Patient-Specific Lung Models for Optimized Mechanical Ventilation
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Solution Overview
Problem
Current mechanical ventilation settings for patients are often empirical and not optimized, leading to inadequate treatment outcomes and potential complications, with a subset of the population not benefiting fully due to excessively long or inadequate startup periods.
Innovation Solution
A method involving the use of pre- and post-treatment three-dimensional imaging of the respiratory system to create patient-specific structural models, which are then used for computational fluid dynamics and finite element analysis to determine optimized ventilation parameters, reducing airway resistance and improving mass flow for personalized mechanical ventilation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If empirical methods are used to set mechanical ventilation parameters, then the setup process is simple and quick, but the treatment efficacy is inadequate and complications may occur
Solution Approach 1:
The patent performs computational fluid dynamics simulations and finite element analysis before actual mechanical ventilation treatment to predict optimal ventilation parameters. This preliminary computational assessment allows clinicians to set evidence-based parameters without lengthy trial-and-error adjustments, improving treatment efficacy while maintaining practical implementation feasibility
Solution Approach 2:
The patent creates a computational model that replicates the patient's unique airway geometry and lung structure based on medical imaging data. This virtual copy allows for risk-free parameter testing and optimization in silico before applying settings to the actual patient, thereby improving treatment reliability without adding significant clinical complexity
2Reliability
If patient-specific computational modeling is used to optimize ventilation parameters, then treatment efficacy is improved, but the time and resources required for setup increase
Solution Approach 1:
The computational modeling and simulations are performed in advance of actual treatment to establish optimal ventilation parameters. By completing the time-consuming computational analysis before treatment begins, the patent enables immediate implementation of optimized settings without extending the clinical startup period
Solution Approach 2:
The patent replaces physical trial-and-error adjustment of ventilation parameters with computational simulations. This substitution allows rapid evaluation of multiple parameter scenarios in silico, avoiding the time-consuming iterative process of adjusting physical ventilator settings in the clinical setting
3Adaptability or versatility
If standardized ventilation settings are used for all patients, then the setup process is simplified, but a subset of the population does not benefit fully from treatment
Solution Approach 1:
The patent analyzes and optimizes ventilation parameters for specific regions of the lung (different lobes and segments) based on patient-specific anatomy. By considering local variations in airway geometry and lung structure, the patent enables personalized ventilation strategies that adapt to each patient's unique respiratory physiology, improving treatment adaptability
Solution Approach 2:
The patent divides the lung into distinct anatomical segments and lobes for individualized analysis. This segmentation allows the computational model to account for regional differences in ventilation requirements, enabling tailored parameter optimization for each lung region rather than applying uniform settings throughout
4Reliability
If empirical adjustment of ventilation parameters is used, then the process is straightforward, but treatment failures may occur due to inadequate parameter selection
Solution Approach 1:
The computational model incorporates feedback from medical imaging data and physiological measurements to iteratively refine ventilation parameter predictions. By integrating multiple data sources and validating model predictions against observed patient responses, the patent improves the reliability of parameter optimization while providing clinicians with decision-support tools that reduce the difficulty of selecting appropriate settings
Data Source
Figure 1A~2B
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AI summary
The present invention concerns a method for determining optimised parameters for mechanical ventilation, MV, of a subject, comprising: a) obtaining data concerning a three- dimensional image of the subject's respiratory system; b) calculating a specific three- dimensional structural model of the subject's lung structure from the image data obtained in step a); c) calculating a specific three-dimensional structural model of the subject's airway structure from the image data obtained in step a); d) calculating a patient-specific three-dimensional structural model of the subject's lobar structure from the lung model obtained in step b); e) modeling by a computer, the air flow through the airway, using the models of the airway and lobar structure of the subject obtained in steps c) and d) at defined MV parameters; f) modeling by a computer, the structural behavior of the airway and the interaction with the flow, using the models of the airway and lobar structure of the subject obtained in steps b) and c) at defined MV parameters; g) determining the MV parameters which lead to a decrease in airway resistance and hence an increase in lobar mass flow for the same driving pressures according to the model of step d), thereby obtaining optimized MV parameters. It also relates to a method for assessing the efficacy of a treatment for a respiratory condition.