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Hemodynamic variables in aneurysms are associated with thrombotic risk in children with Kawasaki disease
Noelia Grande Gutierrez1, Mathew Mathew2, Brian W McCrindle2
1Department of Mechanical Engineering, Stanford University, USA.
Insights
Computational fluid dynamics in coronary artery aneurysms (CAAs) can better predict thrombosis risk in Kawasaki disease (KD) patients than current size-based metrics. Hemodynamic analysis offers improved patient stratification for better long-term management.
Area of Science:
- Cardiovascular Medicine
- Biomedical Engineering
- Computational Fluid Dynamics
Background:
- Coronary artery aneurysms (CAAs) in Kawasaki disease (KD) pose a significant risk of thrombosis.
- Current guidelines use maximum diameter (Dmax) or Z-score for anticoagulation therapy initiation.
- There is a need for more accurate thrombotic risk stratification methods in KD patients with CAAs.
Purpose of the Study:
- To investigate the efficacy of hemodynamic variables derived from computational simulations in stratifying thrombotic risk in KD patients with CAAs.
- To compare the predictive performance of hemodynamic factors against traditional anatomical metrics (Dmax, Z-score).
Main Methods:
- Retrospective study of ten KD patients with CAAs, including five with thrombosis.
- Patient-specific anatomical models constructed from cardiac MRI.
- Computational hemodynamic simulations using SimVascular with pulsatile flow and deformable walls.
- Derivation of hemodynamic parameters: time-averaged wall shear stress (TAWSS), low wall shear stress exposure, oscillatory shear index (OSI), and flow residence time.
Main Results:
- Lower TAWSS and larger low wall shear stress exposure were observed in CAAs with thrombosis.
- Increased flow residence time was significantly associated with confirmed thrombosis.
- Hemodynamic variables demonstrated higher sensitivity and specificity for thrombotic risk assessment compared to Dmax and Z-score.
- No significant differences in OSI, Dmax, or Z-score were found between patients with and without thrombosis.
Conclusions:
- Non-invasively derived hemodynamic variables from simulations offer superior thrombotic risk stratification for KD patients with CAAs.
- These findings suggest a potential improvement over current diameter-based metrics for clinical decision-making.
- Hemodynamic analysis may facilitate more effective long-term management of KD patients with persistent CAAs.
Background:
Thrombosis is a major adverse outcome associated with coronary artery aneurysms (CAAs) resulting from Kawasaki disease (KD). Clinical guidelines recommend initiation of anticoagulation therapy with maximum CAA diameter (Dmax) ≥8 mm or Z-score ≥ 10. Here, we investigate the role of aneurysm hemodynamics as a superior method for thrombotic risk stratification in KD patients.
Methods And Results:
We retrospectively studied ten KD patients with CAAs, including five patients who developed thrombosis. We constructed patient-specific anatomic models from cardiac magnetic resonance images and performed computational hemodynamic simulations using SimVascular. Our simulations incorporated pulsatile flow, deformable arterial walls and boundary conditions automatically tuned to match patient-specific arterial pressure and cardiac output. From simulation results, we derived local hemodynamic variables including time-averaged wall shear stress (TAWSS), low wall shear stress exposure, and oscillatory shear index (OSI). Local TAWSS was significantly lower in CAAs that developed thrombosis (1.2 ± 0.94 vs. 7.28 ± 9.77 dynes/cm2, p = 0.006) and the fraction of CAA surface area exposed to low wall shear stress was larger (0.69 ± 0.17 vs. 0.25 ± 0.26%, p = 0.005). Similarly, longer residence times were obtained in branches where thrombosis was confirmed (9.07 ± 6.26 vs. 2.05 ± 2.91 cycles, p = 0.004). No significant differences were found for OSI or anatomical measurements such us Dmax and Z-score. Assessment of thrombotic risk according to hemodynamic variables had higher sensitivity and specificity compared to standard clinical metrics (Dmax, Z-score).
Conclusions:
Hemodynamic variables can be obtained non-invasively via simulation and may provide improved thrombotic risk stratification compared to current diameter-based metrics, facilitating long-term clinical management of KD patients with persistent CAAs.
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