Chronic thromboembolic pulmonary hypertension (CTEPH) develops due to the accumulation of blood clots in the lung vasculature that obstructs flow and increases pressure. The mechanobiological factors that drive progression of CTEPH are not understood, in part because mechanical and hemodynamic changes in the small pulmonary arteries due to CTEPH are not easily measurable. Using previously published hemodynamic measurements and imaging from a large animal model of CTEPH, we applied a subject-specific one-dimensional (1D) computational fluid dynamic (CFD) approach to investigate the impact of CTEPH on pulmonary artery stiffening, time-averaged wall shear stress (TAWSS), and oscillatory shear index (OSI) in extralobar (main, right, and left) pulmonary arteries and intralobar (distal to the extralobar) arteries. Our results demonstrate that CTEPH increases pulmonary artery wall stiffness and decreases TAWSS in extralobar and intralobar arteries. Moreover, CTEPH increases the percentage of the intralobar arterial network with both low TAWSS and high OSI, quantified by the novel parameter φ , which is related to thrombogenicity. Our analysis reveals a strong positive correlation between increases in mean pulmonary artery pressure (mPAP) and φ from baseline to CTEPH in individual subjects, which supports the suggestion that increased φ drives disease severity. This subject-specific experimental-computational framework shows potential as a predictor of the impact of CTEPH on pulmonary arterial hemodynamics and pulmonary vascular mechanics. By leveraging advanced modeling techniques and calibrated model parameters, we predict spatial distributions of flow and pressure, from which we can compute potential physiomarkers of disease progression. Ultimately, this approach can lead to more spatially targeted interventions that address the needs of individual CTEPH patients.

In 1926, Cecil D. Murray published a fundamental law of physiology relating the form and function of branched vessels. Murray's Law predicts that the diameter of a parent vessel branching into two child branches is mathematically related by a cube law based on parabolic flow and power minimization with vascular volume. This law is foundational for computational analyses of branching vascular structures. However, pulmonary arteries exhibit morphometric and hemodynamic characteristics that may deviate from classical predictions. This study investigates the morphometry of pulmonary arterial networks, examining relationships between parent and child vessel diameters across species. We analyzed three-dimensional segmentations of pulmonary arterial geometries from healthy subjects across four species: human (n=7), canine (n=5), swine (n=4), and murine (n=3). Our findings reveal an average exponent value of 2.31 (± 0.60) in humans, 2.13 (± 0.54) in canine, 2.10 (± 0.49) in swine and 2.59 (± 0.58) in murine, all lower than the predicted value of 3.0 from Murray's Law. Extending Murray's Law to fully-developed pulsatile flow based on minimal impedance, we show that mean flow is proportional to radius raised to a power between 2.1 and 3, depending on the Womersley number. Our findings suggest that while Murray's Law provides a useful baseline, pulmonary artery branching follows a different optimization principle depending on Womersley number. This study contributes to a deeper understanding of pulmonary arterial structure-function relationships and implications for vascular disease modeling.

Subject-specific modeling is a powerful tool in cardiovascular research, providing insights beyond the reach of current clinical diagnostics. Limitations in available clinical data require the incorporation of uncertainty into models to improve guidance for personalized treatments. However, for clinical relevance, such modeling must be computationally efficient. In this study, we used a one-dimensional (1D) fluid dynamics model informed by experimental data from a dog model of chronic thromboembolic pulmonary hypertension (CTEPH), incorporating measurements from multiple subjects under both baseline and CTEPH conditions. Surgical intervention can alleviate CTEPH, yet patients with microvascular disease (e.g., remodeling and narrowing of small vessels) often exhibit persistent pulmonary hypertension, highlighting the importance of assessing microvascular disease severity. Thus, each lung was modeled separately to account for the heterogeneous nature of CTEPH, allowing us to explore lung-specific microvascular narrowing and resistance. We compared inferred parameters between baseline and CTEPH and examined their correlation with clinical markers of disease severity. To accelerate model calibration, we employed Gaussian process (GP) emulators, enabling the estimation of microvascular parameters and their uncertainties within a clinically feasible timeframe. Our results demonstrated that CTEPH leads to heterogeneous microvascular adaptation, reflected in distinct parameter shifts. Notably, the changes in model parameters strongly correlated with disease severity, especially in the lung previously reported to have more advanced disease. This framework provides a rapid, uncertainty-aware method for evaluating microvascular dysfunction in CTEPH and may support more targeted treatment strategies within a timeframe suitable for clinical application.