Studying hypertension in ocular fundus images using Hausdorff dispersion ordering

Guillermo Ayala1, María Concepción López-Díaz, Miguel López-Díaz

  • 1Departamento de Estadística e I.O., Universidad de Valencia, Avda. Vicent Andrés Estellés 1, E-46100 Burjasot, Valencia, Spain. guillermo.ayala@uv.es

Insights

Vessel diameter dispersion in retinal images, reflecting vascular health, is higher in hypertensive patients. This dispersion measure is crucial for accurate medical research on cardiovascular risk factors.

Area of Science:

  • Ophthalmology
  • Cardiology
  • Medical Imaging

Background:

  • Retinal arterial and vein diameters correlate with cardiovascular health.
  • Measurement of retinal vessel diameters from ocular fundus images is a key indicator.
  • Dispersion in retinal vessel diameter measurements is often overlooked in clinical research.

Purpose of the Study:

  • To propose a method for evaluating how clinical covariables affect retinal arterial and vein diameter dispersion.
  • To assess if hypertension and medication levels influence retinal vessel diameter dispersion.
  • To investigate the relationship between smoking and retinal vessel diameter dispersion.

Main Methods:

  • Utilizing ocular fundus images for retinal vessel diameter measurement.
  • Applying a multivariate dispersion ordering, specifically the Hausdorff dispersion order.
  • Comparing dispersion levels across different patient groups based on clinical factors.

Main Results:

  • Higher dispersion in retinal vessel diameters was observed in individuals with long-standing hypertension.
  • Increased dispersion was noted in patients requiring two or more antihypertensive drugs.
  • Greater smoking levels appeared to be associated with lesser dispersion in vessel diameters.

Conclusions:

  • Dispersion of retinal vessel diameters is a significant factor in individuals with severe hypertension.
  • Accounting for dispersion in image analysis of retinal vessels enhances accuracy in medical research.
  • Homogeneous grouping based on dispersion analysis can lead to more reliable research outcomes.

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