About this Book

In this thesis, the atrial blood flow was modeled using computational fluid dynamics (CFD) to better understand atrial hemodynamics and blood stasis. Atrial hemodynamics and especially stasis are of interest since thrombi can form in the left atrium, travel with the blood stream to the brain, and cause strokes. To model atrial blood flow in a personalized manner, several modeling assumptions and choices need to be made, for example how to model the motion of the atrial wall. There are different approaches to estimate stasis; however, there is no standard method. While it is known that in patients with atrial fibrillation (AF), the stroke risk is increased, the exact mechanisms for this are not fully understood, especially in patients that are in sinus rhythm most of the time. One approach to reduce the stroke risk is to occlude the left atrial appendage (LAA). However, this has not been evaluated for patients in an early phase of AF.

The aim of this thesis was to enhance our understanding of left atrial hemodynamics. For this, the blood flow in the left atrium was simulated using CFD based on time-resolved CT images, including the patient-specific geometry and wall motion. In this thesis, different stasis markers are investigated and a new method to quantify atrial hemodynamics was developed, splitting the atrial blood flow into 6 components. Additionally, virtual LAA occlusion was investigated to see how it impacts atrial hemodynamics during sinus rhythm.

In this thesis, the atrial blood flow and stasis in 21 paroxysmal AF patients during sinus rhythm were compared to 8 controls. The wall motion tracked from time-resolved CT that was used in the CFD simulations showed similar flow rates as measurements from 4D flow MRI. All stasis markers investigated showed higher stasis in AF patients during sinus rhythm compared to the controls. Atrial flow component analysis revealed how blood travels through the left atrium. In the control group, the blood flow was dominated by components characterizing a direct path through the LA. In the patients with AF, however, an increased amount of blood stays in the LA for more than two heart beats and more blood flows back to the lungs. Virtual LAAO showed a reduction of stasis, for some individuals to similar levels as the control group. For others, stasis was reduced but still high, and stasis was located close to the occlusion device. This could indicate an increased risk for device-related thrombi.

In conclusion, this thesis contributes to our understanding of the atrial blood flow. Using CT-based CFD simulations, we could show that stasis is increased in AF patients during sinus rhythm. In the future, adding patient-specific stasis assessment could improve decision-making to prescribe anticoagulants and thus reduce the incidence of cardioembolic strokes.