Multimodal Retinal Imaging for Systemic Microvascular Phenotyping: Chronic Kidney Disease as a Translational Reference Model

Multimodal retinal imaging enables repeated, noninvasive assessment of vascular, neuroretinal, choroidal, perfusion, oxygenation, and flow-related phenotypes, positioning the retina as a platform for systemic microvascular phenotyping. Chronic kidney disease (CKD) provides an informative translational reference model because estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (UACR) offer standardized clinical anchors across disease severity and progression. This critical narrative review, informed by structured searches of PubMed/MEDLINE, Embase, and Web of Science, evaluates retinal phenotypes from biological association and longitudinal prediction to incremental clinical value, external validation, and implementation. Fundus photography, ultra-widefield imaging, optical coherence tomography (OCT), OCT angiography (OCTA), and functional retinal imaging provide complementary information, but retinal signals are not organ-specific. Artificial intelligence (AI)-enabled models may support automated phenotyping and opportunistic risk enrichment, but credible translation requires appropriate comparators, external validation, calibration, subgroup assessment, decision-analytic utility, and workflow evaluation. Retinal imaging should therefore be viewed as an adjunctive platform rather than a stand-alone CKD diagnostic test, with its near-term role being to identify individuals warranting confirmatory kidney assessment when retinal images are already available and recent eGFR/UACR data are absent.