Why the study?
While 3D-TEE is the primary imaging tool for left atrial appendage closure planning, the utility of CCTA and patient-specific computational models is unknown.
Does FEops HEARTguide computational modeling accurately predict device size, location, and compression for WATCHMAN FLX left atrial appendage closure compared to 3D-TEE?
Does FEops HEARTguide computational modeling accurately predict device size, location, and compression for WATCHMAN FLX left atrial appendage closure compared to 3D-TEE?
FEops HEARTguide computational modeling using CCTA accurately predicts WATCHMAN FLX device size and positioning, correlating excellently with intraprocedural 3D-TEE.
May support CCTA-based planning for WATCHMAN FLX; leaves open prospective outcome benefits versus 3D-TEE.
Background: Three-dimensional transesophageal echocardiography (3D-TEE) is the primary imaging tool for left atrial appendage closure planning. The utility of cardiac computed tomography angiography (CCTA) and patient-specific computational models is unknown. Objectives: The purpose of this study was to evaluate the accuracy of the FEops HEARTguide patient-specific computational modeling in predicting appropriate device size, location, and compression of the WATCHMAN FLX compared to intraprocedural 3D-TEE. Methods: Patients with both preprocedural and postprocedural CCTA and 3D-TEE imaging of the LAA who received a WATCHMAN FLX left atrial appendage closure device were studied (n = 22). The FEops HEARTguide platform used baseline CCTA imaging to generate a prediction of device size(s), device position(s), and device dimensions. Blinded (without knowledge of implanted device size/position) and unblinded (implant device size/position disclosed) simulations were evaluated. Results: In 16 (72.7%) patients, the blind simulation predicted the final implanted device size. In these patients, the 3D-TEE measurements were not significantly different and had excellent correlation (Pearson correlation coefficient (r) ≥ 0.90). No patients had peridevice leak after device implant. In the 6 patients for whom the model did not predict the implanted device size, a larger device size was ultimately implanted as per operator preference. The model measurements of the unblinded patients demonstrated excellent correlation with 3D-TEE. Conclusions: This is the first study to demonstrate that the FEops HEARTguide model accurately predicts WATCHMAN FLX device implantation characteristics. Future studies are needed to evaluate if computational modeling can improve confidence in sizing, positioning, and compression of the device without compromising technical success.
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Ranard et al. (2022) studied this question.
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