Hemodynamic characterization of spontaneous isolated superior mesenteric artery dissection revealed by patient-specific computational fluid dynamics.

Background: Spontaneous isolated superior mesenteric artery dissection (SISMAD) is a rare but potentially lethal vascular emergency with unclear pathogenesis. While hemodynamic forces are implicated in its development, current understanding remains limited by the lack of patient-specific data. This study aimed to characterize the detailed hemodynamic environment in SISMAD using patient-specific computational fluid dynamics modeling.

Results: Analysis of a three-dimensional model reconstructed from computed tomography angiography of a Yun Type I SISMAD revealed complex flow patterns with marked hemodynamic differences between the true lumen (TL) and false lumen (FL). The TL exhibited high-velocity flow concentrated near the entry tear and significantly elevated wall shear stress (WSS) and time-averaged wall shear stress (TAWSS) along the intimal flap. In contrast, the FL demonstrated markedly lower velocities, regions of flow stasis, and low WSS. A substantial pressure gradient existed across the intimal flap, with higher pressure in the TL compared to the FL. The FL also showed significantly higher oscillatory shear index (OSI) values, often exceeding 0.4 with a peak of 0.45. These findings provide quantitative confirmation of the theorized hemodynamic forces contributing to dissection progression and potential thrombosis formation, particularly the pro-thrombotic environment within the FL.

Conclusions: Patient-specific computational modeling reveals a complex and heterogeneous hemodynamic environment within the dissected superior mesenteric artery. The high-velocity flow, elevated WSS, and TAWSS in the TL may contribute to flap instability and inflammation, while the low-flow, stagnant conditions, low WSS, and high OSI in the FL likely promote thrombogenesis. This patient-specific approach provides valuable mechanistic insights into SISMAD pathophysiology and demonstrates potential for personalized risk assessment and data-driven treatment planning in this rare but serious vascular condition.