Optical Biopsy Probe for In Vivo T Classification
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Solution Overview
Problem
Current methods for detecting cancer, such as oral squamous cell carcinoma and prostate cancer, lack accurate and real-time diagnostic tools for in vivo characterization of tissue, leading to undetected multifocal cancers and recurrence due to the inability to differentiate between benign and malignant tissue effectively.
Innovation Solution
The use of electromagnetic radiation to characterize tissue by irradiating it with light and analyzing the scattered and fluoresced light to generate an excitation emission matrix, which is then used to derive spectroscopic measures for classification, employing pattern recognition techniques and artificial neural networks to differentiate between benign and malignant tissue.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current cancer detection methods (such as TRUS-guided needle biopsy) are used, then the procedure can be performed with existing technology, but the detection accuracy is low (25-30% clinical detection rate) and multifocal cancers are frequently missed
Solution Approach 1:
The diagnostic system segments the tissue characterization process into multiple independent measurement components: elastic scattering measurement, fluorescence emission measurement, and absorption measurement. Each component uses dedicated optical fibers and detection channels, allowing parallel acquisition of multiple tissue parameters without increasing overall system complexity
Solution Approach 2:
The optical probe head serves multiple functions simultaneously: it delivers excitation light, collects scattered light, collects fluorescence emission, and measures absorption. This multi-functional design consolidates what would otherwise require separate devices into a single integrated tool, improving detection accuracy without proportionally increasing complexity
2Measurement precision
If random needle biopsy is performed without tissue morphology knowledge, then the biopsy procedure is simple to perform, but the pathologic/clinical stage of disease is inaccurate and cancers are undetected
Solution Approach 1:
The system performs preliminary optical measurements of tissue morphology and biochemical properties before the biopsy is taken. These pre-biopsy measurements characterize the tissue at the molecular level, allowing the physician to target specific areas for biopsy and accurately stage the disease before surgical intervention
Solution Approach 2:
The system replaces mechanical tissue examination methods (visual inspection, palpation) with optical measurement techniques. Light interaction with tissue provides biochemical and morphological information without mechanical contact, making tissue characterization non-invasive and more informative
3Measurement precision
If frozen section is used to determine resection margins, then the procedure is currently available, but genetically abnormal tissue is clinically undetectable leading to recurrence
Solution Approach 1:
The system replaces frozen section histology with optical spectroscopy for margin assessment. The optical probe measures fluorescence emission and elastic scattering in real-time during surgery, providing immediate feedback on margin status without requiring tissue removal and laboratory processing
Solution Approach 2:
The optical measurements can be performed continuously during the surgical procedure without interrupting the workflow. The system provides ongoing real-time monitoring of tissue characteristics, allowing continuous assessment of resection margins rather than discrete snapshot analysis
4Measurement precision
If multiple excitation wavelengths are used to generate excitation emission matrix, then the tissue classification accuracy is improved, but the measurement time and system complexity increase
Solution Approach 1:
The system uses periodic modulation of the light source at different wavelengths, with each wavelength sequentially excited in a time-multiplexed manner. The photodetector collects signals during each periodic cycle, allowing reconstruction of the full excitation emission matrix through Fourier analysis of the modulated signals
Solution Approach 2:
The system measures a broader spectral range than strictly necessary for basic tissue classification. By capturing the full excitation emission matrix across multiple wavelengths, the system obtains more spectral features than minimally required, enabling more robust classification algorithms and better differentiation of subtle tissue variations
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
This approach allows for accurate and simple in vivo classification of tissue, enhancing early detection of cancerous conditions and reducing the invasiveness of treatments by providing real-time differentiation between benign and malignant tissue, thereby improving patient outcomes.
Implementation Method 1
The tissue is irradiated with light and light scattered and fluoresced from the sample is received
Implementation Method 2
The tissue is irradiated with light and light scattered and fluoresced from the sample is received
Data Source
AI summary
Methods and systems for in vivo classification of tissue are disclosed. The tissue is irradiated with light from multiple light sources and light scattered and fluoresced from the tissue is received. Distinct emissions of the sample are identified from the received light. An excitation-emission matrix is generated (1002). On-diagonal and off-diagonal components of the excitation-emission matrix are identified (1004, 1006, 1008). Spectroscopic measures are derived from the excitation-emission matrix (1014), and are compared to a database of known spectra (1016) permitting the tissue to be classified as benign or malignant (1018). An optical biopsy needle or an optical probe may be used to contemporaneously classify and sample tissue for pathological confirmation of diagnosis.