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

Zweck: Blood pressure gradient ($\Delta P$) 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 $\Delta P$ estimates derived non-invasively using patient-specific $0\text{D}$ and $3\text{D}$ deformable wall simulations.

Methods: Medical imaging and routine clinical measurements were used to create patient-specific models of patients with CoA ($N=17$). $0\text{D}$ simulations were performed first and used to tune boundary conditions and initialize $3\text{D}$ simulations. $\Delta P$ across the CoA estimated using both $0\text{D}$ and $3\text{D}$ simulations were compared to invasive catheter-based pressure measurements for validation.

Results: The $0\text{D}$ simulations were extremely efficient (~15 secs computation time) compared to $3\text{D}$ simulations (~30 hrs computation time on a cluster). However, the $0\text{D}$ $\Delta P$ estimates, unsurprisingly, had larger mean errors when compared to catheterization than $3\text{D}$ estimates (12.1 ± 9.9 mmHg vs 5.3 ± 5.4 mmHg). In particular, the $0\text{D}$ model performance degraded in cases where the CoA was adjacent to a bifurcation. The $0\text{D}$ model classified patients with severe CoA requiring intervention (defined as $\Delta P\ge 20$ mmHg) with 76% accuracy and $3\text{D}$ simulations improved this to 88%.

Conclusion: Overall, a combined approach, using $0\text{D}$ models to efficiently tune and launch $3\text{D}$ models, offers the best combination of speed and accuracy for non-invasive classification of CoA severity.