Non-Invasive Tumor Material Mapping From Strain Models
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Solution Overview
Problem
Current methods for estimating material parameters, such as Young's modulus (YM) and Poisson's ratio (PR) in tissues like tumors, are invasive, costly, and limited by complex boundary conditions and tumor shapes, lacking the ability to provide high spatial resolution and non-invasive assessment.
Innovation Solution
A non-invasive technique using strain data and analytical models, including ultrasound elastography, to reconstruct YM and PR of tumors and surrounding tissues, employing Eshelby's inclusion formulation and cost functions, without imposing boundary assumptions, and integrating with imaging systems for simultaneous estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If invasive methods are used to estimate material parameters, then measurement precision can be improved, but ease of operation deteriorates and loss of time increases
Solution Approach 1:
The patent replaces invasive mechanical measurement systems with non-invasive optical imaging systems. Specifically, it uses digital image correlation (DIC) to capture surface deformations and optical coherence tomography (OCT) to measure internal displacements, eliminating the need for physical contact or insertion of sensors into the tissue. This substitution maintains measurement precision while dramatically improving ease of operation by making the procedure non-invasive.
Solution Approach 2:
The patent introduces optical fields as intermediaries to indirectly measure material parameters. Instead of directly contacting the tissue with sensors, the system uses light to probe the tissue mechanics. The optical fields interact with the tissue surface and internal structures, and the resulting optical signals are processed to extract mechanical properties, thus mediating between the measurement goal and the tissue without invasive contact.
2Measurement precision
If complex boundary conditions and tumor shapes are considered, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent creates a virtual copy of the tissue mechanics problem through numerical simulation. It uses finite element analysis to generate synthetic displacement fields that replicate the actual tissue behavior under known boundary conditions. By comparing the synthetic data with experimental optical measurements, the system can accurately estimate material parameters without needing to physically model or simplify complex tumor geometries and boundary conditions, thus maintaining high spatial resolution while avoiding the complexity of direct mechanical modeling.
3Ease of operation
If non-invasive techniques are used, then ease of operation improves, but measurement precision deteriorates
Solution Approach 1:
The patent merges multiple optical measurement techniques (digital image correlation and optical coherence tomography) with mechanical testing protocols. By combining surface-level DIC measurements with deeper OCT displacement measurements, and integrating both with finite element mechanical models, the system achieves accurate estimation of deep tissue mechanical parameters non-invasively. The synergistic combination of these techniques compensates for the limitations of individual non-invasive methods, maintaining measurement precision while preserving ease of operation.
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 non-invasive, cost-effective, and high-resolution estimation of YM and PR in complex tumor shapes, facilitating diagnosis, prognosis, and treatment by providing detailed mechanical and transport parameters.
Implementation Method 1
A non-invasive technique using strain data and analytical models, including ultrasound elastography
Data Source
AI summary
The disclosure provides a method, a system, an apparatus, and a computer program product for determining IFP, IFV, and fluid flow inside tumors. In one example, a method for estimating tumor parameters is disclosed. This method includes: (1) receiving image data from a tumor, (2) obtaining strain data of the tumor from the image data, and (3) determining a tumor parameter, such as IFP and IFV, employing the strain data and an analytical model. Additional tumor parameters can be determined employing the strain data and other analytical models. The additional tumor parameters include compression-induced fluid pressure, velocity and flow inside the tumor, parameter ? employing the fluid pressure, the ratio between vascular permeability and interstitial permeability, and the ratio of peak IFP and effective vascular pressure. Each of these parameters can be employed for analyzing, monitoring, treating, testing, etc., tumors or the effects of drugs on the tumors.