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Enabling Automated Device Size Selection for Transcatheter Aortic Valve Implantation.

ABSTRACT: The number of transcatheter aortic valve implantation (TAVI) procedures is expected to increase significantly in the coming years. Improving efficiency will become essential for experienced operators performing large TAVI volumes, while new operators will require training and may benefit from accurate support. In this work, we present a fast deep learning method that can predict aortic annulus perimeter and area automatically from aortic annular plane images. We propose a method combining two deep convolutional neural networks followed by a postprocessing step. The models were trained with 355 patients using modern deep learning techniques, and the method was evaluated on another 118 patients. The method was validated against an interoperator variability study of the same 118 patients. The differences between the manually obtained aortic annulus measurements and the automatic predictions were similar to the differences between two independent observers (paired diff. of 3.3?±?16.8?mm2 vs. 1.3?±?21.1?mm2 for the area and a paired diff. of 0.6?±?1.7?mm vs. 0.2?±?2.5?mm for the perimeter). The area and perimeter were used to retrieve the suggested prosthesis sizes for the Edwards Sapien 3 and the Medtronic Evolut device retrospectively. The automatically obtained device size selections accorded well with the device sizes selected by operator 1. The total analysis time from aortic annular plane to prosthesis size was below one second. This study showed that automated TAVI device size selection using the proposed method is fast, accurate, and reproducible. Comparison with the interobserver variability has shown the reliability of the strategy, and embedding this tool based on deep learning in the preoperative planning routine has the potential to increase the efficiency while ensuring accuracy.

SUBMITTER: Astudillo P

PROVIDER: S-EPMC6875021 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Enabling Automated Device Size Selection for Transcatheter Aortic Valve Implantation.

Astudillo Patricio P Mortier Peter P Bosmans Johan J De Backer Ole O de Jaegere Peter P De Beule Matthieu M Dambre Joni J

Journal of interventional cardiology 20191103

The number of transcatheter aortic valve implantation (TAVI) procedures is expected to increase significantly in the coming years. Improving efficiency will become essential for experienced operators performing large TAVI volumes, while new operators will require training and may benefit from accurate support. In this work, we present a fast deep learning method that can predict aortic annulus perimeter and area automatically from aortic annular plane images. We propose a method combining two de ...[more]

PMID: 31777469

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Project description:ObjectiveTranscatheter aortic valve implantation (TAVI) procedures are increasing rapidly, but the durability of tissue valve and periprocedural complications are not satisfactory. Immune reaction to the galactose-α-1,3 galactose β-1,4-N-acetylglucosamine (α-Gal) and conventional processing protocols of cardiac xenografts lead to calcification. Next-generation TAVI needs to be made with α-Gal-free xenografts by multiple anticalcification therapies to avoid immune rejection and enhance durability, and three-dimensional (3D) printing technology to improve the procedural safety.MethodsPorcine pericardia were decellularized and immunologically modified with α-galactosidase. The pericardia were treated by space filler, crosslinked with glutaraldehyde in organic solvent, and detoxified. The sheep-specific nitinol (nickel-titanium memory alloy) wire backbone was made from a 3D-printed model for ovine aortic root. After it passed the fitting test, we manufactured a self-expandable stented valve with the porcine pericardia mounted on the customized nitinol wire-based stent. After in vitro circulation using customized silicone aortic root, we performed TAVI in 9 sheep and obtained hemodynamic, radiological, immunohistopathological, and biochemical results.ResultsThe valve functioned well, with excellent stent fitting and good coronary flow under in vitro circulation. Sheep were sequentially scheduled to be humanely killed until 238 days after TAVI. Echocardiography and cardiac catheterization demonstrated good hemodynamic status and function of the aortic valve. The xenografts were well preserved without α-Gal immune reaction or calcification based on the immunological, radiographic, microscopic, and biochemical examinations.ConclusionsWe proved preclinical safety and efficacy for next-generation α-Gal-free TAVI with multiple anticalcification therapies and 3D-printing technology. A future clinical study is warranted based on these promising preclinical results.

Dataset Information

Enabling Automated Device Size Selection for Transcatheter Aortic Valve Implantation.

Publications

Enabling Automated Device Size Selection for Transcatheter Aortic Valve Implantation.

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