NeuroImage (Mar 2020)
Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan
- Raymond Pomponio,
- Guray Erus,
- Mohamad Habes,
- Jimit Doshi,
- Dhivya Srinivasan,
- Elizabeth Mamourian,
- Vishnu Bashyam,
- Ilya M. Nasrallah,
- Theodore D. Satterthwaite,
- Yong Fan,
- Lenore J. Launer,
- Colin L. Masters,
- Paul Maruff,
- Chuanjun Zhuo,
- Henry Völzke,
- Sterling C. Johnson,
- Jurgen Fripp,
- Nikolaos Koutsouleris,
- Daniel H. Wolf,
- Raquel Gur,
- Ruben Gur,
- John Morris,
- Marilyn S. Albert,
- Hans J. Grabe,
- Susan M. Resnick,
- R. Nick Bryan,
- David A. Wolk,
- Russell T. Shinohara,
- Haochang Shou,
- Christos Davatzikos
Affiliations
- Raymond Pomponio
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, USA; Corresponding author. 3700 Hamilton Walk, 7th Floor, Center of Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Guray Erus
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, USA
- Mohamad Habes
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, USA; Department of Neurology, University of Pennsylvania, USA
- Jimit Doshi
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, USA
- Dhivya Srinivasan
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, USA
- Elizabeth Mamourian
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, USA
- Vishnu Bashyam
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, USA
- Ilya M. Nasrallah
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, USA; Department of Radiology, University of Pennsylvania, USA
- Theodore D. Satterthwaite
- Department of Psychiatry, University of Pennsylvania, USA
- Yong Fan
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, USA
- Lenore J. Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, USA
- Colin L. Masters
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Australia
- Paul Maruff
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Australia
- Chuanjun Zhuo
- Tianjin Mental Health Center, Nankai University Affiliated Tianjin Anding Hospital, Tianjin, China; Department of Psychiatry, Tianjin Medical University, Tianjin, China
- Henry Völzke
- Institute for Community Medicine, University of Greifswald, Germany
- Sterling C. Johnson
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, USA
- Jurgen Fripp
- CSIRO Health and Biosecurity, Australian e-Health Research Centre CSIRO, Australia
- Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University of Munich, Germany
- Daniel H. Wolf
- Department of Psychiatry, University of Pennsylvania, USA
- Raquel Gur
- Department of Radiology, University of Pennsylvania, USA; Department of Psychiatry, University of Pennsylvania, USA
- Ruben Gur
- Department of Radiology, University of Pennsylvania, USA; Department of Psychiatry, University of Pennsylvania, USA
- John Morris
- Department of Neurology, Washington University in St. Louis, USA
- Marilyn S. Albert
- Department of Neurology, Johns Hopkins University School of Medicine, USA
- Hans J. Grabe
- Department of Psychiatry and Psychotherapy, Ernst-Moritz-Arndt University, Germany
- Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, USA
- R. Nick Bryan
- Department of Diagnostic Medicine, University of Texas at Austin, USA
- David A. Wolk
- Department of Neurology, University of Pennsylvania, USA
- Russell T. Shinohara
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, USA; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, USA; Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, USA
- Haochang Shou
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, USA; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, USA
- Christos Davatzikos
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, USA; Corresponding author.
- Journal volume & issue
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Vol. 208
p. 116450
Abstract
As medical imaging enters its information era and presents rapidly increasing needs for big data analytics, robust pooling and harmonization of imaging data across diverse cohorts with varying acquisition protocols have become critical. We describe a comprehensive effort that merges and harmonizes a large-scale dataset of 10,477 structural brain MRI scans from participants without a known neurological or psychiatric disorder from 18 different studies that represent geographic diversity. We use this dataset and multi-atlas-based image processing methods to obtain a hierarchical partition of the brain from larger anatomical regions to individual cortical and deep structures and derive age trends of brain structure through the lifespan (3–96 years old). Critically, we present and validate a methodology for harmonizing this pooled dataset in the presence of nonlinear age trends. We provide a web-based visualization interface to generate and present the resulting age trends, enabling future studies of brain structure to compare their data with this reference of brain development and aging, and to examine deviations from ranges, potentially related to disease.