Lumped Parameter Model for Non-Invasive Hemodynamic Quantification

The patent creates a computational model that replicates the cardiovascular system's hemodynamic behavior, producing virtual measurements that mirror what invasive catheterization would detect. The model uses patient-specific anatomical data from non-invasive imaging to generate pressure and flow waveforms, effectively creating a digital twin that copies the physiological system's response without physical intrusion.

The patent replaces the mechanical invasive catheterization system with a computational-mechanics framework. Instead of physically inserting catheters into blood vessels to measure pressure and flow, the system uses non-invasive imaging data combined with computational fluid dynamics and lumped-parameter modeling to calculate hemodynamic parameters, substituting mechanical measurement with mathematical simulation.

The patent introduces a computational model as an intermediary between non-invasive imaging data and hemodynamic assessment. The model takes readily available non-invasive measurements (echocardiography, CT, MRI) and transforms them into quantitative hemodynamic parameters through mathematical relationships, acting as a bridge that converts easy-to-obtain data into precise physiological insights without requiring direct invasive measurement.

The patent transforms anatomical parameters from non-invasive imaging into functional hemodynamic parameters through computational modeling. By changing the parameter space from static anatomical measurements to dynamic functional outputs, the system extracts precise hemodynamic information (pressure gradients, flow rates, ventricular workload) that cannot be directly measured by imaging alone but can be derived through parameter transformation in the computational model.

The patent divides the cardiovascular system into discrete segmental models representing different anatomical regions (aorta, ventricles, arteries, veins). Each segment is modeled with appropriate hemodynamic properties and can be analyzed independently or in combination, allowing comprehensive global hemodynamic assessment through aggregation of local segmental analyses without requiring a single overly complex monolithic model.

The patent implements dynamic computational models that simulate time-varying hemodynamic conditions throughout the cardiac cycle. The models capture transient pressure and flow variations, valve opening/closing events, and pulsatile flow patterns, enabling precise quantification of both local and global hemodynamics through dynamic simulation rather than static analysis, thereby managing complexity through temporal decomposition.