Benchtop Flow Stasis Quantification: In Vitro Methods and In Vivo Possibilities.

PURPOSE: Neo-sinus flow stasis has ben correlated with transcatheter heart valve (THV) thrombosis severity and occurrence. Standard benchtop flow field quantification techniques require optical access or modified prosthesis models that may not reflect the true nature of the original valve. En face and fluoroscopic videodensitometry enable visualization of washout in regions otherwise unviewable. METHODS: This study compares two in vitro methods of assessing flow stasis in scenarios with insufficient optical access for traditional techniques such as particle image velocimetry (PIV). A series of seven paired experiments were conducted using a previously described laser-enhanced video densitometry (LEVD) and fluoroscopic video densitometry (FVD). Both sets of experiments were analyzed to calculate washout time as a measure of flow stasis. A novel flow stasis measure termed contrast attenuation ratio (CAR) is proposed as a viable single measure of flow stasis obtainable from only a small number of cardiac cycles of in vitro or in vivo fluoroscopic data. Retrospective fluoroscopic datasets (n = 72) were analyzed to assess the feasibility of obtaining this metric from routine clinical practice and its ability to stratify results. RESULTS: Neo-sinus flow stasis calculated from in vitro fluoroscopy was well correlated with LEVD (r2 = 0.77, p = 0.009). The newly proposed CAR metric showed good agreement with the commonly used "washout time" measure of flow stasis (r2 = 0.91, p < 0.001) while allowing for assessment with incomplete or truncated data. As a proof of concept, CAR was measured in 72 consecutive retrospective fluoroscopic datasets. CAR averaged 10.6 ± 4.6% with a range of 1.5-20.3% in these patients. CONCLUSIONS: This study demonstrates two in vitro methods that can be used to assess relative flow stasis in otherwise optically inaccessible regions surrounding cardiac or vascular implants. In addition, the fluoroscopic benchtop technique was used to validate a metric that allows for extension to routine clinical fluoroscopy. This contrast attenuation ratio (CAR) metric was found to be both accurate and clinically obtainable, and potentially offers a new method for valve thrombosis risk stratification.

Non-invasive Estimation of Pressure Drop Across Aortic Coarctations: Validation of 0D and 3D Computational Models with In Vivo Measurements.

Blood pressure gradient ( Δ P ) across an aortic coarctation (CoA) is an important measurement to diagnose CoA severity and gauge treatment efficacy. Invasive cardiac catheterization is currently the gold-standard method for measuring blood pressure. The objective of this study was to evaluate the accuracy of Δ P estimates derived non-invasively using patient-specific 0D and 3D deformable wall simulations. Medical imaging and routine clinical measurements were used to create patient-specific models of patients with CoA (N = 17). 0D simulations were performed first and used to tune boundary conditions and initialize 3D simulations. Δ P across the CoA estimated using both 0D and 3D simulations were compared to invasive catheter-based pressure measurements for validation. The 0D simulations were extremely efficient ( ∼ 15 s computation time) compared to 3D simulations ( ∼ 30 h computation time on a cluster). However, the 0D Δ P estimates, unsurprisingly, had larger mean errors when compared to catheterization than 3D estimates (12.1 ± 9.9 mmHg vs 5.3 ± 5.4 mmHg). In particular, the 0D model performance degraded in cases where the CoA was adjacent to a bifurcation. The 0D model classified patients with severe CoA requiring intervention (defined as Δ P ≥ 20 mmHg) with 76% accuracy and 3D simulations improved this to 88%. Overall, a combined approach, using 0D models to efficiently tune and launch 3D models, offers the best combination of speed and accuracy for non-invasive classification of CoA severity.

Non-invasive estimation of pressure drop across aortic coarctations: validation of 0D and 3D computational models with in vivo measurements.

Purpose: Blood pressure gradient (ΔP) across an aortic coarctation (CoA) is an important measurement to diagnose CoA severity and gauge treatment efficacy. Invasive cardiac catheterization is currently the gold-standard method for measuring blood pressure. The objective of this study was to evaluate the accuracy of ΔP estimates derived non-invasively using patient-specific 0D and 3D deformable wall simulations. Methods: Medical imaging and routine clinical measurements were used to create patient-specific models of patients with CoA (N=17). 0D simulations were performed first and used to tune boundary conditions and initialize 3D simulations. ΔP across the CoA estimated using both 0D and 3D simulations were compared to invasive catheter-based pressure measurements for validation. Results: The 0D simulations were extremely efficient (~15 secs computation time) compared to 3D simulations (~30 hrs computation time on a cluster). However, the 0D ΔP estimates, unsurprisingly, had larger mean errors when compared to catheterization than 3D estimates (12.1 ± 9.9 mmHg vs 5.3 ± 5.4 mmHg). In particular, the 0D model performance degraded in cases where the CoA was adjacent to a bifurcation. The 0D model classified patients with severe CoA requiring intervention (defined as ΔP≥20 mmHg) with 76% accuracy and 3D simulations improved this to 88%. Conclusion: Overall, a combined approach, using 0D models to efficiently tune and launch 3D models, offers the best combination of speed and accuracy for non-invasive classification of CoA severity.