Guidelines for the content and format of PET brain data in publications and archives: A consensus paper. Issue 8 (August 2020)

• Record Type: Journal Article
• Authors: Knudsen, Gitte M; Ganz, Melanie; Appelhoff, Stefan; Boellaard, Ronald; Bormans, Guy; Carson, Richard E; Catana, Ciprian; Doudet, Doris; Gee, Antony D; Greve, Douglas N; Gunn, Roger N; Halldin, Christer; Herscovitch, Peter; Huang, Henry; Keller, Sune H; Lammertsma, Adriaan A; Lanzenberger, Rupert; Liow, Jeih-San; Lohith, Talakad G; Lubberink, Mark; Lyoo, Chul H; Mann, J John; Matheson, Granville J; Nichols, Thomas E; Nørgaard, Martin; Ogden, Todd; Parsey, Ramin; Pike, Victor W; Price, Julie; Rizzo, Gaia; Rosa-Neto, Pedro; Schain, Martin; Scott, Peter JH; Searle, Graham; Slifstein, Mark; Suhara, Tetsuya; Talbot, Peter S; Thomas, Adam; Veronese, Mattia; Wong, Dean F; Yaqub, Maqsood; Zanderigo, Francesca; Zoghbi, Sami; Innis, Robert B;
• Is Part Of: Journal of cerebral blood flow & metabolism. Volume 40:Issue 8(2020)
• Page Start: 1576
• Page End: 1585
• Publication Date: 2020-08
• Subjects: Consensus guidelines -- data sharing -- data structure -- open source -- positron emission tomography; Cerebral circulation -- Periodicals; Brain -- Metabolism -- Periodicals; Brain -- Blood-vessels -- Periodicals; Cerebrovascular disease -- Periodicals; 612.824
• DOI: 10.1177/0271678X20905433
• Languages: English
• ISSNs: 0271-678X

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.