hamburg, Germany. 7. Department of Medicine, University of British Columbia, Vancouver, BC, Canada. 8. Department of Biomedical Engineering, University of Alberta, Edmonton, AB, Canada. 9. Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada.
Abstract
BACKGROUND AND PURPOSE: Myelin water imaging (MWI) and diffusion tensor imaging (DTI) provide information about myelin and axon-related brain microstructure, which can be useful for investigating normal brain development and many childhood brain disorders. While pediatric DTI atlases exist, there are no pediatric MWI atlases available for the 9-10 years old age group. As myelination and structural development occurs throughout childhood and adolescence, studies of pediatric brain pathologies must use age-specific MWI and DTI healthy control data. We created atlases of myelin water fraction (MWF) and DTI metrics for healthy children aged 9-10 years for use as normative data in pediatric neuroimaging studies. METHODS: 3D-T1 , DTI, and MWI scans were acquired from 20 healthy children (mean age: 9.6 years, range: 9.2-10.3 years, 4 females). ANTs and FSL registration were used to create quantitative MWF and DTI atlases. Region of interest (ROI) analysis in nine white matter regions was used to compare pediatric MWF with adult MWF values from a recent study and to investigate the correlation between pediatric MWF and DTI metrics. RESULTS: Adults had significantly higher MWF than the pediatric cohort in seven of the nine white matter ROIs, but not in the genu of the corpus callosum or the cingulum. In the pediatric data, MWF correlated significantly with mean diffusivity, but not with axial diffusivity, radial diffusivity, or fractional anisotropy. CONCLUSIONS: Normative MWF and DTI metrics from a group of 9-10 year old healthy children provide a resource for comparison to pathologies. The age-specific atlases are ready for use in pediatric neuroimaging research and can be accessed: https://sourceforge.net/projects/pediatric-mri-myelin-diffusion/.
BACKGROUND AND PURPOSE: Myelin water imaging (MWI) and diffusion tensor imaging (DTI) provide information about myelin and axon-related brain microstructure, which can be useful for investigating normal brain development and many childhood brain disorders. While pediatric DTI atlases exist, there are no pediatric MWI atlases available for the 9-10 years old age group. As myelination and structural development occurs throughout childhood and adolescence, studies of pediatric brain pathologies must use age-specific MWI and DTI healthy control data. We created atlases of myelin water fraction (MWF) and DTI metrics for healthy children aged 9-10 years for use as normative data in pediatric neuroimaging studies. METHODS: 3D-T1 , DTI, and MWI scans were acquired from 20 healthy children (mean age: 9.6 years, range: 9.2-10.3 years, 4 females). ANTs and FSL registration were used to create quantitative MWF and DTI atlases. Region of interest (ROI) analysis in nine white matter regions was used to compare pediatric MWF with adult MWF values from a recent study and to investigate the correlation between pediatric MWF and DTI metrics. RESULTS: Adults had significantly higher MWF than the pediatric cohort in seven of the nine white matter ROIs, but not in the genu of the corpus callosum or the cingulum. In the pediatric data, MWF correlated significantly with mean diffusivity, but not with axial diffusivity, radial diffusivity, or fractional anisotropy. CONCLUSIONS: Normative MWF and DTI metrics from a group of 9-10 year old healthy children provide a resource for comparison to pathologies. The age-specific atlases are ready for use in pediatric neuroimaging research and can be accessed: https://sourceforge.net/projects/pediatric-mri-myelin-diffusion/.
Authors: Gerhard S Drenthen; Eric L A Fonseca Wald; Walter H Backes; Albert P Aldenkamp; R Jeroen Vermeulen; Mariette H J A Debeij-van Hall; Sylvia Klinkenberg; Jacobus F A Jansen Journal: J Neuroimaging Date: 2020-04-07 Impact factor: 2.486
Authors: Adam V Dvorak; Taylor Swift-LaPointe; Irene M Vavasour; Lisa Eunyoung Lee; Shawna Abel; Bretta Russell-Schulz; Carina Graf; Anika Wurl; Hanwen Liu; Cornelia Laule; David K B Li; Anthony Traboulsee; Roger Tam; Lara A Boyd; Alex L MacKay; Shannon H Kolind Journal: Sci Rep Date: 2021-01-11 Impact factor: 4.379
Authors: Kaitlyn Easson; Guillaume Gilbert; Charles V Rohlicek; Christine Saint-Martin; Maxime Descoteaux; Sean C L Deoni; Marie Brossard-Racine Journal: Hum Brain Mapp Date: 2022-04-12 Impact factor: 5.399