title: Diffeomorphic shape trajectories for improved longitudinal segmentation and statistics.
abstract: Longitudinal imaging studies involve tracking changes in individuals by repeated image acquisition over time. The goal of these studies is to quantify biological shape variability within and across individuals, and also to distinguish between normal and disease populations. However, data variability is influenced by outside sources such as image acquisition, image calibration, human expert judgment, and limited robustness of segmentation and registration algorithms. In this paper, we propose a two-stage method for the statistical analysis of longitudinal shape. In the first stage, we estimate diffeomorphic shape trajectories for each individual that minimize inconsistencies in segmented shapes across time. This is followed by a longitudinal mixed-effects statistical model in the second stage for testing differences in shape trajectories between groups. We apply our method to a longitudinal database from PREDICT-HD and demonstrate our approach reduces unwanted variability for both shape and derived measures, such as volume. This leads to greater statistical power to distinguish differences in shape trajectory between healthy subjects and subjects with a genetic biomarker for Huntington's disease (HD).
authors.forename: Prasanna
authors.initials: P
authors.lastname: Muralidharan
authors.forename: James
authors.initials: J
authors.lastname: Fishbaugh
authors.forename: Hans J
authors.initials: HJ
authors.lastname: Johnson
authors.forename: Stanley
authors.initials: S
authors.lastname: Durrleman
authors.forename: Jane S
authors.initials: JS
authors.lastname: Paulsen
authors.forename: Guido
authors.initials: G
authors.lastname: Gerig
authors.forename: P Thomas
authors.initials: PT
authors.lastname: Fletcher
mesh_terms: D000375:Aging / Q000473:pathology*; D000465:Algorithms; D001921:Brain / Q000473:pathology*; D003627:Data Interpretation, Statistical; D006801:Humans; D006816:Huntington Disease / Q000473:pathology*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008137:Longitudinal Studies; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity