Deformable Lung Phantom with Polymer Nanocomposite
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Solution Overview
Problem
Current methods for estimating lung deformation during breathing lack accuracy due to the absence of physical lung phantoms that replicate both material properties and X-ray attenuation similar to actual lung anatomy, leading to discrepancies in radiation therapy planning.
Innovation Solution
Development of a deformable physical lung phantom using polymer nanocomposite materials with elastic and radiological properties equivalent to human lung tissue, combined with computational fluid dynamics (CFD) and radiotherapy data integration for accurate simulation of spatio-temporal flow and deformation, utilizing Tikhonov regularization to fuse CFD predictions with experimental data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pure imaging methods or inverse deformation methods are used to estimate lung deformation, then the estimation can be obtained, but discrepancies and lack of accuracy occur due to absence of physical material properties
Solution Approach 1:
The patent changes the fundamental parameter of measurement from pure image data to physical material properties by developing polymer nanocomposite materials with elastic properties matching human lung tissue. This allows deformation estimation based on actual physical behavior rather than image processing alone, resolving the accuracy and reliability discrepancies.
Solution Approach 2:
The patent creates composite polymer nanocomposite materials combining polymer matrices with nanoparticles to achieve both mechanical elasticity equivalent to lung tissue and appropriate X-ray attenuation properties. This composite approach enables physical phantoms that accurately represent both structural and radiological properties of real lungs.
2Loss of information
If numerical modeling is used to simulate flow and deformation, then detailed information can be obtained, but limitations prevent accurate representation of actual lung behavior
Solution Approach 1:
The patent creates physical copies (phantoms) of lung tissue using polymer nanocomposites that replicate the elastic and radiological properties of actual lung tissue. These physical models provide more reliable deformation characteristics than numerical modeling alone, while retaining the detailed information capability.
3Ease of manufacture
If conventional phantoms are used for radiation therapy QA, then treatment planning can be performed, but accurate simulation of lung anatomy and behavior is not achieved
Solution Approach 1:
The patent develops polymer nanocomposite materials that simultaneously achieve mechanical elasticity matching lung tissue and X-ray attenuation properties equivalent to real lung anatomy. This allows conventional phantom manufacturing approaches to produce highly accurate anatomical and behavioral simulations.
Solution Approach 2:
The patent enables region-specific customization of phantom properties by varying nanoparticle distribution and polymer composition to match different lung regions' elastic and radiological characteristics, improving overall anatomical simulation accuracy while maintaining manufacturability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables precise simulation and testing of radiation therapy plans, reducing normal tissue irradiation and improving radiation therapy efficiency by creating a patient-specific, 3D-printable phantom that mimics lung anatomy and behavior.
Implementation Method 1
polymer nanocomposite materials with elastic and radiological properties that mimic the human lung
Implementation Method 2
radiation-attenuation equivalency to the anatomy being represented
Data Source
AI summary
A system and method to integrate computational fluid dynamics (CFD) and radiotherapy data for accurate simulation of spatio-temporal flow and deformation in real human lung is presented. The method utilizes a mathematical formulation that fuses the CFD predictions of lung displacement with the corresponding radiotherapy data using the theory of Tikhonov regularization.