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Using Clinically Acquired MRI to Construct Age-specific Atlases: Quantifying Spatiotemporal ADC Changes from Birth to 6-year Old

Institution:
1Psychiatric Neuroimaging, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
2Laboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
Publisher:
Wiley
Publication Date:
Jun-2017
Journal:
Hum Brain Mapp
Volume Number:
38
Issue Number:
6
Pages:
3052-68
Citation:
Hum Brain Mapp. 2017 Jun;38(6):3052-68.
PubMed ID:
28371107
PMCID:
PMC5426959
Keywords:
atlas construction, big data informatics, clinical images, diffusion MRI, neurodevelopment
Appears in Collections:
NAC, SPL
Sponsors:
S10 RR019307/RR/NCRR NIH HHS/United States
S10 RR023043/RR/NCRR NIH HHS/United States
P41 EB015902/EB/NIBIB NIH HHS/United States
S10 RR023401/RR/NCRR NIH HHS/United States
R01 EB014947/EB/NIBIB NIH HHS/United States
Generated Citation:
Ou Y., Zöllei L., Retzepi K., Castro V., Bates S.V., Pieper S., Andriole K.P., Murphy S.N., Gollub R.L., Grant P.E. Using Clinically Acquired MRI to Construct Age-specific Atlases: Quantifying Spatiotemporal ADC Changes from Birth to 6-year Old. Hum Brain Mapp. 2017 Jun;38(6):3052-68. PMID: 28371107. PMCID: PMC5426959.
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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.