Peripheral Nerve Reflectance Imaging With CNN Segmentation
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Solution Overview
Problem
Current methods for intraoperative nerve identification, such as electromyography (EMG) and optical imaging, face limitations in specificity, invasiveness, and complexity, while radiological imaging is unsuitable for real-time surgical guidance due to size, resolution, and radiation concerns, and existing fluorescent agents have toxicity issues.
Innovation Solution
An imaging method using wavelength-dependent reflectance detection with a light source and deep learning assistance to visualize peripheral nerves, employing a light source to generate reflected light at 410-490 nm and utilize convolutional neural networks (CNN) for real-time imaging and segmentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If electromyography (EMG) is used for nerve identification, then nerve detection can be performed with compact equipment, but the method is invasive and may cause muscle injury, bleeding, and nerve damage
Solution Approach 1:
The patent replaces the mechanical invasive electrode insertion method with an optical imaging method using light sources and cameras to visualize nerves non-invasively, eliminating physical trauma to muscles and nerves while maintaining detection capability
Solution Approach 2:
The patent introduces fluorescent dyes as intermediary substances that bind to nerves and emit light signals, allowing indirect visualization of nerves without direct mechanical contact or insertion, thus avoiding tissue damage
2Measurement precision
If conventional radiological imaging modalities (MRI, PET, ultrasound) are used for nerve detection, then imaging capability is provided, but the equipment is bulky and complicated for intraoperative use
Solution Approach 1:
The patent replaces bulky radiological equipment with a compact optical imaging system using light sources and cameras, enabling portable and intraoperative nerve visualization without requiring large MRI or PET scanners
Solution Approach 2:
The patent changes the imaging parameter from radiological modalities to optical wavelength detection, specifically using fluorescent emission wavelengths that can be captured by standard cameras, making the system compact and suitable for operating rooms
3Measurement precision
If fluorescent dyes with high specificity for nerves are used, then nerve identification specificity is improved, but toxicity concerns limit clinical application
Solution Approach 1:
The patent uses low-toxicity or biocompatible fluorescent dyes that can be safely administered, replacing highly specific but toxic fluorescent agents with safer alternatives that maintain adequate nerve detection capability
Solution Approach 2:
The patent explores using endogenous fluorescent substances naturally present in nerves (such as NADH, FAD, or myelin components) to provide self-illumination without requiring exogenous fluorescent agents, thereby eliminating toxicity concerns while maintaining nerve specificity
4Measurement precision
If advanced optical imaging techniques (third-harmonic generation microscopy, optical coherence tomography) are used for nerve visualization, then high resolution and sensitivity are achieved, but the instruments are complicated and expensive with time-consuming image processing
Solution Approach 1:
The patent uses standard, readily available optical components (light sources, filters, cameras) instead of expensive and complex specialized microscopes, achieving adequate nerve visualization with simple, inexpensive equipment that can be deployed in operating rooms
Solution Approach 2:
The patent simplifies the optical imaging approach by using broad spectral light sources and standard camera detection, avoiding complex multiphoton or coherence-based techniques, thereby reducing instrument complexity and processing requirements while maintaining sufficient nerve detection capability
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
Provides real-time, specific, and non-invasive visualization of peripheral nerves without exogenous agents, enhancing surgical precision and safety by improving nerve detection and segmentation accuracy.
Implementation Method 1
irradiating the tissue sample with a light source thereby producing a reflected light from the tissue sample; and generating one or more nerve image by detecting the reflected light at a wavelength of 410-490 nm
Data Source
AI summary
Methods and systems useful for machine learning assisted imaging and detection of peripheral nerves comprising reflectance imaging spectroscopy. The method can be conducted label-free and in real-time.