Personalized Analysis of Left Atrial Blood Flow through Computational Modeling

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.