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Guidelines for the content and format of PET brain data in publications and archives: A consensus paper
https://repo.qst.go.jp/records/80041
https://repo.qst.go.jp/records/800416d154eaa-9278-4062-ae49-9582d36bae8c
Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2020-06-09 | |||||
タイトル | ||||||
タイトル | Guidelines for the content and format of PET brain data in publications and archives: A consensus paper | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
アクセス権 | ||||||
アクセス権 | metadata only access | |||||
アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
著者 |
M Knudsen, Gitte
× M Knudsen, Gitte× Ganz, Melanie× Appelhoff, Stefan× Boellaard, Ronald× Guy Bormans× E Carson, Richard× Catana, Ciprian× Doudet, Doris× D Gee, Antony× N Greve, Douglas× Suhara, Tetsuya× Others, Many× Suhara, Tetsuya |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | 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. | |||||
書誌情報 |
Journal of Cerebral Blood Flow & Metabolism 巻 40, 号 8, 発行日 2020-02 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 0271-678X | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1177/0271678X20905433 | |||||
関連サイト | ||||||
識別子タイプ | URI | |||||
関連識別子 | https://pubmed.ncbi.nlm.nih.gov/32065076/ |