Multivariate longitudinal statistics for neonatal-pediatric brain tissue development

Shun Xu, Martin Styner, John Gilmore, Guido Gerig

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    The topic of studying the growth of human brain development has become of increasing interest in the neuroimaging community. Cross-sectional studies may allow comparisons between means of different age groups, but they do not provide a growth model that integrates the continuum of time, nor do they present any information about how individuals/population change over time. Longitudinal data analysis method arises as a strong tool to address these questions. In this paper, we use longitudinal analysis methods to study tissue development in early brain growth. A novel approach of multivariate longitudinal analysis is applied to study the associations between the growth of different brain tissues. In this paper, we present the methodologies to statistically study scalar (univariate) and vector (multivariate) longitudinal data, and demonstrate exploratory results in a neuroimaging study of early brain tissue development. We obtained growth curves as a quadratic function of time for all three tissues. The quadratic terms were tested to be statistically significant, showing that there was indeed a quadratic growth of tissues in early brain development. Moreover, our result shows that there is a positive correlation between repeated measurements of any single tissue, and among those of different tissues. Our approach is generic in natural and thus can be applied to any longitudinal data with multiple outcomes, even brain structures. Also, our joint mixed model is flexible enough to allow incomplete and unbalanced data, i.e. subjects do not need to have the same number of measurements, or be measured at the exact time points.

    Original languageEnglish (US)
    Title of host publicationMedical Imaging 2008: Image Processing
    Volume6914
    DOIs
    StatePublished - 2008
    EventMedical Imaging 2008: Image Processing - San Diego, CA, United States
    Duration: Feb 17 2008Feb 19 2008

    Other

    OtherMedical Imaging 2008: Image Processing
    CountryUnited States
    CitySan Diego, CA
    Period2/17/082/19/08

    Fingerprint

    Pediatrics
    Brain
    Statistics
    Tissue
    Neuroimaging

    Keywords

    • Early brain development
    • Mixed model
    • Multivariate longitudinal analysis
    • Statistical analysis

    ASJC Scopus subject areas

    • Engineering(all)

    Cite this

    Xu, S., Styner, M., Gilmore, J., & Gerig, G. (2008). Multivariate longitudinal statistics for neonatal-pediatric brain tissue development. In Medical Imaging 2008: Image Processing (Vol. 6914). [69140C] https://doi.org/10.1117/12.773966

    Multivariate longitudinal statistics for neonatal-pediatric brain tissue development. / Xu, Shun; Styner, Martin; Gilmore, John; Gerig, Guido.

    Medical Imaging 2008: Image Processing. Vol. 6914 2008. 69140C.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Xu, S, Styner, M, Gilmore, J & Gerig, G 2008, Multivariate longitudinal statistics for neonatal-pediatric brain tissue development. in Medical Imaging 2008: Image Processing. vol. 6914, 69140C, Medical Imaging 2008: Image Processing, San Diego, CA, United States, 2/17/08. https://doi.org/10.1117/12.773966
    Xu S, Styner M, Gilmore J, Gerig G. Multivariate longitudinal statistics for neonatal-pediatric brain tissue development. In Medical Imaging 2008: Image Processing. Vol. 6914. 2008. 69140C https://doi.org/10.1117/12.773966
    Xu, Shun ; Styner, Martin ; Gilmore, John ; Gerig, Guido. / Multivariate longitudinal statistics for neonatal-pediatric brain tissue development. Medical Imaging 2008: Image Processing. Vol. 6914 2008.
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