发表机构
Tan Tock Seng Hospital; National Healthcare Group（陈笃生医院; 国家卫生集团）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对视网膜年龄预测中忽视结构-血管异质老化的问题，提出统一双路径框架SAP-DPF，分别估计OCT结构老化与OCTA血管老化，经不确定性门控融合，将平均绝对误差降至4.02年。
AI 中文摘要
估计生物学年龄是衰老研究中的一项重要任务，因为它量化了超越实际年龄的个体衰老轨迹。视网膜年龄估计已成为该领域中一个成熟的方向，因为视网膜成像为神经和微血管衰老提供了非侵入性窗口。然而，现有研究主要集中在眼底照片上，通常将视网膜老化建模为单一通用过程。尽管生物学衰老是异质性的，不同器官或组织可能以不同速率衰老，但很少有研究明确区分视网膜年龄预测中的神经结构和血管老化。本研究通过使用光学相干断层扫描（OCT）图像研究神经结构老化，并使用光学相干断层扫描血管成像（OCTA）图像研究血管老化，填补了这一空白。我们将多模态OCT/OCTA视网膜年龄估计表述为结构-血管老化分解问题，并提出SAP-DPF，一个统一的双路径预测框架，该框架分别估计结构和血管老化，建模模态特定的预测不确定性，并通过不确定性门控的后期融合模块自适应地融合两种老化信号。使用这一统一预测框架，SAP-DPF在结构路径上实现了4.07年的平均绝对误差，在血管路径上实现了7.37年的平均绝对误差，而所提出的后期融合算法进一步将整体平均绝对误差提高到4.02年，相比最强的单模态基线提高了12.52%。这项工作可能将视网膜年龄预测扩展到单一生物学年龄估计之外，为研究结构和血管对异质性视网膜老化的贡献提供了一个框架。
英文摘要
Estimating biological age is an important task in ageing research, as it quantifies individual ageing trajectories beyond chronological age. Retinal age estimation has become a well-established direction in this area because retinal imaging provides a non-invasive window into neural and microvascular ageing. Existing studies, however, have predominantly focused on fundus photographs and usually model retinal ageing as a single generic process. Although biological ageing is heterogeneous and different organs or tissues may age at different rates, little research has explicitly distinguished neurostructural and vascular ageing in retinal age prediction. This work fills this gap by studying neurostructural ageing with Optical Coherence Tomography (OCT) images and vascular ageing with Optical Coherence Tomography Angiography (OCTA) images. We formulate multimodal OCT/OCTA retinal age estimation as a structural-vascular ageing decomposition problem and propose SAP-DPF, a unified dual-path prediction framework that separately estimates structural and vascular ageing, models modality-specific predictive uncertainty, and adaptively fuses the two ageing signals through an uncertainty-gated late-fusion module. Using this unified prediction framework, SAP-DPF achieves a mean absolute error of 4.07 years for the structural pathway and 7.37 years for the vascular pathway, while the proposed late-fusion algorithm further improves the overall mean absolute error to 4.02 years, representing a 12.52% improvement over the strongest single-modality baseline. This work could extend retinal age prediction beyond a single biological-age estimate, providing a framework for investigating structural and vascular contributions to heterogeneous retinal ageing.
CommentsAccepted as a short paper at IEEE BIBM 2026
