Patient-Specific Vasculature Model for Hemodynamic Force Estimation
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Solution Overview
Problem
Current medical imaging technologies lack effective methods for estimating hemodynamic forces such as wall shear stress and axial plaque stress, which are crucial for assessing the risk of plaque rupture in coronary atherosclerosis, and do not provide personalized monitoring for outpatients.
Innovation Solution
A system and method for estimating hemodynamic forces by constructing patient-specific geometric models of the vasculature using patient-specific parameters, incorporating pressure and radius gradients, and applying computational fluid dynamics or machine learning algorithms to predict axial plaque stress and wall shear stress.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If patient-specific geometric models and computational fluid dynamics are used to estimate hemodynamic forces, then measurement precision of axial plaque stress and wall shear stress is improved, but device complexity increases
Solution Approach 1:
The system pre-computes and stores hemodynamic force values (axial plaque stress and wall shear stress) for various geometric configurations in a lookup table during system initialization. When analyzing patient data, the system retrieves pre-computed values based on matching geometric parameters rather than performing real-time computational fluid dynamics simulations, thereby maintaining high measurement precision while reducing operational complexity
Solution Approach 2:
The system creates simplified geometric models that replicate the essential features of complex patient-specific vasculature. These simplified models are used to query pre-computed hemodynamic force values from lookup tables, allowing accurate estimation without requiring complex computational resources during clinical operation
2Reliability
If continuous monitoring of hemodynamic parameters is implemented for outpatients, then reliability of risk stratification is improved, but loss of time for data collection and processing increases
Solution Approach 1:
The system pre-computes hemodynamic force values and stores them in lookup tables based on geometric parameters (radius gradient, lesion length, minimum lumen area) during system initialization. When patient data is collected, the system quickly retrieves pre-computed values by matching geometric parameters rather than performing time-consuming simulations, maintaining reliable risk stratification while minimizing data processing time
Solution Approach 2:
The system replaces time-consuming computational fluid dynamics simulations with a database query mechanism. By substituting complex mechanical computations with pre-computed lookup tables, the system achieves continuous monitoring capability with minimal processing time while maintaining the reliability needed for accurate risk stratification
Data Source
AI summary
Computer-implemented methods are disclosed for estimating values of hemodynamic forces acting on plaque or lesions. One method includes: receiving one or more patient-specific parameters of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion; constructing a patient-specific geometric model of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion, using the received one or more patient-specific parameters; estimating, using one or more processors, the values of hemodynamic forces at one or more points on the patient-specific geometric model, using the patient-specific parameters and geometric model by measuring, deriving, or obtaining one or more of a pressure gradient and a radius gradient; and outputting the estimated values of hemodynamic forces to an electronic storage medium. Systems and computer readable media for executing these methods are also disclosed.