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

Amro Daboul, Tatyana Ivanovska, Robin Bülow, Reiner Biffar, Andrea Cardini

    Research output: Contribution to journalArticle

    2 Citations (Scopus)

    Abstract

    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’.

    Original languageEnglish
    Article numbere0197675
    JournalPLoS One
    Volume13
    Issue number5
    DOIs
    Publication statusPublished - 1 May 2018

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    operator regions
    Nose
    Magnetic resonance imaging
    Bone and Bones
    Sex Characteristics
    Research Design
    Head
    bones
    Measurement errors
    sampling
    Bone
    digital images
    gender differences
    reproducibility
    Analog to digital conversion
    Datasets
    Tissue

    Cite this

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    abstract = "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’.",
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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. / Daboul, Amro; Ivanovska, Tatyana; Bülow, Robin; Biffar, Reiner; Cardini, Andrea.

    In: PLoS One, Vol. 13, No. 5, e0197675, 01.05.2018.

    Research output: Contribution to journalArticle

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    T1 - Procrustes-based geometric morphometrics on MRI images

    T2 - An example of inter-operator bias in 3D landmarks and its impact on big datasets

    AU - Daboul, Amro

    AU - Ivanovska, Tatyana

    AU - Bülow, Robin

    AU - Biffar, Reiner

    AU - Cardini, Andrea

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