Sensitivity Analysis of Left Atrial Wall Modeling Approaches and Inlet/Outlet Boundary Conditions in Fluid Simulations to Predict Thrombus Formation

Albors, Carlos; Mill, Jordi; Kjeldsberg, Henrik A.; Medel, David Viladés; Olivares, Andy L.; Valen‐Sendstad, Kristian; Cámara, Óscar

doi:10.1007/978-3-031-23443-9_17

Cited by 2 publications

(5 citation statements)

References 19 publications

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“…Despite PV flow rates not being patientderived, the MV orifice's velocity curve closely resembled ultrasound measurements, showing similar maxima and a diminished A-wave, characteristic of AF patients. 93 Furthermore, the measured mean and maximum velocity magnitudes at the PVs (13 and 70 cm/s, respectively) corresponded to realistic values. 85,94 Regarding the split of the PV flow, we assumed an equal distribution of the velocity in the PVs, as opposed to an equal flow rate split that previously aligned well with MRI measurements.…”

Section: Discussionmentioning

confidence: 52%

“…Lastly, we did not have access to patient‐specific flow rates or flow split. Despite PV flow rates not being patient‐derived, the MV orifice's velocity curve closely resembled ultrasound measurements, showing similar maxima and a diminished A‐wave, characteristic of AF patients 93 . Furthermore, the measured mean and maximum velocity magnitudes at the PVs (13 and 70 cm/s, respectively) corresponded to realistic values 85,94 .…”

Section: Discussionmentioning

confidence: 58%

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Impact of left atrial wall motion assumptions in fluid simulations on proposed predictors of thrombus formation

Kjeldsberg,

Albors,

Mill

et al. 2024

Numer Methods Biomed Eng

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Atrial fibrillation (AF) poses a significant risk of stroke due to thrombus formation, which primarily occurs in the left atrial appendage (LAA). Medical image‐based computational fluid dynamics (CFD) simulations can provide valuable insight into patient‐specific hemodynamics and could potentially enhance personalized assessment of thrombus risk. However, the importance of accurately representing the left atrial (LA) wall dynamics has not been fully resolved. In this study, we compared four modeling scenarios; rigid walls, a generic wall motion based on a reference motion, a semi‐generic wall motion based on patient‐specific motion, and patient‐specific wall motion based on medical images. We considered a LA geometry acquired from 4D computed tomography during AF, systematically performed convergence tests to assess the numerical accuracy of our solution strategy, and quantified the differences between the four approaches. The results revealed that wall motion had no discernible impact on LA cavity hemodynamics, nor on the markers that indicate thrombus formation. However, the flow patterns within the LAA deviated significantly in the rigid model, indicating that the assumption of rigid walls may lead to errors in the estimated risk factors. In contrast, the generic, semi‐generic, and patient‐specific cases were qualitatively similar. The results highlight the crucial role of wall motion on hemodynamics and predictors of thrombus formation, and also demonstrate the potential of using a generic motion model as a surrogate for the more complex patient‐specific motion. While the present study considered a single case, the employed CFD framework is entirely open‐source and designed for adaptability, allowing for integration of additional models and generic motions.

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Section: Discussionmentioning

confidence: 52%

Section: Discussionmentioning

confidence: 58%

Impact of left atrial wall motion assumptions in fluid simulations on proposed predictors of thrombus formation

Kjeldsberg,

Albors,

Mill

et al. 2024

Numer Methods Biomed Eng

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“…Variations in anticoagulant therapy and CT scan acquisition timings across the cohort may impact DRT prediction. Furthermore, the representation of LA wall movement using a spring-based dynamic mesh, based on the passive longitudinal movement observed at the mitral valve, may not fully capture the importance of 4D LA wall motion in hemodynamics and in-silico indices behavior, as highlighted by a recent sensitivity analysis on wall motion [28]. Although CT scans are commonly used for pre- and intra-LAAO planning and follow-ups, dynamic CTs providing heart motion information are not routinely included in patient protocols within the clinical routine.…”

Section: Discussionmentioning

confidence: 99%

“…The simulation was run for two cardiac cycles, with 88 steps per beat and a Δ t = 0.01 s , in accordance with the patient’s heart rate (HR). Moreover, a half-scaled function representing the mitral valve annulus displacement, from Veronesi et al [37], with a peak displacement of 4 mm was set as in [28]. Then, LA wall motion diffusion was estimated with a spring-based dynamic mesh approach within the CFD solver [23].…”

Section: In-silico Simulationsmentioning

confidence: 99%

“…Computational fluid dynamics (CFD) is a powerful tool that can help to fill the gap in understanding LA and LAA morphology and complex hemodynamics characteristics. The hemodynamics of the left atria in patients with atrial fibrillation has been well-studied and -documented in the CFD field, with sensitivity analysis (for a recent 8literature review, see Mill et al (2021) [23]) establishing best modeling practices for patient-specific simulations [24], analysing rheological conditions [25], input/output boundary conditions, inclusion of wall motion [26–28], among other relevant factors. Nevertheless, despite the increasing number of LAAO interventions, only a limited number of in-silico studies explicitly incorporate LAAO devices in fluid simulations.…”

Section: Introductionmentioning

confidence: 99%

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Impact of occluder device configurations in in-silico left atrial hemodynamics for the analysis of device-related thrombus

Albors,

Mill,

Olivares

et al. 2024

Preprint

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Left atrial appendage occlusion devices (LAAO) are a feasible alternative for non-valvular atrial fibrillation (AF) patients at high risk of thromboembolic stroke and contraindication to antithrombotic therapies. However, optimal LAAO device configurations (i.e., size, type, location) remain unstandardized due to the large anatomical variability of the left atrial appendage (LAA) morphology, leading to a 4-6% incidence of device-related thrombus (DRT). In-silico simulations have the potential to assess DRT risk and identify the key factors, such as suboptimal device positioning. This work presents fluid simulation results computed on 20 patient-specific left atrial geometries, analysing different commercially available LAAO occluders, including plug-type and pacifier-type devices. In addition, we explored two distinct device positions: 1) the real post-LAAO intervention configuration derived from follow-up imaging; and 2) one covering the pulmonary ridge if it was not achieved during the implantation (13 out of 20). In total, 33 different configurations were analysed. In-silico indices indicating high risk of DRT (e.g., low blood flow velocities and flow complexity around the device) were combined with particle deposition analysis based on a discrete phase model. The obtained results revealed that covering the pulmonary ridge with the LAAO device may be one of the key factors to prevent DRT. Moreover, disk-based devices exhibited enhanced adaptability to various LAA morphologies and, generally, demonstrated a lower risk of abnormal events after LAAO implantation.

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Sensitivity Analysis of Left Atrial Wall Modeling Approaches and Inlet/Outlet Boundary Conditions in Fluid Simulations to Predict Thrombus Formation

Cited by 2 publications

References 19 publications

Impact of left atrial wall motion assumptions in fluid simulations on proposed predictors of thrombus formation

Impact of left atrial wall motion assumptions in fluid simulations on proposed predictors of thrombus formation

Impact of occluder device configurations in in-silico left atrial hemodynamics for the analysis of device-related thrombus

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