Imperial College London
Alternate

ProfessorRogerGunn

Faculty of Medicine, Department of Brain Sciences

Emeritus Professor of Molecular Neuroimaging
 
 
 
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Contact

 

r.gunn

 
 
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Location

 

Burlington DanesHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Knudsen:2020:10.1177/0271678X20905433,
author = {Knudsen, GM and Ganz, M and Appelhoff, S and Boellaard, R and Bormans, G and Carson, RE and Catana, C and Doudet, D and Gee, AD and Greve, DN and Gunn, RN and Halldin, C and Herscovitch, P and Huang, H and Keller, SH and Lammertsma, AA and Lanzenberger, R and Liow, J-S and Lohith, TG and Lubberink, M and Lyoo, CH and Mann, JJ and Matheson, GJ and Nichols, TE and Nørgaard, M and Ogden, T and Parsey, R and Pike, VW and Price, J and Rizzo, G and Rosa-Neto, P and Schain, M and Scott, PJ and Searle, G and Slifstein, M and Suhara, T and Talbot, PS and Thomas, A and Veronese, M and Wong, DF and Yaqub, M and Zanderigo, F and Zoghbi, S and Innis, RB},
doi = {10.1177/0271678X20905433},
journal = {Journal of Cerebral Blood Flow and Metabolism},
title = {Guidelines for the content and format of PET brain data in publications and archives: A consensus paper.},
url = {http://dx.doi.org/10.1177/0271678X20905433},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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.
AU  - Knudsen,GM
AU  - Ganz,M
AU  - Appelhoff,S
AU  - Boellaard,R
AU  - Bormans,G
AU  - Carson,RE
AU  - Catana,C
AU  - Doudet,D
AU  - Gee,AD
AU  - Greve,DN
AU  - Gunn,RN
AU  - Halldin,C
AU  - Herscovitch,P
AU  - Huang,H
AU  - Keller,SH
AU  - Lammertsma,AA
AU  - Lanzenberger,R
AU  - Liow,J-S
AU  - Lohith,TG
AU  - Lubberink,M
AU  - Lyoo,CH
AU  - Mann,JJ
AU  - Matheson,GJ
AU  - Nichols,TE
AU  - Nørgaard,M
AU  - Ogden,T
AU  - Parsey,R
AU  - Pike,VW
AU  - Price,J
AU  - Rizzo,G
AU  - Rosa-Neto,P
AU  - Schain,M
AU  - Scott,PJ
AU  - Searle,G
AU  - Slifstein,M
AU  - Suhara,T
AU  - Talbot,PS
AU  - Thomas,A
AU  - Veronese,M
AU  - Wong,DF
AU  - Yaqub,M
AU  - Zanderigo,F
AU  - Zoghbi,S
AU  - Innis,RB
DO  - 10.1177/0271678X20905433
PY  - 2020///
SN  - 0271-678X
TI  - Guidelines for the content and format of PET brain data in publications and archives: A consensus paper.
T2  - Journal of Cerebral Blood Flow and Metabolism
UR  - http://dx.doi.org/10.1177/0271678X20905433
UR  - https://www.ncbi.nlm.nih.gov/pubmed/32065076
UR  - https://journals.sagepub.com/doi/10.1177/0271678X20905433
ER  -
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