Hybrid Cardiovascular Model Parameter Determination
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Solution Overview
Problem
Current models of cardiovascular systems, including both statistical form models and physiological simulation models, face limitations such as the inability of statistical form models to accurately map patient data in extreme disease cases and the difficulty in initializing and constraining physiological simulation models.
Innovation Solution
The proposed method involves determining parameters for one model based on the other, specifically by using a statistical form model to guide the fitting of a physiological simulation model, and vice versa, to create a modified model that combines the strengths of both approaches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If statistical form models are used to represent cardiovascular systems, then the model can be fitted to patient data, but the model lacks flexibility to deal with real patient data in marginal disease cases
Solution Approach 1:
The patent combines statistical form models and physiological simulation models into a hybrid approach. The statistical form model provides anatomical structure and geometry, while the physiological simulation model adds dynamic behavior and disease progression capabilities. This merging allows the system to handle both common and marginal disease cases effectively by leveraging the strengths of both model types.
Solution Approach 2:
The hybrid model system serves multiple functions: it can represent normal anatomy, simulate disease progression, predict treatment outcomes, and handle edge cases that pure statistical models cannot. The physiological simulation component adds universal applicability across different disease states and patient populations, making the system versatile for various clinical scenarios.
2Reliability
If physiological simulation models are used to predict system evolution, then the model can describe biological characteristics, but the model is difficult to initialize as many parameters can only be measured invasively or not at all
Solution Approach 1:
The statistical form model acts as an intermediary that bridges the gap between available patient data and the physiological simulation model. It provides initial anatomical parameters and geometric constraints that can be non-invasively derived from imaging data, thereby facilitating the initialization of the physiological simulation model without requiring invasive measurements.
Solution Approach 2:
The system performs preliminary actions by using the statistical form model to pre-process and prepare initial parameters before they are input into the physiological simulation model. This preliminary processing transforms readily available imaging data into meaningful initial conditions, reducing the need for invasive measurements and simplifying the initialization process.
3Adaptability or versatility
If physiological simulation models are used to represent cardiovascular systems, then the model can describe biological characteristics, but not every parameter of the model has a real-world equivalent
Solution Approach 1:
The patent applies local quality by differentiating the roles of different parameters: some parameters are directly tied to measurable physical quantities (e.g., chamber volume, wall thickness), while others represent abstracted biological characteristics (e.g., material properties, cellular behavior). This allows the model to maintain biological realism where needed while keeping parameters measurable where possible.
Data Source
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AI summary
A method by which a first parameter of a first model of a statistical form model and a physiological simulation model of a cardiovascular system, is determined based on the other, second model of the statistical form model and the physiological simulation model. The first model may then be modified based on the determined first parameter to determine a modified first model.