fig1

Figure 1. Panvascular aging data ecosystem: a multi-source integration and application framework. Data sources (left) include imaging (MRI, CT, PET), multi-omics (genomics, proteomics, metabolomics), clinical records & longitudinal follow-up, wearables & lifestyle data, and environmental exposures. The integration layer (center) performs data cleaning, standardization, and multimodal fusion into Big Data Platforms. Outputs (right) comprise risk prediction models, individualized interventions, and cross-organ mechanism research. Arrows indicate the direction of data flow and hierarchical aggregation. MRI: Magnetic resonance imaging; CT: computed tomography; PET: positron emission tomography.