Non-invasive estimation of pressure drop across aortic coarctations: validation of 0D and 3D computational models within vivomeasurements

Abstract

PurposeBlood 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 ofΔP estimates derived non-invasively using patient-specific 0D and 3D deformable wall simulations.MethodsMedical 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.ResultsThe 0D simulations were extremely efficient (∼15 secs computation time) compared to 3D simulations (∼30 hrs computation time on a cluster). However, the 0DΔP 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 asΔP≥20 mmHg) with 76% accuracy and 3D simulations improved this to 88%.ConclusionOverall, 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.