Axial Length Matters: Scaling Effects in Retinal Fundus Image Analysis

Abstract Purpose Quantitative metrics obtained from retinal fundus images (such as vessel length, tortuosity and other scale-dependent measures) are increasingly used as potential biomarkers for systemic diseases, including cardio- and neurovascular conditions. However, with the increasing prevalence of myopia and related axial growth, this study evaluated whether axial length scaling alters inferred biomarkers compared with measurements obtained without axial length scaling and whether these effects can be corrected. Methods 2,309 clinic visits from patients aged ≤21 years were analysed for axial-length scaling analysis (range20 to 28 mm). The retinal fundus photographs were automatically segmented using AutoMorph to extract vascular metrics. The parameters were corrected for axial length using correction factors based on the Bennett–Littmann formula and true axial length. Results Axial length significantly influenced biometric parameters (vessel metrics) derived from fundus photography. The magnitude of error in diameter and length of blood vessels was approximately 4-5% for each 1 mm deviation from the reference axial length of 24 mm, whereas the error in vessel area was approximately 9-10% per 1 mm, consistent with the geometric expectation that area scales with the square of linear dimensions. The scaling corrections for different axial lengths are presented. Conclusions Axial-length-related magnification introduces systematic bias into retinal vascular metrics from fundus photographs. Bennett–Littmann correction using true axial length reduces these errors and should be adopted in quantitative fundus imaging and AI biomarker development. Translational Relevance Accounting for axial-length-related magnification may improve the comparability and accuracy of quantitative retinal vascular biomarkers derived from fundus photographs.