Mapping lifetime brain volumetry with covariate-adjusted restricted cubic spline regression from cross-sectional multi-site MRI

Yuankai Huo, Katherine Aboud, Hakmook Kang, Laurie E. Cutting, Bennett A. Landman

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

Abstract

Understanding brain volumetry is essential to understand neurodevelopment and disease. Historically,age-related changes have been studied in detail for specific age ranges (e.g.,early childhood,teen,young adults,elderly,etc.) or more sparsely sampled for wider considerations of lifetime aging. Recent advancements in data sharing and robust processing have made available considerable quantities of brain images from normal,healthy volunteers. However,existing analysis approaches have had difficulty addressing (1) complex volumetric developments on the large cohort across the life time (e.g.,beyond cubic age trends),(2) accounting for confound effects,and (3) maintaining an analysis framework consistent with the general linear model (GLM) approach pervasive in neuroscience. To address these challenges,we propose to use covariateadjusted restricted cubic spline (C-RCS) regression within a multi-site crosssectional framework. This model allows for flexible consideration of nonlinear age-associated patterns while accounting for traditional covariates and interaction effects. As a demonstration of this approach on lifetime brain aging,we derive normative volumetric trajectories and 95 % confidence intervals from 5111 healthy patients from 64 sites while accounting for confounding sex,intracranial volume and field strength effects. The volumetric results are shown to be consistent with traditional studies that have explored more limited age ranges using single-site analyses. This work represents the first integration of C-RCS with neuroimaging and the derivation of structural covariance networks (SCNs) from a large study of multi-site,cross-sectional data.

Original languageEnglish (US)
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings
PublisherSpringer Verlag
Pages81-88
Number of pages8
Volume9900 LNCS
ISBN (Print)9783319467191
DOIs
StatePublished - 2016
Externally publishedYes
Event1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016 - Athens, Greece
Duration: Oct 21 2016Oct 21 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9900 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016
Country/TerritoryGreece
CityAthens
Period10/21/1610/21/16

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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