Personalized Multiscale Cardiovascular Model for Patient-Specific Circulation
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Solution Overview
Problem
Current models of whole-body circulation are overly simplified, process-intensive, and inaccurate, failing to effectively assist in clinical settings for patient-specific cardiac disease evaluation and therapy planning.
Innovation Solution
A personalized multiscale computational model of the cardiovascular system is developed using medical images and signals, incorporating full-scale or reduced-order cardiac electromechanics coupled with whole-body circulation models to estimate and calculate dynamics, allowing for patient-specific parameter personalization and simulation of physiological and pathophysiological characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If current simplified models of whole-body circulation are used, then the modeling process is less intensive, but the accuracy and patient-specific relevance deteriorate
Solution Approach 1:
The cardiovascular system is segmented into multiple compartments (systemic circulation, pulmonary circulation, heart chambers) with distinct parameters for each, allowing the model to capture complex physiological behavior while maintaining computational tractability through modular structure
Solution Approach 2:
The model transforms fixed, generic circulation parameters into dynamic, patient-specific parameters by incorporating real-time measurements of blood pressure, flow rates, and cardiac output, enabling accurate personalization without requiring complete model reconstruction
2Adaptability or versatility
If generic circulation models are used, then patient-specific physiology is not reflected, but the model complexity and personalization requirements are reduced
Solution Approach 1:
Patient-specific anatomical and physiological parameters are pre-measured and stored in a database before circulation modeling, allowing the model to be quickly personalized by retrieving and applying these pre-collected data without complex real-time measurements
Solution Approach 2:
The model creates a virtual copy of the patient's cardiovascular system using measured anatomical dimensions and physiological parameters, enabling accurate simulation of patient-specific circulation dynamics without requiring direct intervention in the patient's system
3Reliability
If process-intensive modeling approaches are used, then comprehensive circulation parameters can be calculated, but the computational time and resource requirements increase
Solution Approach 1:
The circulation model is updated periodically using intermittent measurements rather than continuous computation, calculating comprehensive circulation parameters at key physiological moments (e.g., cardiac cycle phases) to maintain reliability while reducing overall computational burden
Solution Approach 2:
Complex fluid dynamics computations are replaced with equivalent electrical circuit analogies for circulation modeling, substituting mechanical blood flow calculations with simpler electrical current and voltage analogs that yield equivalent results with reduced computational complexity
Data Source
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AI summary
Personalized whole-body circulation calculation is provided. In one embodiment, a combination of models at different scales and machine learning may be used to personalize and calculate the circulation for a particular patient. In another embodiment, imaging, ECG, and pressure data are used to personalize a multi-scale whole body circulation model. Different parameters, such as (but not limited to) time-varying flow rate for the heart, pressure variation for the heart, cardiovascular systemic impedance, and cardiovascular pulmonary impedance, are determined for the patient and used to personalize the model. The model is then used to determine, visualize, or report a diagnostically or therapeutically useful circulation metric for that patient.