Monitoring Progression in Hypertensive Patients with Dyslipidemia Using Optical Coherence Tomography Angiography: Can...

Area of Science:

• Ophthalmology
• Medical Imaging
• Artificial Intelligence

Background:

• Hypertensive retinopathy progression analysis can be improved with AI-driven OCTA.
• Investigating the impact of uncontrolled dyslipidemia and hypertensive retinopathy on retinal microvasculature.
• Identifying potential AI software updates for OCTA analysis based on lipid levels.

Purpose of the Study:

• To utilize OCTA to study the effects of uncontrolled dyslipidemia and hypertensive retinopathy on retinal microvasculature.
• To identify potential AI software upgrades for OCTA analysis by incorporating new mathematical formulas linking OCTA parameters and lipid levels.

Main Methods:

• Prospective cohort study involving 154 eyes from Eastern European participants.
• Standardized data collection on medical history of dyslipidemia and hypertension.
• OCTA used to measure retinal vascular parameters.

Main Results:

• Statistically significant correlations found between lipid levels (total cholesterol, LDL) and retinal vascular parameters (skeleton total, FAZ circularity, NFA, VFA).
• Dyslipidemia and hypertensive retinopathy associated with reduced microvascular density and vascular flow.
• Evidence of focal capillary non-perfusion and increased FAZ in affected subjects.

Conclusions:

• Subjects with dyslipidemia and progressive hypertensive retinopathy exhibit reduced microvascular density, vascular flow, focal capillary non-perfusion, and increased FAZ.
• Improving AI systems for OCTA analysis can lead to better monitoring and early detection of hypertensive retinopathy progression.
• Research supports the development of AI screening programs for increased diagnostic efficiency.