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The eye, the kidney, and cardiovascular disease: old concepts, better tools, and new horizons
Tariq E Farrah1, Baljean Dhillon2, Pearse A Keane3
1University/BHF Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK; Department of Renal Medicine, Royal Infirmary of Edinburgh, Edinburgh, UK.
Insights
Eye imaging can detect early signs of chronic kidney disease (CKD) and cardiovascular disease. Optical coherence tomography (OCT) and deep learning analyze retinal vessels to identify at-risk patients, improving risk stratification.
Area of Science:
- Ophthalmology
- Nephrology
- Cardiology
- Medical Imaging
- Artificial Intelligence
Background:
- Chronic kidney disease (CKD) and cardiovascular disease (CVD) are prevalent, with hypertension and diabetes as key risk factors.
- Microvascular alterations are implicated in the pathogenesis of hypertension, diabetes, CKD, and CVD.
- Current risk stratification tools for CKD and CVD require enhancement for greater precision.
Purpose of the Study:
- To investigate the potential of noninvasive retinal imaging to detect microvascular changes associated with CKD and CVD.
- To evaluate retinal vessel-derived metrics as predictors of incident hypertension, diabetes, CKD, and CVD.
- To explore the role of optical coherence tomography (OCT) and deep learning in assessing ocular and renal health.
Main Methods:
- Utilizing optical coherence tomography (OCT) for high-resolution imaging of chorioretinal microcirculation.
- Employing OCT angiography for contrast-free visualization of retinal capillary networks.
- Applying deep learning algorithms to analyze OCT data for microvascular pathology detection.
Main Results:
- OCT imaging revealed retinal vessel remodeling and chorioretinal thinning in patients with hypertension, diabetes, and CKD.
- Retinal microvascular pathology identified via OCT correlates with markers of kidney injury.
- Retinal vessel-derived metrics demonstrate predictive value for incident hypertension, diabetes, CKD, and CVD.
Conclusions:
- Noninvasive retinal imaging, particularly OCT, offers a promising avenue for early detection and risk stratification of CKD and CVD.
- The eye serves as a window to systemic microvascular health, reflecting kidney and cardiovascular status.
- Integrating OCT imaging with deep learning presents a novel frontier for understanding the eye-kidney-cardiovascular axis.
Abstract:
Chronic kidney disease (CKD) is common, with hypertension and diabetes mellitus acting as major risk factors for its development. Cardiovascular disease is the leading cause of death worldwide and the most frequent end point of CKD. There is an urgent need for more precise methods to identify patients at risk of CKD and cardiovascular disease. Alterations in microvascular structure and function contribute to the development of hypertension, diabetes, CKD, and their associated cardiovascular disease. Homology between the eye and the kidney suggests that noninvasive imaging of the retinal vessels can detect these microvascular alterations to improve targeting of at-risk patients. Retinal vessel-derived metrics predict incident hypertension, diabetes, CKD, and cardiovascular disease and add to the current renal and cardiovascular risk stratification tools. The advent of optical coherence tomography (OCT) has transformed retinal imaging by capturing the chorioretinal microcirculation and its dependent tissue with near-histological resolution. In hypertension, diabetes, and CKD, OCT has revealed vessel remodeling and chorioretinal thinning. Clinical and preclinical OCT has linked retinal microvascular pathology to circulating and histological markers of injury in the kidney. The advent of OCT angiography allows contrast-free visualization of intraretinal capillary networks to potentially detect early incipient microvascular disease. Combining OCT's deep imaging with the analytical power of deep learning represents the next frontier in defining what the eye can reveal about the kidney and broader cardiovascular health.
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