Patient-Specific Computational Analysis of Hemodynamics in Adult Pulmonary Hypertension

Pulmonary hypertension (PH) is a progressive disease characterized by elevated pressure and vascular resistance in the pulmonary arteries. Nearly 250,000 hospitalizations occur annually in the US with PH as the primary or secondary condition. A definitive diagnosis of PH requires right heart catheterization (RHC) in addition to a chest computed tomography, a walking test, and others. While RHC is the gold standard for diagnosing PH, it is invasive and posseses inherent risks and contraindications. In this work, we characterized the patient-specific pulmonary hemodynamics in silico for diverse PH WHO groups. We grouped patients on the basis of mean pulmonary arterial pressure (mPAP) into three disease severity groups: at-risk (18mmHg <= mPAP<25mmHg, denoted with A), mild (25mmHg <= mPAP<40mmHg, denoted with M), and severe (mPAP >= 40mmHg, denoted with S). The pulsatile flow hemodynamics was simulated by evaluating the three-dimensional Navier-Stokes system of equations using a flow solver developed by customizing OpenFOAM libraries (v5.0, The OpenFOAM Foundation). Quasi patient-specific boundary conditions were implemented using a Womersley inlet velocity profile and transient resistance outflow conditions. Hemodynamic indices such as spatially averaged wall shear stress (SAWSS), wall shear stress gradient (WSSG), time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), and relative residence time (RRT), were evaluated along with the clinical metrics pulmonary vascular resistance (PVR), stroke volume (SV) and compliance (C), to assess possible spatiotemporal correlations. We observed statistically significant decreases in SAWSS, WSSG, and TAWSS, and increases in OSI and RRT with disease severity. PVR was moderately correlated with SAWSS and RRT at the mid-notch stage of the cardiac cycle when these indices were computed using the global pulmonary arterial geometry. These results are promising in the context of a long-term goal of identifying computational biomarkers that can serve as surrogates for invasive diagnostic protocols of PH.

Automated summary

Pulmonary hypertension is a progressive disease that requires multiple tests for diagnosis, with right heart catheterization being the gold standard. Hemodynamic indices show significant changes as the disease progresses. The study aims to identify computational biomarkers as non-invasive alternatives for diagnosing PH.