Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Invicro LLC, London, UK.
J Cereb Blood Flow Metab. 2021 Oct;41(10):2778-2796. doi: 10.1177/0271678X211015101. Epub 2021 May 17.
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.
发现结果的可重复性是神经影像学领域目前面临的一个极具说服力的方法学问题。即使使用相同的数据进行分析,图像处理、量化和统计的标准化流程的缺乏也会导致结果的可变性和解释的不一致,这在 MRI 研究中尤为明显,该方法的无可争议的价值因一些产生不一致结果的研究而变得复杂。然而,任何具有复杂数据和灵活分析程序的研究领域都可能经历类似的可重复性缺失问题。本文针对脑 PET 成像研究了这一问题。在 2018 年神经受体映射会议期间,脑 PET 社区面临着一项涉及模拟神经递质释放实验的计算竞赛挑战。14 个国际团队分析了相同的成像数据集,其真实情况是已知的。尽管方法多样,但参与者的解决方案是一致的,尽管不完全相同。这些结果应该让人们意识到,仅增加 PET 数据的共享将只是提高神经影像学结果可信度的一个组成部分,重要的是要通过已用于量化数据的分析流程和程序的完整详细信息来对此进行补充。