Longitudinal Modeling of Iron Accumulation in the Thalamus and Putamen Using Change-Point Mixed Effects Analysis

Motivation: Iron accumulation in deep gray matter (DGM) regions, essential for brain function, varies across individuals, complicating detection of disease-related changes. Cross-sectional studies struggle to capture individual iron accumulation trajectories due to inter-subject variability. Goal(s): This study aimed to define normative, intra-subject changes in DGM iron over time using longitudinal quantitative susceptibility mapping (QSM), focusing on thalamus and putamen regions. Approach: Novel change-point mixed effects model was appplied to healthy adults' QSM data across multiple time points. Analyses examined intra-subject trajectories and sex-specific patterns. Results: Our model revealed consistent intra-subject iron trajectories, with sex-specific change points. Minimal inter-subject slope variability confirmed stable individual trajectories. Impact: This study's normative DGM iron trajectories provide a benchmark, offering a sensitive longitudinal biomarker for detecting early pathological changes in neurodegenerative diseases.