Waveband-Selective Ureter Imaging Using Endogenous Reflectance
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Solution Overview
Problem
Existing techniques for ureter detection during surgical procedures often require the introduction of exogenous fluorophores, temperature differences, or radioactive dyes, disrupting clinical workflow and may not be feasible in all situations.
Innovation Solution
Utilizing the selective reflection of light by ureters and surrounding tissues to capture and analyze surgical site scenes from different light spectrums, enabling endogenous contrast for ureter visualization without the need for illuminating catheters or exogenous agents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If exogenous fluorophores or radioactive dyes are introduced to locate ureters, then ureter visualization is improved, but clinical workflow is disrupted and procedural complexity increases
Solution Approach 1:
The ureters naturally reflect light at specific wavelengths without requiring external agents. The system captures images at multiple wavelengths and uses computational processing to highlight ureters based on their inherent optical properties, eliminating the need for exogenous fluorophores or radioactive dyes.
Solution Approach 2:
The system changes the wavelength parameter of illumination light to capture images at multiple specific wavelengths (e.g., 450-580 nm, 640-750 nm, 900-1080 nm). By processing images captured at these different wavelengths, the system exploits the wavelength-dependent reflectance properties of ureteral tissue to achieve selective visualization.
2Measurement precision
If exogenous fluorophores are administered to image ureters, then detection capability is improved, but patient safety is compromised due to additional agents
Solution Approach 1:
The method utilizes the endogenous optical properties of ureteral tissue itself to generate contrast. No exogenous fluorophores, dyes, or radioactive agents are administered to the patient, eliminating the associated safety risks while maintaining the ability to detect and visualize ureters.
Solution Approach 2:
The system extracts and removes the need for exogenous contrast agents by directly utilizing the natural light-reflecting properties of ureteral tissue. The harmful factor (exogenous agents) is completely eliminated while preserving the detection function.
3Measurement precision
If multiple wavelengths of light are used to capture surgical scenes, then ureter identification accuracy is improved, but imaging system complexity increases
Solution Approach 1:
The imaging process is segmented into discrete wavelength bands, with each band captured separately by the image sensor. The system illuminates the surgical site with light at multiple specific wavelengths and captures reflected light at each wavelength, then processes these segmented images to identify ureters based on their spectral reflectance characteristics.
Solution Approach 2:
A single imaging system performs multiple functions by capturing images at multiple wavelengths and processing them through computational algorithms. The same hardware platform (light source, image sensor, processor) handles both standard visible light imaging and multi-wavelength spectral analysis, eliminating the need for separate specialized devices.
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 safe and efficient ureter imaging by highlighting ureters in surgical scenes, enhancing surgical precision and reducing procedural disruptions.
Implementation Method 1
a plurality of surgical site scenes is captured from reflected light having a different light spectrum
Implementation Method 2
The illuminator is configured to illuminate a surgical site with each of the plurality of wavebands
Data Source
AI summary
An illustrative surgical system may access a plurality of images captured outside a structure within a patient; detect a difference between spectral reflectances of scenes captured in the plurality of images; and identify, based on the detected difference between the spectral reflectances of the scenes captured in the plurality of images, pixels in at least one of the plurality of images that correspond to structure tissue of the structure.