Centre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, UK.
School of Informatics, University of Edinburgh, Edinburgh, UK.
Transl Vis Sci Technol. 2024 Apr 2;13(4):19. doi: 10.1167/tvst.13.4.19.
To investigate whether fractal dimension (FD), a retinal trait relating to vascular complexity and a potential "oculomics" biomarker for systemic disease, is applicable to a mixed-age, primary-care population.
We used cross-sectional data (96 individuals; 183 eyes; ages 18-81 years) from a university-based optometry clinic in Glasgow, Scotland, to study the association between FD and systemic health. We computed FD from color fundus images using Deep Approximation of Retinal Traits (DART), an artificial intelligence-based method designed to be more robust to poor image quality.
Despite DART being designed to be more robust, a significant association (P < 0.001) between image quality and FD remained. Consistent with previous literature, age was associated with lower FD (P < 0.001 univariate and when adjusting for image quality). However, FD variance was higher in older patients, and some patients over 60 had FD comparable to those of patients in their 20s. Prevalent systemic conditions were significantly (P = 0.037) associated with lower FD when adjusting for image quality and age.
Our work suggests that FD as a biomarker for systemic health extends to mixed-age, primary-care populations. FD decreases with age but might not substantially decrease in everyone. This should be further investigated using longitudinal data. Finally, image quality was associated with FD, but it is unclear whether this finding is measurement error caused by image quality or confounded by age and health. Future work should investigate this to clarify whether adjusting for image quality is appropriate.
FD could potentially be used in regular screening settings, but questions around image quality remain.
研究分形维数（FD）是否适用于混合年龄的初级保健人群，FD 是一种与血管复杂性相关的视网膜特征，也是系统性疾病的潜在“眼科学”生物标志物。
我们使用苏格兰格拉斯哥大学视光诊所的横断面数据（96 名个体；183 只眼；年龄 18-81 岁），研究 FD 与全身健康之间的关联。我们使用基于人工智能的 Deep Approximation of Retinal Traits（DART）从眼底彩色图像中计算 FD，该方法旨在对图像质量较差更具鲁棒性。
尽管 DART 旨在更稳健，但图像质量与 FD 之间仍存在显著关联（P < 0.001）。与之前的文献一致，年龄与较低的 FD 相关（P < 0.001 单变量和调整图像质量后）。然而，老年患者的 FD 方差更高，一些 60 岁以上的患者的 FD 与 20 多岁的患者相当。调整图像质量和年龄后，常见的系统性疾病与较低的 FD 显著相关（P = 0.037）。
我们的工作表明，作为系统性健康生物标志物的 FD 扩展到了混合年龄的初级保健人群。FD 随年龄增长而降低，但并非每个人都会显著降低。这应该使用纵向数据进一步研究。最后，图像质量与 FD 相关，但尚不清楚这一发现是由于图像质量引起的测量误差，还是由年龄和健康状况引起的混杂因素。未来的工作应该对此进行调查，以明确是否需要调整图像质量。
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