Predictive Model for Thrombus Formation After Transcatheter Valve Replacement

Abstract

Purpose-Leaflet thrombosis is a significant adverse event after transcatheter aortic valve (TAV) replacement (TAVR). The purpose of our study was to present a semi-empirical, mathematical model that links patient-specific anatomic, valve, and flow parameters to predict likelihood of leaflet thrombosis. Methods-The two main energy sources of neo-sinus (NS) washout after TAVR include the jet flow downstream of the TAV and NS geometric change in volume due to the leaflets opening and closing. Both are highly dependent on patient anatomic and hemodynamic factors. As rotation of blood flow is prevalent in both the sinus of Valsalva and then the NS, we adopted the vorticity flux or circulation (U) as a metric quantifying overall washout. Leaflet thrombus volumes were segmented based on hypo-attenuating leaflet thickening (HALT) in post-TAVR patient's gated computed tomography. U was assessed using dimensional scaling as well as computational fluid dynamics (CFD) respectively and correlated to the thrombosis volumes using sensitivity and specificity analysis. Results-U in the NS, that accounted for patient flow and anatomic conditions derived from scaling arguments significantly better predicted the occurrence of leaflet thrombus than CFD derived measures such as stasis volumes or wall shear stress. Given results from the six patient datasets considered herein, a threshold U value of 28.0 yielded a sensitivity and specificity of 100% where patients with Gamma < 28 developed valve thrombosis. A 10% error in measurements of all variables can bring the sensitivity specificity down to 87%. Conclusion-A predictive model relating likelihood of valve thrombosis using U in the NS was developed with promising sensitivity and specificity. With further studies and improvements, this predictive technology may lead to alerting physicians on the risk for thrombus formation following TAVR.

Long-term prognostic impact of paravalvular leakage on coronary artery disease requires patient-specific quantification of hemodynamics

“…The blood flow inside the coronary arteries was simulated using similar 3-D FSI set-up as described in our previous works 18 , 19 , using open-source FOAM-Extend library 64 . The transcatheter aortic valve (TAV) frame and aortic wall are assumed to be rigid during diastole 65 , 66 . All details about governing equations, FSI method and modeling were presented in Supplementary Materials.…”

“…However, we acknowledge that this a limitation of our study and we addressed this in the limitation section. Yet, it is worth mentioning that in the absence of essential characterization of patient-specific material properties required for FSI simulation of valve flow (which is the case in all ongoing FSI simulations 69 , 72 , 73 ), the results of FSI simulation could be an incorrect representative of the flow 66 . Therefore, whether the FSI simulation of the valve and aorta with such limitations improves the results is still debatable especially if the end goal is to provide a patient-specific framework 74 .…”

A Model of Fluid-Structure and Biochemical Interactions for Applications to Subclinical Leaflet Thrombosis

“…A common finding in CFD simulations is the presence of stagnant regions in the aortic sinus, in which blood clots are thought to form. Hatoum et al [17] combined a CFD model of flow through patient specific geometry post-TAVR with a reduced order model that predicted thrombus growth based on the wall shear stress and percent stasis volume measurements. While they were able to determine a correlation between circulation and amount of thrombosis, they concluded that finer flow metrics or FSI analysis are needed to fully predict thrombosis.…”

The impact of local blood residence time in neo-sinus on post transcatheter aortic valve replacement subclinical leaflet thrombosis—a commentary

“…SLT is a complicated phenomenon that depends on numerous indicators, such as valve and root anatomy [ 2 ], haemodynamics [ 3 , 4 ], age of the patient [ 5 ], medication history [ 5 ], valve type (bicuspid or tricuspid), and valve size [ 6 ]. For instance, we would like to note that according to our most recent dimensional analysis study, we showed that the coronary artery ostia locations, mean jet velocity, area of the neo-sinus opening, cross-sectional area of neo-sinus, ejection time and flow separated area (area between the valve stent and the aortic wall) significantly impact the risk of SLT [ 2 ]. We showed that all these parameters can be grouped into 1 nondimensional parameter called normalized circulation.…”

“…We showed that all these parameters can be grouped into 1 nondimensional parameter called normalized circulation. Normalized circulation is a fast predictor of the risk of thrombus formation [ 2 ]. The method we have developed can be applied prior to the transcatheter aortic valve replacement and assist in finding the optimum replacement location and expansion degree to minimize the risk of SLT [ 2 ].…”