Estimation of Diabetic Retinal Microaneurysm Perfusion Parameters Based on Computational Fluid Dynamics Modeling of

Miguel O Bernabeu1, Yang Lu2, Omar Abu-Qamar2

  • 1Centre for Medical Informatics, Usher Institute, The University of Edinburgh, Edinburgh, United Kingdom.

Frontiers in Physiology
|September 25, 2018
PubMed

Insights

Diabetic retinopathy (DR) microaneurysms (MAs) structural features correlate with blood flow dynamics. Computational Fluid Dynamics (CFD) analysis of MA morphology can predict clot likelihood, aiding DR management.

Area of Science:

  • Ophthalmology
  • Biomedical Engineering
  • Computational Science

Background:

  • Diabetic retinopathy (DR) is a major cause of vision loss, with microaneurysms (MAs) being early indicators.
  • MA leakage contributes to retinal thickening and vision impairment.
  • Perfusion parameters like shear rate (SR) and wall shear stress (WSS) are crucial in vascular health but their relation to MAs is unclear.

Purpose of the Study:

  • To investigate the association between microaneurysm (MA) structural characteristics and vascular perfusion parameters.
  • To explore the utility of Computational Fluid Dynamics (CFD) in analyzing MA morphology and estimating perfusion attributes.

Main Methods:

  • High-resolution adaptive optics scanning laser ophthalmoscopy (AOSLO) images were used to obtain MA structural data.
  • Computational Fluid Dynamics (CFD) simulations, utilizing the HemeLB flow solver, were performed on AOSLO-derived MA models.
  • Simulations were run on both hospital-based and high-performance computing resources.

Main Results:

  • Wall shear stress (WSS) was found to be lowest in MA regions distant from feeding vessels.
  • Low shear rate (SR) areas correlated with clot location in saccular MAs.
  • MA morphology and CFD-derived perfusion parameters show potential for predicting clot presence.

Conclusions:

  • The structural features of diabetic retinopathy microaneurysms are linked to specific vascular perfusion parameters.
  • CFD analysis of MA morphology offers a promising method for estimating perfusion and predicting clot formation.
  • These findings may enhance the assessment of DR severity and patient risk stratification.

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