多模态MRI联合建模，实现全生命周期脑龄精准预测
A Two-Stage Multi-Modal MRI Framework for Lifespan Brain Age Prediction
- 分两阶段处理不同模态数据，晚期融合提升跨年龄适用性
- 在6个发育阶段内预测脑龄，误差小于1.5岁（全年龄段）
- 适合研究脑发育与衰老机制的神经科学与医学工作者
从MRI中准确量化脑龄已成为评估脑健康的重要生物标志物。然而，现有方法通常局限于狭窄年龄范围和单模态MRI数据，难以捕捉人类全生命周期中宏观与微观结构变化的协同演化。为此，我们提出一种多模态脑龄预测框架，用于表征脑形态与白质组织结构的整合演变。该模型采用两阶段架构：各模态独立处理，并在两个阶段均通过晚期融合进行集成——首先将受试者分类至六个发育阶段之一，然后在预测的阶段内估计年龄。这一设计实现了对不同发育时期脑成熟度的统一、全生命周期评估。
原文摘要 · Abstract (English)
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.
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