Prosthetic venous valve patient selection by validated physics-based computational models

Background: There is significant interest in a venous prosthesis to replace insufficient valves. The aim of the current study was to select the patients with hemodynamic conditions most likely to benefit from a valve implant. The hypothesis is that the venous valve prosthesis is most suitable for patients with significant reflux, such as in chronic venous insufficiency (CVI), right heart hypertrophy (RHH), and right heart failure (RHF). Conversely, a prosthetic valve is likely to be of least benefit for deep venous thrombosis (DVT) patients with low flow. Methods: To address this hypothesis, fully coupled fluid and solid mechanics computational models were developed and validated in five acute canine implants. The animal-validated simulations were then carried out for the CVI, RHH, RHF, and DVT patients based on literature hemodynamic data. A mechanical stress ratio of leaflet wall stress to fluid wall shear stress was defined to combine the effects of both fluid mechanics and solid mechanics on leaflet function, for which a lower stress ratio is hemodynamically desirable. Results: The simulation results of mean valve flow velocity and percentage valve opening were found to be within 10% of the measurements in canines. The simulations show that the patients in the CVI classes 4 to 6, RHH patients, and RHF patients may have a significant reduction in stress ratio with virtual implant of a prosthetic valve. The DVT patient simulations demonstrate a minimal reduction in the stress ratio. After thrombus removal where flow is restored, however, the prosthetic valve may be helpful for post-thrombotic patients. Conclusions: For patient selections of the venous valve prosthesis, the most suitable patients are the CVI classes 4 to 6, RHH, and RHF patients. The least suitable patients are the DVT patients because a valve is not effective under low flow conditions. The present study demonstrates a physics based approach to patient selection that can be tested in future clinical trials.