Umbilical artery thrombosis simulation applied to investigate the hemodynamic effects of umbilical coiling on thrombus progression

Umbilical artery thrombosis (UAT), a catastrophic obstetric complication, is strongly associated with adverse fetal outcomes, yet its hemodynamic drivers remain poorly understood. Therefore, the present study aims to develop a computational model of UAT and thus investigate the hemodynamic effects of umbilical coiling on thrombus progression. For this purpose, first, the parametric geometrical models of umbilical artery with different umbilical coiling index (UCI) were constructed based on the ultrasound-measured data. Subsequently, hemodynamic simulations, including blood flow, platelet activation, coagulant generation, and bound platelet formation, were conducted by solving the convection–diffusion–reaction equations to mimic thrombus growth in the models with different UCI. Results demonstrated that thrombi propagated radially inward in spiral patterns, which progressively induced lumen narrowing, accelerated flow velocity, and increased flow resistance. More specifically, hypocoiling condition induced the most severe UAT, with an about fourfold increase in flow resistance compared to threefold and twofold increases in the normal coiling and hypercoiling models, respectively. Moreover, time-averaged wall shear stress inversely correlated with thrombosis, with hypocoiling exhibiting the lowest wall shear stress and the most extensive coagulant accumulation, collectively accelerating thrombosis. Besides, normal physiological flow velocities suppressed thrombus formation across all models, revealing that pathological flow reduction was a critical trigger of UAT. These findings suggest that hypocoiling condition would amplify UAT risk, especially under low-flow condition, highlighting the necessity for the integrated prenatal monitoring of both blood flow and UCI. This computational framework advances the insights into UAT pathogenesis and offers a potential direction for stratifying UAT risk in clinical settings.