In silico modeling of patient-specific blood rheology in type 2 diabetes mellitus

Increased blood viscosity in type 2 diabetes mellitus (T2DM) is a risk factor for the development of insulin resis-tance and diabetes-related vascular complications; however, individuals with T2DM exhibit heterogeneous hemorheological properties, including cell deformation and aggregation. Using a multiscale red blood cell (RBC) model with key parameters derived from patient-specific data, we present a computational study of the rheological properties of blood from individual pa-tients with T2DM. Specifically, one key model parameter, which determines the shear stiffness of the RBC membrane (m) is informed by the high-shear-rate blood viscosity of patients with T2DM. At the same time, the other, which contributes to the strength of the RBC aggregation interaction (D0), is derived from the low-shear-rate blood viscosity of patients with T2DM. The T2DM RBC suspensions are simulated at different shear rates, and the predicted blood viscosity is compared with clinical laboratory-measured data. The results show that the blood viscosity obtained from clinical laboratories and computational sim-ulations are in agreement at both low and high shear rates. These quantitative simulation results demonstrate that the patient -specific model has truly learned the rheological behavior of T2DM blood by unifying the mechanical and aggregation factors of the RBCs, which provides an effective way to extract quantitative predictions of the rheological properties of the blood of indi-vidual patients with T2DM.

Automated summary

The rheological properties of blood from individual patients with type 2 diabetes mellitus (T2DM) were studied using a computational model. The model accurately predicted the blood viscosity at both low and high shear rates, showing agreement with clinical laboratory-measured data.