RESUMO
Objective: To develop a novel in vitro method for evaluating coronary artery ischemia using a combination of non-invasive coronary CT angiograms (CCTA) and 3D printing (FFR3D). Methods: Twenty eight patients with varying degrees of coronary artery disease who underwent non-invasive CCTA scans and invasive fractional flow reserve (FFR) of their epicardial coronary arteries were included in this study. Coronary arteries were segmented and reconstructed from CCTA scans using Mimics (Materialize). The segmented models were then 3D printed using a Carbon M1 3D printer with urethane methacrylate (UMA) family of rigid resins. Physiological coronary circulation was modeled in vitro as flow-dependent stenosis resistance in series with variable downstream resistance. A range of physiological flow rates (Q) were applied using a peristaltic steady flow pump and titrated with a flow sensor. The pressure drop (ΔP) and the pressure ratio (Pd/Pa) were assessed for patient-specific aortic pressure (Pa) and differing flow rates (Q) to evaluate FFR3D using the 3D printed model. Results: There was a good positive correlation (r = 0.87, p < 0.0001) between FFR3D and invasive FFR. Bland-Altman analysis revealed a good concordance between the FFR3D and invasive FFR values with a mean bias of 0.02 (limits of agreement: -0.14 to 0.18; p = 0.2). Conclusions: 3D printed patient-specific models can be used in a non-invasive in vitro environment to quantify coronary artery ischemia with good correlation and concordance to that of invasive FFR.
RESUMO
The primary mode of visualization during transcatheter procedures for structrural heart disease is fluoroscopy, which suffers from low contrast and lacks any depth perception, thus limiting the ability of an interventionalist to position a catheter accurately. This paper describes a new image guidance system by utilizing augmented reality to provide a 3D visual environment and quantitative feedback of the catheter's position within the heart of the patient. The real-time 3D position of the catheter is acquired via two fluoroscopic images taken at different angles, and a patient-specific 3D heart rendering is produced pre-operatively from a CT scan. The spine acts as a fiduciary land marker, allowing the position and orientation of the catheter within the heart to be fully registered. The automated registration method is based on Fourier transformation, and has a high success rate (100%), low registration error (0.42 mm), and clinically acceptable computational cost (1.22 second). The 3D renderings are displayed and updated on the augmented reality device (i.e., Microsoft HoloLens), which can provide pre-set views of various angles of the heart using voice-command. This new image-guidance system with augmented reality provides a better visualization to interventionalists and potentially assists them in understanding of complicated cases. Furthermore, this system coupled with the developed 3D printed models can serve as a training tool for the next generation of cardiac interventionalists.
