TY - JOUR
T1 - A Bayesian approach to the creation of a study-customized neonatal brain atlas
AU - Zhang, Yajing
AU - Chang, Linda
AU - Ceritoglu, Can
AU - Skranes, Jon
AU - Ernst, Thomas
AU - Mori, Susumu
AU - Miller, Michael I.
AU - Oishi, Kenichi
N1 - Funding Information:
This publication was made possible by grants R21AG033774 , R01HD065955 , 2K24DA16170 , U54NS056883 , G12MD007601-26 , and P41EB015909 from the National Institutes of Health , the Yousem Family Research Grant 2013 from the Yousem Family Research Fund , and grant 46039500 from the Central Norway Regional Health Authority . The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official view of NIH, the Yousem Family Research Fund, or the Central Norway Regional Health Authority. The terms of this arrangement are being managed by Johns Hopkins University in accordance with its conflict of interest policies. The authors are grateful to the families of our research participants, and our research staff (Heather Johansen, Antonette Hernandez, and Robyn Yamakawa, Caroline Jiang, Dr. Daniel Alicata, and Dr. Steven Buchthal) who assisted with the data collection and data transfer. We also thank Ms. Mary McAllister for help with manuscript editing.
PY - 2014/11/1
Y1 - 2014/11/1
N2 - Atlas-based image analysis (ABA), in which an anatomical "parcellation map" is used for parcel-by-parcel image quantification, is widely used to analyze anatomical and functional changes related to brain development, aging, and various diseases. The parcellation maps are often created based on common MRI templates, which allow users to transform the template to target images, or vice versa, to perform parcel-by-parcel statistics, and report the scientific findings based on common anatomical parcels. The use of a study-specific template, which represents the anatomical features of the study population better than common templates, is preferable for accurate anatomical labeling; however, the creation of a parcellation map for a study-specific template is extremely labor intensive, and the definitions of anatomical boundaries are not necessarily compatible with those of the common template. In this study, we employed a volume-based template estimation (VTE) method to create a neonatal brain template customized to a study population, while keeping the anatomical parcellation identical to that of a common MRI atlas. The VTE was used to morph the standardized parcellation map of the JHU-neonate-SS atlas to capture the anatomical features of a study population. The resultant "study-customized" T1-weighted and diffusion tensor imaging (DTI) template, with three-dimensional anatomical parcellation that defined 122 brain regions, was compared with the JHU-neonate-SS atlas, in terms of the registration accuracy. A pronounced increase in the accuracy of cortical parcellation and superior tensor alignment were observed when the customized template was used. With the customized atlas-based analysis, the fractional anisotropy (FA) detected closely approximated the manual measurements. This tool provides a solution for achieving normalization-based measurements with increased accuracy, while reporting scientific findings in a consistent framework.
AB - Atlas-based image analysis (ABA), in which an anatomical "parcellation map" is used for parcel-by-parcel image quantification, is widely used to analyze anatomical and functional changes related to brain development, aging, and various diseases. The parcellation maps are often created based on common MRI templates, which allow users to transform the template to target images, or vice versa, to perform parcel-by-parcel statistics, and report the scientific findings based on common anatomical parcels. The use of a study-specific template, which represents the anatomical features of the study population better than common templates, is preferable for accurate anatomical labeling; however, the creation of a parcellation map for a study-specific template is extremely labor intensive, and the definitions of anatomical boundaries are not necessarily compatible with those of the common template. In this study, we employed a volume-based template estimation (VTE) method to create a neonatal brain template customized to a study population, while keeping the anatomical parcellation identical to that of a common MRI atlas. The VTE was used to morph the standardized parcellation map of the JHU-neonate-SS atlas to capture the anatomical features of a study population. The resultant "study-customized" T1-weighted and diffusion tensor imaging (DTI) template, with three-dimensional anatomical parcellation that defined 122 brain regions, was compared with the JHU-neonate-SS atlas, in terms of the registration accuracy. A pronounced increase in the accuracy of cortical parcellation and superior tensor alignment were observed when the customized template was used. With the customized atlas-based analysis, the fractional anisotropy (FA) detected closely approximated the manual measurements. This tool provides a solution for achieving normalization-based measurements with increased accuracy, while reporting scientific findings in a consistent framework.
KW - Customized atlas
KW - MRI
KW - Neonatal brain atlas
KW - Registration accuracy
KW - Volume-based template estimation (VTE)
UR - http://www.scopus.com/inward/record.url?scp=84904906899&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84904906899&partnerID=8YFLogxK
U2 - 10.1016/j.neuroimage.2014.07.001
DO - 10.1016/j.neuroimage.2014.07.001
M3 - Article
C2 - 25026155
AN - SCOPUS:84904906899
VL - 101
SP - 256
EP - 267
JO - NeuroImage
JF - NeuroImage
SN - 1053-8119
ER -