Cortical thickness in brain imaging studies using FreeSurfer and CAT12: A matter of reproducibility

Q4 Neuroscience Neuroimage. Reports Pub Date : 2022-12-01 DOI:10.1016/j.ynirp.2022.100137
Maria de Fátima Machado Dias , Paulo Carvalho , Miguel Castelo-Branco , João Valente Duarte
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引用次数: 3

Abstract

A reproducibility crisis has been reported across many research fields, including neuroimaging, reaching up to 70% of studies. Neuroimaging data, such as magnetic resonance imaging (MRI), requires pre-processing to allow for inter-subject comparison, increase signal contrast and noise reduction. As manual MRI pre-processing is time consuming and requires expertise, multiple automatic pre-processing frameworks have been proposed. However, neuroimaging studies often report divergent results, even for similar populations, thus it is important to determine whether this occurs as a result of different processing tools. Two of the most used tools are FreeSurfer and the Computational Anatomy Toolbox (CAT12). In this study we assessed the reproducibility between these two automatic pre-processing frameworks for structural MRI and test-retest reliability within framework on estimation of cortical thickness. Our results show that the reproducibility between the frameworks is lower at the region-of-interest (ROI) level than at individual level. Furthermore, we found that the reproducibility was lower in paediatric samples than in adults. Finally, an acquisition site effect was also identified. Given the widespread use of these frameworks in basic and clinical neuroscience, the results of multicentric cross-sectional studies must be interpreted with caution, particularly with paediatric samples. The observed reproducibility issue might be one of the sources of discrepancies reported in neuroimaging studies. On a positive note, framework test-retest reliability within subject is high, suggesting that inconsistency of results may be less concerning in longitudinal studies. The code is available at: https://cibit-uc.github.io/fs-cat12-cortical-thickness-reproducibility.

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使用FreeSurfer和CAT12进行脑成像研究的皮质厚度:可重复性问题
据报道,包括神经影像学在内的许多研究领域都存在可重复性危机,高达70%的研究都存在可重复性危机。神经成像数据,如磁共振成像(MRI),需要预处理,以允许主体间比较,增加信号对比度和降噪。由于人工MRI预处理耗时且需要专业知识,因此提出了多种自动预处理框架。然而,即使在相似的人群中,神经影像学研究也经常报告不同的结果,因此确定这种情况是否由于不同的处理工具而发生是很重要的。两个最常用的工具是FreeSurfer和计算解剖工具箱(CAT12)。在这项研究中,我们评估了这两种结构MRI自动预处理框架之间的再现性,以及在皮质厚度估计框架内的测试-重测可靠性。我们的研究结果表明,在兴趣区域(ROI)水平上,框架之间的可重复性低于个体水平。此外,我们发现再现性是在儿童样本低于成人。最后,我们还发现了一种获取地点效应。鉴于这些框架在基础和临床神经科学中的广泛使用,多中心横断面研究的结果必须谨慎解释,特别是对于儿科样本。观察到的可重复性问题可能是神经影像学研究报告中差异的来源之一。从积极的方面来看,框架测试-重测在受试者中的信度很高,这表明在纵向研究中,结果的不一致可能较少受到关注。代码可从https://cibit-uc.github.io/fs-cat12-cortical-thickness-reproducibility获得。
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来源期刊
Neuroimage. Reports
Neuroimage. Reports Neuroscience (General)
CiteScore
1.90
自引率
0.00%
发文量
0
审稿时长
87 days
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