Predictive modelling of thrombus formation in diabetic retinal microaneurysms

Abstract

Microaneurysms (MAs) are one of the earliest clinically visible signs of diabetic retinopathy (DR). Vision can be reduced at any stage of DR by MAs, which may enlarge, rupture and leak fluid into the neural retina. Recent advances in ophthalmic imaging techniques enable reconstruction of the geometries of MAs and quantification of the corresponding haemodynamic metrics, such as shear rate and wall shear stress, but there is lack of computational models that can predict thrombus formation in individual MAs. In this study, we couple a particle model to a continuum model to simulate the platelet aggregation in MAs with different shapes. Our simulation results show that under a physiologically relevant blood flow rate, thrombosis is more pronounced in saccular-shaped MAs than fusiform-shaped MAs, in agreement with recent clinical findings. Our model predictions of the size and shape of the thrombi in MAs are consistent with experimental observations, suggesting that our model is capable of predicting the formation of thrombus for newly detected MAs. This is the first quantitative study of thrombosis in MAs through simulating platelet aggregation, and our results suggest that computational models can be used to predict initiation and development of intraluminal thrombus in MAs as well as provide insights into their role in the pathophysiology of DR.

Artificial intelligence velocimetry and microaneurysm-on-a-chip for three-dimensional analysis of blood flow in physiology and disease

“…7 D , and it shows a sudden drop of the wall shear stress from the parent vessel to the vessel wall of the MA. The wall shear stress continues to decrease in the region further away from the feeding channel, consistent with our 2D predictions and the findings reported from prior studies ( 42 , 59 , 65 ).…”

“…The AIV model can potentially be used to interpret the AOSLO images and predict the thrombus formation or rupture of MAs by monitoring the key hemodynamic metrics, such as wall shear stress, which is associated with the inflammation and dysfunction of endothelium cell, as well as the shear rate and the platelet residence time in the MAs, which can be used to predict the platelet activation and aggregation. We note that quantification of hemodynamic parameters from in vivo measurements in previous studies ( 42 , 59 , 65 ) were performed by using CFD models with assumed and general inflow and outflow boundary conditions since patient-specific inflow velocity was not readily available from in vivo images. The present AIV model, which does not require implementation of flow boundary conditions and mesh generation, can potentially learn the flow fields directly from in vivo video images and provide more accurate evaluation of hemodynamic indicators.…”

Computational investigation of blood cell transport in retinal microaneurysms

“…However, the underlying mechanism that initiates thrombosis in MAs is not clear. Data reported from clinical and computational studies [ 9 – 11 ] imply that thrombosis in MAs may be associated with their risk of leakage. Therefore, a detailed investigation of the mechanism of thrombus formation in MAs and their propensity to present in certain group of MAs could improve our understanding of the pathophysiology of MAs in DR.…”

Integrating blood cell mechanics, platelet adhesive dynamics and coagulation cascade for modelling thrombus formation in normal and diabetic blood

“…Numerous computational models [5][6][7][8][9][10][11][12][13][14][15] have been developed to address the underlying blood clotting processes and predict thrombus growth despite making assumptions and simplifications in the models, see reviews in [16,17]. It is worth noting that Xu et al [18] outlined a multiscale model that included macroscale dynamics of the blood flow using the continuum Navier-Stokes (NS) equations, and microscale interactions between platelets and the wall using a stochastic discrete cellular Potts model.…”