title: Using clinically acquired MRI to construct age-specific ADC atlases: Quantifying spatiotemporal ADC changes from birth to 6-year old.
abstract: Diffusion imaging is critical for detecting acute brain injury. However, normal apparent diffusion coefficient (ADC) maps change rapidly in early childhood, making abnormality detection difficult. In this article, we explored clinical PACS and electronic healthcare records (EHR) to create age-specific ADC atlases for clinical radiology reference. Using the EHR and three rounds of multiexpert reviews, we found ADC maps from 201 children 0-6 years of age scanned between 2006 and 2013 who had brain MRIs with no reported abnormalities and normal clinical evaluations 2+ years later. These images were grouped in 10 age bins, densely sampling the first 1 year of life (5 bins, including neonates and 4 quarters) and representing the 1-6 year age range (an age bin per year). Unbiased group-wise registration was used to construct ADC atlases for 10 age bins. We used the atlases to quantify (a) cross-sectional normative ADC variations; (b) spatiotemporal heterogeneous ADC changes; and (c) spatiotemporal heterogeneous volumetric changes. The quantified age-specific whole-brain and region-wise ADC values were compared to those from age-matched individual subjects in our study and in multiple existing independent studies. The significance of this study is that we have shown that clinically acquired images can be used to construct normative age-specific atlases. These first of their kind age-specific normative ADC atlases quantitatively characterize changes of myelination-related water diffusion in the first 6 years of life. The quantified voxel-wise spatiotemporal ADC variations provide standard references to assist radiologists toward more objective interpretation of abnormalities in clinical images. Our atlases are available at https://www.nitrc.org/projects/mgh_adcatlases. Hum Brain Mapp 38:3052-3068, 2017. © 2017 Wiley Periodicals, Inc.
authors.affiliation: Psychiatric Neuroimaging, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts.|Laboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts.|Quantitative Tumor Imaging at Martinos, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts.|Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts.
authors.forename: Yangming
authors.identifier: 0000-0002-7726-6208
authors.initials: Y
authors.lastname: Ou
authors.affiliation: Laboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts.
authors.forename: Lilla
authors.initials: L
authors.lastname: Zöllei
authors.affiliation: Psychiatric Neuroimaging, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts.|Laboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts.
authors.forename: Kallirroi
authors.initials: K
authors.lastname: Retzepi
authors.affiliation: Research Computing, Partners Healthcare, 1 Constitution Center, Charlestown, Massachusetts.|Laboratory of Computer Science, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
authors.forename: Victor
authors.initials: V
authors.lastname: Castro
authors.affiliation: Division of Newborn Medicine, Department of Pediatrics, Massachusetts General Hospital for Children, Harvard Medical School, Boston, Massachusetts.
authors.forename: Sara V
authors.initials: SV
authors.lastname: Bates
authors.affiliation: somics Inc, Cambridge, Massachusetts.
authors.forename: Steve
authors.initials: S
authors.lastname: Pieper
authors.affiliation: Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
authors.forename: Katherine P
authors.initials: KP
authors.lastname: Andriole
authors.affiliation: Research Computing, Partners Healthcare, 1 Constitution Center, Charlestown, Massachusetts.|Laboratory of Computer Science, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
authors.forename: Shawn N
authors.initials: SN
authors.lastname: Murphy
authors.affiliation: Psychiatric Neuroimaging, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts.|Laboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts.
authors.forename: Randy L
authors.initials: RL
authors.lastname: Gollub
authors.affiliation: Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts.
authors.forename: Patricia Ellen
authors.initials: PE
authors.lastname: Grant
mesh_terms: D000328:Adult; D001921:Brain / Q000000981:diagnostic imaging* / Q000254:growth & development*; D001930:Brain Injuries / Q000000981:diagnostic imaging / Q000473:pathology*; D001931:Brain Mapping; D002648:Child; D002675:Child, Preschool; D015331:Cohort Studies; D003430:Cross-Sectional Studies; D038524:Diffusion Magnetic Resonance Imaging; D057286:Electronic Health Records / Q000706:statistics & numerical data; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007223:Infant; D007231:Infant, Newborn; D055815:Young Adult
keywords: atlas construction; big data informatics; clinical images; diffusion MRI; neurodevelopment