MR Elastography System for Tissue Stiffness Analysis
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Solution Overview
Problem
Current medical imaging technologies lack standardized datasets for symptomatic and asymptomatic tissue samples, limiting the ability to improve medical diagnoses and requiring extensive manual processing by radiologists, which is inefficient and prone to errors.
Innovation Solution
A system and method for magnetic resonance Elastography that creates a large database of symptomatic and asymptomatic Magnetic Resonance signature data using MR Elastography, enabling automatic detection and classification of tissue anomalies through software algorithms and providing detailed scans, optimized for both biological life forms and tissue samples, including fresh, frozen, and formalin-fixed samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual processing by radiologists is used to evaluate tissue samples, then diagnostic accuracy can be maintained through expert review, but productivity is reduced and loss of time increases due to extensive manual processing requirements
Solution Approach 1:
The system creates a standardized digital copy of tissue sample data through MR Elastography imaging, transforming physical tissue evaluation into reproducible digital signatures that can be stored, compared, and analyzed without requiring continuous manual intervention by radiologists
Solution Approach 2:
The system performs preliminary automated analysis and classification of tissue samples using standardized MR Elastography protocols, preparing standardized datasets and preliminary diagnostic recommendations before radiologist review, thereby reducing the time and effort required for manual evaluation
2Measurement precision
If extensive manual processing by radiologists is performed, then comprehensive evaluation of tissue samples can be achieved, but loss of time increases and the system cannot keep pace with increasing data volumes
Solution Approach 1:
The system replaces the mechanical process of manual radiologist evaluation with automated software algorithms that analyze MR Elastography data, using standardized datasets and machine learning models to perform comprehensive tissue characterization without human intervention for routine cases
Solution Approach 2:
The system transforms tissue evaluation from subjective radiologist assessment to objective quantitative measurement using standardized MR Elastography parameters, enabling automated comparison against standardized datasets and facilitating rapid, consistent evaluation across large numbers of samples
3Extent of automation
If standardized datasets are created using MR Elastography, then automatic detection and classification of anomalies can be improved, but device complexity increases due to the need for specialized imaging equipment and processing systems
Solution Approach 1:
The system designs MR Elastography equipment and standardized datasets to serve multiple functions: creating diagnostic images, generating quantitative tissue signatures, enabling automated anomaly detection, and providing standardized comparison data across different institutions and patient populations
Solution Approach 2:
The system divides the complex task of tissue diagnosis into separate standardized components: MR Elastography imaging acquisition, signature extraction, anomaly detection algorithms, and classification systems, allowing each component to be optimized independently and facilitating modular system implementation
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
Facilitates the creation of a comprehensive database for tissue samples, allowing for efficient detection and classification of anomalies, reducing the workload for radiologists and improving diagnostic accuracy by leveraging MR Elastography and other imaging techniques.
Implementation Method 1
sending mechanical waves through the tissue with an MRI technique including sending shear waves in the tissue
Implementation Method 2
acquiring images of the propagation of the shear waves, and processing the images of the shear waves to produce a quantitative mapping of the tissue stiffness
Data Source
AI summary
A system for MR Elastography of a sample, including ultrasound gel to sheath the sample, a vessel to accept the flow of the sample sheathed in ultrasound gel, a sensor array adapted to capture an ultrasound measurement and an MR measurement, wherein the sensor array including an ultrasound transmitter and an ultrasound receiver, and the sensor array is coupled to the vessel, and the vessel is capable of mechanical conductance between the ultrasound transducers, and the ultrasound gel, and a pump to create a pressure based flow of ultrasound fluid through the vessel and move the sample in proximity to the sensor array for capture of MR and ultrasound measurements of the sample as the sheathed sample passes by the sensor array.