A Two-Stage Multi-Modal MRI Framework for Lifespan Brain Age Prediction
For researchers studying brain aging and development, this framework provides a unified method to predict brain age across the lifespan using multi-modal MRI, addressing limitations of narrow age ranges and single-modality data.
This paper presents a two-stage multi-modal MRI framework for brain age prediction across the entire lifespan, integrating T1-weighted and diffusion MRI data. The model first classifies subjects into developmental stages, then estimates age within each stage, achieving improved accuracy over single-modality and single-stage approaches.
The accurate quantification of brain age from MRI has emerged as an important biomarker of brain health. However, existing approaches are often restricted to narrow age ranges and single-modality MRI data, limiting their capacity to capture the coordinated macro- and microstructural changes that unfold across the human lifespan. To address these limitations, we developed a multi-modal brain age framework to characterize the integrated evolution of brain morphology and white matter organization. Our model adopts a two-stage architecture, where modalities are processed independently and integrated via late fusion in both stages: first to classify each subject into one of six developmental stages, and then to estimate age within the predicted stage. This design enables a unified and lifespan-spanning assessment of brain maturity across diverse developmental periods.