A Calibration Framework for Patient‐Specific 1D Arterial Models: Reflection‐Coefficient Pre‐Optimization, Coupled Conduit–Peripheral Compliance, and Exact Terminal Flow Distribution

ABSTRACT

The accurate simulation of blood pressure and flow waveforms in patient‐specific 1D models requires precise calibration of numerous parameters, a task often complicated by limitations in clinical measurements and by heterogeneous modeling assumptions. This work proposes a comprehensive calibration methodology designed to ensure physiological consistency in the modeling of arterial networks across multiple spatial scales. The framework introduces a pre‐optimization strategy based on reflection coefficients to balance potential mismatches between measured inflow conditions, network topology, and pulse wave velocity distributions by quantifying their impact on reflections at terminal‐segment and junctions. A key component of the proposed approach is the combined calibration of conduit (1D) compliance and peripheral (0D) compliance, which are shown to be strongly coupled in realistic patient‐specific geometries and therefore cannot always be tuned independently to match pulse‐pressure targets. In parallel, we introduce a computational strategy to calibrate total and peripheral resistances so as to enforce an exact distribution of mean flow across all terminal segments while converging to target diastolic pressure. This exact enforcement of terminal flow fractions is vital to reliably compare and analyze the impact of alternative modeling hypotheses (friction/velocity‐profile assumptions, local versus averaged impedance, and pulse wave velocity formulations) without confounding effects due to residual flow‐distribution errors. The robustness of the proposed approach is demonstrated in four scenarios of increasing complexity, ranging from experimental hydraulic replicas to highly detailed systemic arterial trees. Overall, the method provides a versatile tool for developing reliable subject‐specific models. It enables a systematic assessment of how different factors, such as vascular topology, the balance between central and peripheral compliance, and the control of wave reflections, directly influence the accuracy of hemodynamic predictions.