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The MCIC Collection: A Shared Repository of Multi-Modal, Multi-Site Brain Image Data from a Clinical Investigation of Schizophrenia

Abstract

Expertly collected, well-curated data sets consisting of comprehensive clinical characterization and raw structural, functional and diffusion-weighted DICOM images in schizophrenia patients and sex and age-matched controls are now accessible to the scientific community through an on-line data repository (coins.mrn.org). The Mental Illness and Neuroscience Discovery Institute, now the Mind Research Network (MRN, http://www.mrn.org/), comprised of investigators at the University of New Mexico, the University of Minnesota, Massachusetts General Hospital, and the University of Iowa, conducted a cross-sectional study to identify quantitative neuroimaging biomarkers of schizophrenia. Data acquisition across multiple sites permitted the integration and cross-validation of clinical, cognitive, morphometric, and functional neuroimaging results gathered from unique samples of schizophrenia patients and controls using a common protocol across sites. Particular effort was made to recruit patients early in the course of their illness, at the onset of their symptoms. There is a relatively even sampling of illness duration in chronic patients. This data repository will be useful to 1) scientists who can study schizophrenia by further analysis of this cohort and/or by pooling with other data; 2) computer scientists and software algorithm developers for testing and validating novel registration, segmentation, and other analysis software; and 3) educators in the fields of neuroimaging, medical image analysis and medical imaging informatics who need exemplar data sets for courses and workshops. Sharing provides the opportunity for independent replication of already published results from this data set and novel exploration. This manuscript describes the inclusion/exclusion criteria, imaging parameters and other information that will assist those wishing to use this data repository.

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Acknowledgments

The authors wish to thank our many colleagues who served as mentors, advisors and supporters during the inception and conduct of the study including Donald Goff, Gina Kuperberg, Jill Goldstein, Martha Shenton, Robert McCarley, Stephan Heckers, Cynthia Wible, Raquelle Mesholam-Gately, and Mark Vangel.

We thank the study staff and clinicians at each site that were responsible for the data acquisition. These include: Stuart Wallace, Ann Cousins, Raquelle Mesholam-Gately, Steven Stufflebeam, Oliver Freudenreich, Daphne Holt, Laura Kunkel, Frank Fleming, George He, Hans Johnson, Ron Pierson, Arvind Caprihan, Phyllis Somers, Christine Portal, Kaila Norman, Diana South, Michael Doty and Haley Milner.

We would also like to acknowledge the expert guidance on image and other types of data acquisition we obtained from Lee Friedman, Stephan Posse, Jorge Jovicich, and Tom Wassink.

We would also like to acknowledge the many research assistants, students and colleagues who assisted in data curation over the years since data acquisition was completed. These include: Stuart Wallace, Carolyn Zyloney, Komal Sawlani, Esther Walton, Jill Fries, Adam Scott, Dylan Wood, Runtang Wang, William Courtney, Angie Guimaraes, Lisa Shenkman, Mustafa Kendi, Aysa Tuba Karagulle Kendi, Ryan Muetzel, Tara Biehl, and Marcus Schmidt.

Funding Acknowledgments

This work was supported primarily by the Department of Energy DE-FG02-99ER62764 through its support of the Mind Research Network (MRN, formerly known as the MIND Institute) and the consortium as well as by the National Association for Research in Schizophrenia and Affective Disorders (NARSAD) Young Investigator Award (to SE) as well as through the Blowitz-Ridgeway and Essel Foundations, and through NWO ZonMw TOP 91211021, the DFG research fellowship (to SE), the Mind Research Network, National Institutes of Health through NCRR 5 month-RR001066 (MGH General Clinical Research Center), NIMH K08 MH068540, the Biomedical Informatics Research Network with NCRR Supplements to P41 RR14075 (MGH), M01 RR 01066 (MGH), NIBIB R01EB006841 (MRN), R01EB005846 (MRN), 2R01 EB000840 (MRN), 1RC1MH089257 (MRN), as well as grant U24 RR021992.

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Gollub, R.L., Shoemaker, J.M., King, M.D. et al. The MCIC Collection: A Shared Repository of Multi-Modal, Multi-Site Brain Image Data from a Clinical Investigation of Schizophrenia. Neuroinform 11, 367–388 (2013). https://doi.org/10.1007/s12021-013-9184-3

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Keywords

  • Medical Image Data repository
  • Schizophrenia
  • fMRI
  • DWI
  • mMRI
  • Healthy controls