Non-invasive Tissue Characterization via IVUS Signal Correlation
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Solution Overview
Problem
Current medical imaging technologies provide non-invasive diagnosis but often require highly trained observers and may be subject to observer variability, failing to characterize tissue types accurately, which can lead to delayed treatment due to the need for biopsies.
Innovation Solution
A non-invasive tissue characterization system using a signal analyzer and correlation processor to analyze imaging data from external probes, correlating signal properties with pre-determined tissue properties through pattern recognition, enabling real-time tissue type identification and reducing the need for biopsies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If non-invasive imaging technologies are used to diagnose tissue conditions, then patient safety is improved by avoiding invasive procedures, but tissue characterization accuracy deteriorates due to observer variability and inability to definitively classify tissue types
Solution Approach 1:
The patent introduces an intravascular ultrasound (IVUS) probe as an intermediary device that can be positioned within the vasculature to obtain high-frequency imaging data. This intermediary approach allows non-invasive external imaging to be complemented by minimally invasive intravascular imaging, thereby improving tissue characterization accuracy while still avoiding open surgical procedures. The IVUS probe serves as a mediator between non-invasive external imaging and invasive biopsy procedures.
Solution Approach 2:
The patent replaces manual observer analysis with an automated computerized analysis system that processes IVUS imaging data. The system uses signal processing algorithms and pattern recognition to automatically characterize tissue types, replacing the mechanical system of human observation and interpretation. This substitution eliminates observer variability and improves measurement precision through consistent, reproducible automated analysis.
2Ease of operation
If traditional radiological imaging techniques are used for non-invasive diagnosis, then diagnostic information is obtained without introducing instruments into the patient's body, but tissue type classification deteriorates requiring additional biopsy procedures
Solution Approach 1:
The patent combines external non-invasive imaging techniques with intravascular ultrasound imaging and automated computerized analysis. By merging multiple imaging modalities and analysis approaches, the system achieves both non-invasive operation and accurate tissue type classification. The combination allows the system to overcome the limitations of individual techniques, providing comprehensive tissue characterization without requiring separate biopsy procedures.
Solution Approach 2:
The patent changes the parameters of imaging by using high-frequency ultrasound waves from the IVUS probe, which provide superior resolution compared to traditional radiological imaging. The system also changes the analysis parameters by using automated signal processing and pattern recognition algorithms that can extract tissue type information from the imaging data, transforming insufficient diagnostic information into accurate tissue characterization.
3Reliability
If highly trained observers analyze imaging data to localize objects of interest, then diagnostic capability is improved, but observer variability and subjectivity worsen leading to inconsistent results
Solution Approach 1:
The patent replaces the mechanical system of human observer analysis with an automated computerized analysis system. The system uses standardized algorithms and pattern recognition techniques to process IVUS imaging data, eliminating the variability and subjectivity inherent in manual observation. This substitution ensures consistent, reproducible results while maintaining high diagnostic capability through objective, algorithm-based tissue characterization.
4Measurement precision
If biopsy procedures are performed to definitively classify tissue types, then diagnostic accuracy is improved, but patient risk and procedural complexity worsen
Solution Approach 1:
The patent replaces the mechanical procedure of tissue biopsy with a non-invasive IVUS imaging and automated analysis system. The system uses high-frequency ultrasound waves to obtain detailed images of tissue structure and employs computerized pattern recognition to classify tissue types, eliminating the need for physical tissue sampling. This substitution maintains diagnostic accuracy while significantly reducing procedural complexity and patient risk.
Data Source
AI summary
Disclosed herein is a non-invasive system for determining tissue composition. The system comprises an imaging system with a non-invasive probe, a signal analyzer, and a correlation processor. The probe includes active imaging components for emitting energy and collecting imaging data including reflected signals from an object of interest. The signal analyzer analyzes the imaging data and determines one or more signal properties from the reflected signals. The correlation processor then associates the one or more signal properties to pre-determined tissue signal properties of different tissue components through a pattern recognition technique wherein the pre-determined tissue signal properties are embodied in a database, and identifies a tissue component of the object based on the pattern recognition technique.