Guidelines for the content and format of PET brain data in publications and archives: A consensus paper

Author:

Knudsen Gitte M1,Ganz Melanie1,Appelhoff Stefan2,Boellaard Ronald3,Bormans Guy4,Carson Richard E5,Catana Ciprian6,Doudet Doris7,Gee Antony D8ORCID,Greve Douglas N6,Gunn Roger N9,Halldin Christer10,Herscovitch Peter11,Huang Henry5,Keller Sune H12,Lammertsma Adriaan A3,Lanzenberger Rupert13,Liow Jeih-San14,Lohith Talakad G15,Lubberink Mark16,Lyoo Chul H17,Mann J John18,Matheson Granville J10,Nichols Thomas E19ORCID,Nørgaard Martin1ORCID,Ogden Todd20,Parsey Ramin21,Pike Victor W14,Price Julie6,Rizzo Gaia9,Rosa-Neto Pedro2223,Schain Martin20,Scott Peter JH24,Searle Graham9,Slifstein Mark21,Suhara Tetsuya25,Talbot Peter S26,Thomas Adam27,Veronese Mattia28,Wong Dean F29,Yaqub Maqsood3,Zanderigo Francesca30,Zoghbi Sami14,Innis Robert B14

Affiliation:

1. Neurobiology Research Unit, Rigshospital and University of Copenhagen, Copenhagen, Denmark

2. Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany

3. Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, The Netherlands

4. Laboratory for Radiopharmaceutical Research, KU, Leuven, Belgium

5. Department of Radiology and Biomedical Imaging, Yale University, New Haven, USA

6. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Department of Radiology, Boston, MA, USA

7. Department of Medicine/Neurology, Pacific Parkinson Research Center, Vancouver, Canada

8. Clinical PET Centre, King’s College London, London, UK

9. Invicro and Division of Brain Sciences, Imperial College London, London, UK

10. Center for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden;

11. Department of Positron Emission Tomography, National Institutes of Health, Bethesda, USA

12. Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark

13. Department of Psychiatry and Psychotherapy, Medical University of Vienna, Wien, Austria

14. Molecular Imaging Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, USA

15. Translational Biomarkers, Merck & Co., West Point, USA

16. Uppsala University, Department of Surgical Sciences/Radiology and Nuclear Medicine, Uppsala University Hospital, Department of Medical Physics, Sweden

17. Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea

18. Department of Psychiatry, Molecular Imaging and Neuropathology Division, Columbia University, New York, USA

19. Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, UK

20. Columbia Mailman School of Public Health, Columbia University, New York, USA

21. Department of Psychiatry, School of Medicine, Stony Brook University, Stony Brook, NY, USA

22. McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada

23. Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, Douglas Mental Health University Institute, Montreal, Canada

24. Department of Radiology, University of Michigan, Ann Arbor, USA

25. Institute for Quantum Life Science, National Institute for Quantum and Radiological Science and Technology, Chiba, Japan

26. Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK

27. National Institute of Mental Health, Bethesda, USA

28. Centre for Neuroimaging Sciences, King’s College London, London, UK

29. Department of Radiology, Johns Hopkins Hospital, Baltimore, USA

30. Department of Psychiatry, Columbia University, New York, USA

Abstract

It is a growing concern that outcomes of neuroimaging studies often cannot be replicated. To counteract this, the magnetic resonance (MR) neuroimaging community has promoted acquisition standards and created data sharing platforms, based on a consensus on how to organize and share MR neuroimaging data. Here, we take a similar approach to positron emission tomography (PET) data. To facilitate comparison of findings across studies, we first recommend publication standards for tracer characteristics, image acquisition, image preprocessing, and outcome estimation for PET neuroimaging data. The co-authors of this paper, representing more than 25 PET centers worldwide, voted to classify information as mandatory, recommended, or optional. Second, we describe a framework to facilitate data archiving and data sharing within and across centers. Because of the high cost of PET neuroimaging studies, sample sizes tend to be small and relatively few sites worldwide have the required multidisciplinary expertise to properly conduct and analyze PET studies. Data sharing will make it easier to combine datasets from different centers to achieve larger sample sizes and stronger statistical power to test hypotheses. The combining of datasets from different centers may be enhanced by adoption of a common set of best practices in data acquisition and analysis.

Publisher

SAGE Publications

Subject

Cardiology and Cardiovascular Medicine,Clinical Neurology,Neurology

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