FEops HEARTguide Patient-Specific Computational Simulations for WATCHMAN FLX Left Atrial Appendage Closure: A Retrospective Study.

computational modeling left atrial appendage closure

Journal

JACC. Advances
ISSN: 2772-963X
Titre abrégé: JACC Adv
Pays: United States
ID NLM: 9918419284106676

Informations de publication

Date de publication:
Dec 2022
Historique:
received: 21 06 2022
revised: 21 09 2022
accepted: 12 10 2022
medline: 30 11 2022
pubmed: 30 11 2022
entrez: 28 6 2024
Statut: epublish

Résumé

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. 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. 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. 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. 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.

Sections du résumé

Background UNASSIGNED
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 UNASSIGNED
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 UNASSIGNED
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 UNASSIGNED
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 UNASSIGNED
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.

Identifiants

pubmed: 38939468
doi: 10.1016/j.jacadv.2022.100139
pii: S2772-963X(22)00216-2
pmc: PMC11198077
doi:

Types de publication

Journal Article

Langues

eng

Pagination

100139

Informations de copyright

© 2022 The Authors.

Déclaration de conflit d'intérêts

Dr Vahl has received institutional funding to Columbia University Irving Medical Center from Boston Scientific, Edwards Lifesciences, JenaValve, Medtronic, and Siemens Healthineers; and has personally received consulting fees from Abbott Vascular, Boston Scientific, and Siemens Healthineers. Dr Sommer is a trainer for Boston Scientific’s Watchman device; is an investigator for the following Boston Scientific trials: OPTION and CHAMPION-AF; and is the National Principal Investigator on for two Gore trials: ASSURED and RELIEF. Dr Khalique is part of a corelab contracting with JenaValve, but has not received any direct compensation; has received consulting fees from Abbott Structural and Boston Scientific; and has received Speakers bureau fees from Edwards Lifesciences. Dr Hamid is part of a corelab contracting with JenaValve, but she has not received any direct compensation. Drs Bavo and De Beule are employees of FEops. Dr Hahn has received speaker fees from Abbot Vascular, Baylis Medical, Edwards Lifescience, and Philips Healthcare; institutional consulting contracts with no direct compensation for Abbott Structural, Edwards Lifesciences, Medtronic, Novartis, and Philips Healthcare; and equity with Navigate. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Auteurs

Lauren S Ranard (LS)

Structural Heart and Valve Center, NewYork-Presbyterian Hospital, Columbia University Irving Medical Center, New York, New York, USA.

Torsten P Vahl (TP)

Structural Heart and Valve Center, NewYork-Presbyterian Hospital, Columbia University Irving Medical Center, New York, New York, USA.

Robert Sommer (R)

Structural Heart and Valve Center, NewYork-Presbyterian Hospital, Columbia University Irving Medical Center, New York, New York, USA.

Vivian Ng (V)

Structural Heart and Valve Center, NewYork-Presbyterian Hospital, Columbia University Irving Medical Center, New York, New York, USA.

Jay Leb (J)

Structural Heart and Valve Center, NewYork-Presbyterian Hospital, Columbia University Irving Medical Center, New York, New York, USA.

Kyle Lehenbauer (K)

Structural Heart and Valve Center, NewYork-Presbyterian Hospital, Columbia University Irving Medical Center, New York, New York, USA.

Patita Sitticharoenchai (P)

Structural Heart and Valve Center, NewYork-Presbyterian Hospital, Columbia University Irving Medical Center, New York, New York, USA.

Omar Khalique (O)

Structural Heart and Valve Center, NewYork-Presbyterian Hospital, Columbia University Irving Medical Center, New York, New York, USA.

Nadira Hamid (N)

Structural Heart and Valve Center, NewYork-Presbyterian Hospital, Columbia University Irving Medical Center, New York, New York, USA.

Matthieu De Beule (M)

FEops NV, Ghent, Belgium.

Alessandra Bavo (A)

FEops NV, Ghent, Belgium.

Rebecca T Hahn (RT)

Structural Heart and Valve Center, NewYork-Presbyterian Hospital, Columbia University Irving Medical Center, New York, New York, USA.

Classifications MeSH