A fully automated artificial intelligence-driven software for planning of transcatheter aortic valve replacement.

BACKGROUND: Transcatheter aortic valve replacement (TAVR) is increasingly performed for the treatment of aortic stenosis. Computed tomography (CT) analysis is essential for pre-procedural planning. Currently available software packages for TAVR planning require substantial human interaction. We describe development and validation of an artificial intelligence (AI) powered software to automatically rend anatomical measurements and other information required for TAVR planning and implantation. METHODS: Automated measurements from 100 CTs were compared to measurements from three expert clinicians and TAVR operators using commercially available software packages. Correlation coefficients and mean differences were calculated to assess precision and accuracy. RESULTS: AI-generated annular measurements had excellent agreements with manual measurements by expert operators yielding correlation coefficients of 0.97 for both perimeter and area. There was no relevant bias with a mean difference of -0.07 mm and - 1.4 mm2 for perimeter and area, respectively. For the ascending aorta measured 5 cm above the annular plane, correlation coefficient was 0.95 and mean difference was 1.4 mm. Instruction for use-based sizing yielded agreement with the effective implant size in 87-88 % of patients for self-expanding valves (perimeter-based sizing) and in 88 % for balloon-expandable valves (area-based sizing). CONCLUSIONS: A fully automated software enables accurate and precise anatomical segmentation and measurements required for TAVR planning without human interaction and with high reliability.

In vitro investigation of the blood flow downstream of a 3D-printed aortic valve.

The hemodynamics in the aorta as well as the durability of aortic valve prostheses vary greatly between different types of devices. Although placement and sizing of surgical aortic valve prostheses are excellent, the valve geometry of common devices cannot be customized to fit the patient's anatomy perfectly. Similarly, transcatheter aortic valve implantation (TAVI) devices are not customizable and may be orientated unfavorably during implantation. Imperfect fit of an aortic valve prosthesis may result in suboptimal performance and in some cases the need for additional surgery. Leveraging the advent of precision, multi-material 3D-printing, a bioinspired silicone aortic valve was developed. The manufacturing technique makes it fully customizable and significantly cheaper to develop and produce than common prostheses. In this study, we assess the hemodynamic performance of such a 3D-printed aortic valve and compare it to two TAVI devices as well as to a severely stenosed valve. We investigate the blood flow distal to the valve in an anatomically accurate, compliant aorta model via three-dimensional particle tracking velocimetry measurements. Our results demonstrate that the 3D-printed aortic valve induces flow patterns and topology compatible with the TAVI valves and showing similarity to healthy aortic blood flow. Compared to the stenosis, the 3D-printed aortic valve reduces turbulent kinetic energy levels and irreversible energy losses by over 75%, reaching values compatible with healthy subjects and conventional TAVIs. Our study substantiates that the 3D-printed heart valve displays a hemodynamic performance similar to established devices and underscores its potential for driving innovation towards patient specific valve prostheses.