Visionary AI: Decoding Systemic Vascular Health and Hypertensive Disorders in Pregnancy Through Retinal Imaging and Artificial Intelligence
Bearelly, S.; Areff, C.; Hoffman, M. K.; Sunko, D.; Laine, A. F.; Choi, B.; Coleman, H. R.; Vargas, B. C.; Li, C. Y.; Dawkins, J. J.; Amir, E.; Hark, L. A.; Booker, W. A.; Jauhal, A.; Wapner, R. J.; Shenhav, L.
Show abstract
Pregnancy orchestrates a rare physiological transformation across vascular, immune, and metabolic systems. When this dynamic balance is disrupted - as in hypertensive disorders of pregnancy - the consequences can be life-threatening, spanning maternal mortality, fetal growth restriction, and elevated long-term cardiovascular risk. Despite clear links to early placental dysfunction and systemic endothelial disruption, current screening remains clinically imprecise, biologically opaque, and logistically challenging. A shift is urgently needed - from detecting maternal complications late in gestation to understanding how pregnancy reshapes vascular physiology systemically and how this remodeling may go awry. Here we present Visionary AI, an artificial intelligence platform that integrates ultra-widefield retinal imaging (200{degrees}) with biologically grounded vascular modeling to predict hypertensive disorders of pregnancy early in gestation. Unlike prior approaches that rely on generic deep learning models and clinical inputs, Visionary AI constructs an interpretable, graph-based representation of the maternal retinal vasculature and applies topological and geometric analysis to identify condition-specific microvascular signatures. In a prospective multiethnic U.S. cohort of 1,267 pregnancies, Visionary AI achieved high predictive performance for preeclampsia (AUC = 0.90), early-onset (AUC = 0.93), and severe preeclampsia (AUC = 0.89), outperforming current clinical paradigms. It also generalized to predict gestational hypertension (AUC = 0.91) and chronic hypertension (AUC = 0.90). Topological and geometric analyses of the vasculature revealed distinct and interpretable remodeling patterns across subtypes of hypertensive disorders of pregnancy, offering mechanistic insight into their divergent pathophysiology. These results position the maternal retina as a minimally invasive, high-fidelity biosensor of early systemic vascular health and establish Visionary AI as a clinically actionable, biologically grounded diagnostic framework with potential for broad global scalability.
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