Dual-Sided UV Scanning Microscopy for Rapid Tumor Margin Assessment
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Solution Overview
Problem
Current methods for determining tumor margins during surgery are inaccurate and time-consuming, leading to a significant number of patients requiring additional surgeries and treatments, which impose emotional, cosmetic, and financial burdens.
Innovation Solution
A deep-ultraviolet scanning microscopy system with dual-sided imaging and deep-learning algorithms for rapid, subcellular resolution tumor margin assessment, utilizing dual ultraviolet light sources and cameras, along with image processing and automated classification techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional margin assessment methods are used, then surgical time is reduced, but measurement precision and reliability of margin status determination deteriorate
Solution Approach 1:
The patent replaces traditional mechanical frozen section analysis with a fluorescence imaging system that uses ultraviolet light excitation to generate optical signals from fluorophores. This substitution enables rapid, real-time margin assessment during surgery with high precision, eliminating the time-consuming mechanical processing of frozen sections while maintaining or improving measurement accuracy.
Solution Approach 2:
The system changes the assessment parameters by using fluorescence intensity and spectral characteristics as diagnostic parameters instead of traditional histological examination. By detecting fluorescence signals from fluorophore-labeled tumor cells, the system provides rapid, accurate margin status determination within minutes, resolving the contradiction between speed and precision.
2Measurement precision
If traditional margin assessment methods are used, then device complexity is reduced, but measurement precision and reliability deteriorate
Solution Approach 1:
The fluorescence imaging system serves multiple functions: it provides real-time margin assessment, visualizes tumor boundaries, and guides surgical resection. By integrating ultraviolet light sources, fluorophore detection, and image processing capabilities into a single platform, the system achieves high measurement precision while managing complexity through multi-functionality.
Solution Approach 2:
The patent introduces fluorophores as intermediary substances that bind to tumor cells and emit fluorescence signals when excited by ultraviolet light. This intermediary mechanism enables highly precise tumor margin detection without requiring complex direct imaging of tissue structures, as the fluorophores act as sensitive markers that simplify the detection process while maintaining high accuracy.
3Measurement precision
If additional surgeries are performed to address positive margins, then measurement precision is improved, but loss of time and productivity worsen
Solution Approach 1:
The fluorescence imaging system performs preliminary margin assessment during the initial surgery by detecting fluorophore-labeled tumor cells at resection margins. This preliminary action provides immediate feedback on margin status, allowing surgeons to achieve complete tumor removal with negative margins during the first procedure, thereby eliminating the need for additional corrective surgeries and improving overall surgical productivity.
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 accurate and efficient identification of tumor margins during initial surgery, reducing the need for additional tissue removal and surgeries by providing high-resolution, rapid imaging and classification of tissue specimens.
Implementation Method 1
a first ultraviolet light source to illuminate the first side of the sample holder and a first camera to receive light emitted from the tissue sample
Data Source
AI summary
Deep-ultraviolet scanning microscopy uses a first imaging apparatus arranged on a first side of a sample and a second imaging apparatus arranged on a second side of the sample. The first imaging apparatus includes a first ultraviolet light source to illuminate the first side of the sample and a first camera to receive light emitted from the first side of the sample. The second imaging apparatus includes a second ultraviolet light source to illuminate the second side of the sample and a second camera to receive light emitted from the second side of the sample. The first and second sides can be imaged in parallel, and can be sparsely sampled to increase imaging speed. A machine learning model can be used to generate images from the acquired signals. Signals can be detected from intrinsic sources (e.g., tryptophan) and extrinsic sources (e.g., propidium iodide and/or eosin Y) at the same time.