Numerical study of the risk of thrombosis in the left atrial appendage of chicken wing shape in atrial fibrillation

Yang, Jun; Song, Chentao; Ding, Huirong; Mu, Chunlai; Sun, Jian; Liu, Xiaohua

doi:10.3389/fcvm.2022.985674

Cited by 7 publications

(7 citation statements)

References 43 publications

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“…According to the literature, the chicken wing morphology is the least critical when compared to the other geometries, which reveals a link between the LAA morphology and the risk of clot formation [33,35,36,46]. However, varied quantifications of the risks can be found in the literature depending on the population that was analyzed; thus, it is difficult to generalize the significance of this association [5,49]. Notably, the Cauliflower shape appears to be related to an increased risk of thrombus formation [4,35,36].…”

Section: Discussionmentioning

confidence: 99%

Computational Flow Dynamic Analysis in Left Atrial Appendage Thrombus Formation Risk: A Review

et al. 2023

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Atrial fibrillation (AF) is a common cardiac arrhythmia characterized by irregular and rapid electrical activity in the atria, leading to ineffective contraction and poor blood flow. More than 90% of the left atrial (LA) thrombi that cause thromboembolic events during atrial fibrillation (AF) develop in the left atrial appendage (LAA). AF modifies the hemodynamics of the left atrium, which can result in thrombosis of the LAA, systemic embolism, and stroke. The current options to reduce thromboembolic events are oral anticoagulation, surgical LAA exclusion, or percutaneous LAA occlusion. However, the mechanism underlying thrombus development in the LAA remains poorly understood. Computational fluid dynamics (CFD) analysis can be used to better understand the risk of thrombus formation and subsequent embolic events. CFD enables the simulation and visualization of blood flow patterns within the heart, including complex structures such as the LAA. Using CFD, researchers can analyze the hemodynamics of blood flow, identify areas of stagnation or turbulence, and predict the risk of thrombus formation. The correlation between blood flow dynamics, atrial fibrillation, and the risk of stroke has been highlighted by CFD studies investigating the underlying mechanism of thrombus formation in the LAA. This review study intends to provide a comprehensive overview of the factors involved in thrombus formation and their implications for clinical practice by synthesizing the insights acquired from these CFD studies.

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Section: Discussionmentioning

confidence: 99%

Computational Flow Dynamic Analysis in Left Atrial Appendage Thrombus Formation Risk: A Review

et al. 2023

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“…In this study, only OSI and TAWSS were calculated to assess thrombosis risk as well as occurence of flow disturbances, even though a large number of potential parameters are discussed. These parameters have been selected as they are the most commonly used parameters, common thresholds for them are suggested, and they are applied to a wide range of applications, such as abdominal aortic aneurysms ( 31 , 32 ), left atrial appendage thrombus formation ( 33 ), and medical device thrombosis ( 34 ). Another commonly evaluated parameter, the relative residence time (RRT) can be calculated from TAWSS and OSI and was therefore considered redundant for the purpose of this study.…”

Section: Discussionmentioning

confidence: 99%

In-silico enhanced animal study of pulmonary artery pressure sensors: assessing hemodynamics using computational fluid dynamics

Brüning,

Yevtushenko,

Schlief

et al. 2023

Front. Cardiovasc. Med.

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To assess whether in-silico models can be used to predict the risk of thrombus formation in pulmonary artery pressure sensors (PAPS), a chronic animal study using pigs was conducted. Computed tomography (CT) data was acquired before and immediately after implantation, as well as one and three months after the implantation. Devices were implanted into 10 pigs, each one in the left and right pulmonary artery (PA), to reduce the required number of animal experiments. The implantation procedure aimed at facilitating optimal and non-optimal positioning of the devices to increase chances of thrombus formation. Eight devices were positioned non-optimally. Three devices were positioned in the main PA instead of the left and right PA. Pre-interventional PA geometries were reconstructed from the respective CT images, and the devices were virtually implanted at the exact sites and orientations indicated by the follow-up CT after one month. Transient intra-arterial hemodynamics were calculated using computational fluid dynamics. Volume flow rates were modelled specifically matching the animals body weights. Wall shear stresses (WSS) and oscillatory shear indices (OSI) before and after device implantation were compared. Simulations revealed no relevant changes in any investigated hemodynamic parameters due to device implantation. Even in cases, where devices were implanted in a non-optimal manner, no marked differences in hemodynamic parameters compared to devices implanted in an optimal position were found. Before implantation time and surface-averaged WSS was 2.35±0.47 Pa, whereas OSI was 0.08±0.17, respectively. Areas affected by low WSS magnitudes were 2.5±2.7 cm2, whereas the areas affected by high OSI were 18.1±6.3 cm2. After device implantation, WSS and OSI were 2.45±0.49 Pa and 0.08±0.16, respectively. Surface areas affected by low WSS and high OSI were 2.9±2.7 cm2, and 18.4±6.1 cm2, respectively. This in-silico study indicates that no clinically relevant differences in intra-arterial hemodynamics are occurring after device implantation, even at non-optimal positioning of the sensor. Simultaneously, no embolic events were observed, suggesting that the risk for thrombus formation after device implantation is low and independent of the sensor position.

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“…Consequently, in this paper, the risk of thrombus formation is represented by the RRT value. An escalated risk of thrombosis can be inferred from a higher RRT value [ 19 ].…”

Section: Methodsmentioning

confidence: 99%

“…This approach better illustrates the disparities in RT across different sections of the LA. Each cardiac cycle is 0.8 s in duration (comprising 37.5% of atrial diastolic period and 62.5% of atrial systolic period), culminating in a total computation duration of 8 s, with each time step measuring 0.005 s [ 19 ]. The convergence criterion is identified as the root mean square residual (RMS), and the residual target is set at 1 × 10 −5 .…”

Section: Methodsmentioning

confidence: 99%

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Research on the Internal Flow Field of Left Atrial Appendage and Stroke Risk Assessment with Different Blood Models

Yang,

Bai,

Song

et al. 2023

Bioengineering

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Extant clinical research has underscored that patients suffering from atrial fibrillation (AF) bear an elevated risk for stroke, predominantly driven by the formation of thrombus in the left atrial appendage (LAA). As such, accurately identifying those at an increased risk of thrombosis becomes paramount to facilitate timely and effective treatment. This study was designed to shed light on the mechanisms underlying thrombus formation in the LAA by employing three-dimensional (3D) left atrium (LA) models of AF patients, which were constructed based on Computed Tomography (CT) imaging. The distinct benefits of Computational Fluid Dynamics (CFD) were leveraged to simulate the blood flow field within the LA, using three distinct blood flow models, both under AF and sinus rhythm (SR) conditions. The potential risk of thrombus formation was evaluated by analyzing the Relative Residence Time (RRT) and Endothelial Cell Activation Potential (ECAP) values. The results gleaned from this study affirm that all three blood flow models align with extant clinical guidelines, thereby enabling an effective prediction of thrombosis risk. However, noteworthy differences emerged when comparing the intricacies of the flow field and thrombosis risk across the three models. The single-phase non-Newtonian blood flow model resulted in comparatively lower residence times for blood within the LA and lower values for the Oscillatory Shear Index (OSI), RRT, and ECAP within the LAA. These findings suggest a reduced thrombosis risk. Conversely, the two-phase non-Newtonian blood flow model exhibited a higher residence time for blood and elevated RRT value within the LAA, suggesting an increased risk for thrombosis.

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Numerical study of the risk of thrombosis in the left atrial appendage of chicken wing shape in atrial fibrillation

Cited by 7 publications

References 43 publications

Computational Flow Dynamic Analysis in Left Atrial Appendage Thrombus Formation Risk: A Review

Computational Flow Dynamic Analysis in Left Atrial Appendage Thrombus Formation Risk: A Review

In-silico enhanced animal study of pulmonary artery pressure sensors: assessing hemodynamics using computational fluid dynamics

Research on the Internal Flow Field of Left Atrial Appendage and Stroke Risk Assessment with Different Blood Models

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