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

PurposeBlood 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 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.{Delta} P 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 0D{Delta} 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{Delta} P[≥] 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.