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Publication Detail
Reproducibility of findings in modern PET neuroimaging: insight from the NRM2018 grand challenge
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Journal Article
  • Authors:
    Veronese M, Rizzo G, Belzunce M, Schubert J, Searle G, Whittington A, Mansur A, Dunn J, Reader A, Gunn RN, Albrecht DS, Mandeville JB, Sander CY, Price J, Levine MA, Rullmann M, Becker GA, Barthel H, Hesse S, Sattler B, Sabri O, Zanderigo F, Rubin-Falcone H, Ogden T, Johansson J, Jonasson L, Grill F, Karalija N, Rieckmann A, Boellaard R, Golla S, Yaqub M, Erlandsson K, Thomas BA, Kr€amer SD, Lawson LN, Lawson UA, Norgaard M, Ganz M, Schain M, Svarer C, Hansen HD, Knudsen GM, Smith CT, Jonasson M, Lubberink M, Tonietto M
  • Publication date:
  • Pagination:
    2778, 2796
  • Journal:
    Journal of Cerebral Blood Flow and Metabolism
  • Volume:
  • Issue:
  • Status:
  • Print ISSN:
The reproducibility of findings is a compelling methodological problem that the neuroimaging community is facing these days. The lack of standardized pipelines for image processing, quantification and statistics plays a major role in the variability and interpretation of results, even when the same data are analysed. This problem is well-known in MRI studies, where the indisputable value of the method has been complicated by a number of studies that produce discrepant results. However, any research domain with complex data and flexible analytical procedures can experience a similar lack of reproducibility. In this paper we investigate this issue for brain PET imaging. During the 2018 NeuroReceptor Mapping conference, the brain PET community was challenged with a computational contest involving a simulated neurotransmitter release experiment. Fourteen international teams analysed the same imaging dataset, for which the ground-truth was known. Despite a plurality of methods, the solutions were consistent across participants, although not identical. These results should create awareness that the increased sharing of PET data alone will only be one component of enhancing confidence in neuroimaging results and that it will be important to complement this with full details of the analysis pipelines and procedures that have been used to quantify data.
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