Functional Nonlinear Mixed Effects Models for Longitudinal Image Data

• Published in: Information Processing in Medical Imaging Vol. 24; pp. 794 - 805
• Main Authors: Luo, Xinchao, Zhu, Lixing, Kong, Linglong, Zhu, Hongtu
• Format: Book Chapter Journal Article
• Language: English
• Published: Cham Springer International Publishing 2015
• Series: Lecture Notes in Computer Science
• Subjects: Adolescent; Aging - pathology; Autistic Disorder - pathology; Brain - pathology; Child; Child, Preschool; Computer Simulation; Data Interpretation, Statistical; Female; Functional nonlinear mixed effects model; Functional response; Global test statistic; Humans; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Infant; Infant, Newborn; Longitudinal Studies; Male; Models, Statistical; Nonlinear Dynamics; Pattern Recognition, Automated - methods; Reproducibility of Results; Sensitivity and Specificity; Simultaneous confidence band; Spatial-temporal pattern; Subtraction Technique; Young Adult
• ISBN: 9783319199917; 3319199919
• ISSN: 0302-9743; 1011-2499; 1611-3349
• DOI: 10.1007/978-3-319-19992-4_63

Motivated by studying large-scale longitudinal image data, we propose a novel functional nonlinear mixed effects modeling (FNMEM) framework to model the nonlinear spatial-temporal growth patterns of brain structure and function and their association with covariates of interest (e.g., time or diagnostic status). Our FNMEM explicitly quantifies a random nonlinear association map of individual trajectories. We develop an efficient estimation method to estimate the nonlinear growth function and the covariance operator of the spatial-temporal process. We propose a global test and a simultaneous confidence band for some specific growth patterns. We conduct Monte Carlo simulation to examine the finite-sample performance of the proposed procedures. We apply FNMEM to investigate the spatial-temporal dynamics of white-matter fiber skeletons in a national database for autism research. Our FNMEM may provide a valuable tool for charting the developmental trajectories of various neuropsychiatric and neurodegenerative disorders.