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Procrustes-based geometric morphometrics on MRI images: An example of inter-operator bias in 3D landmarks and its impact on big datasets

机译:MRI图像上基于Proprocrusts的几何形态计量学:3D地标中操作员间偏差及其对大数据集的影响的示例

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摘要

Using 3D anatomical landmarks from adult human head MRIs, we assessed the magnitude of inter-operator differences in Procrustes-based geometric morphometric analyses. An in depth analysis of both absolute and relative error was performed in a subsample of individuals with replicated digitization by three different operators. The effect of inter-operator differences was also explored in a large sample of more than 900 individuals. Although absolute error was not unusual for MRI measurements, including bone landmarks, shape was particularly affected by differences among operators, with up to more than 30% of sample variation accounted for by this type of error. The magnitude of the bias was such that it dominated the main pattern of bone and total (all landmarks included) shape variation, largely surpassing the effect of sex differences between hundreds of men and women. In contrast, however, we found higher reproducibility in soft-tissue nasal landmarks, despite relatively larger errors in estimates of nasal size. Our study exemplifies the assessment of measurement error using geometric morphometrics on landmarks from MRIs and stresses the importance of relating it to total sample variance within the specific methodological framework being used. In summary, precise landmarks may not necessarily imply negligible errors, especially in shape data; indeed, size and shape may be differentially impacted by measurement error and different types of landmarks may have relatively larger or smaller errors. Importantly, and consistently with other recent studies using geometric morphometrics on digital images (which, however, were not specific to MRI data), this study showed that inter-operator biases can be a major source of error in the analysis of large samples, as those that are becoming increasingly common in the 'era of big data'.
机译:使用来自成人人头MRI的3D解剖标志,我们评估了基于Procrustes的几何形态分析中操作者之间差异的大小。由三个不同的操作员对具有重复数字化的个人子样本进行了绝对和相对误差的深入分析。在超过900个人的大样本中,还探讨了操作员间差异的影响。尽管绝对误差在包括骨骼标志在内的MRI测量中并不罕见,但形状尤其受操作者之间差异的影响,这种类型的误差最多可导致超过30%的样品变化。偏差的程度如此之大,以至于它主导了骨骼的主要模式和整体(包括所有地标)形状变化,大大超过了成百​​上千男女之间性别差异的影响。相反,尽管鼻腔大小的估计误差较大,但我们发现软组织鼻腔标志物具有较高的可重复性。我们的研究通过在MRI上对地标使用几何形态计量学来举例说明测量误差的评估,并强调了在所使用的特定方法框架内将其与总样本差异相关联的重要性。总而言之,精确的界标不一定意味着隐含的误差,尤其是在形状数据中。实际上,尺寸和形状可能受到测量误差的不同影响,并且不同类型的界标可能具有相对较大或较小的误差。重要的是,与最近在数字图像上使用几何形态计量学的其他研究一致(然而,这并非特定于MRI数据),该研究表明,操作员之间的偏差可能是大样本分析中误差的主要来源,因为在“大数据时代”变得越来越普遍的那些。

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