Tumor Edge Detection Using Fluorescence Intensity Slope
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Solution Overview
Problem
Current methods for marking tumor regions in tissue fields, especially at tumor edges, face challenges due to infiltration of tumor cells into healthy tissue and variations in fluorescence intensity among patients and tumors, leading to uncertain boundary definitions.
Innovation Solution
A computer-implemented method that uses the intensity or temporal intensity profile of light emitted or reflected by tissue regions, specifically determined from histologically relevant image portions, to mark tumor edges, allowing for individualized identification of tumor boundaries based on characteristics like tumor cell proportion or oxygen content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fluorescence intensity threshold is used to mark tumor boundaries, then tumor regions can be identified, but measurement precision deteriorates due to variations in fluorescence intensity among patients and tumors
Solution Approach 1:
The patent changes the parameter used for boundary detection from absolute fluorescence intensity to the slope of fluorescence intensity change. This parameter transformation makes the measurement independent of variations in overall fluorescence intensity among different patients and tumors, thereby improving both measurement precision and reliability of boundary identification
Solution Approach 2:
The patent employs a feedback mechanism by using the calculated slope of fluorescence intensity change to dynamically adjust and optimize the threshold value for boundary detection. This feedback approach allows the system to adapt to different patients and tumor types, maintaining consistent boundary definition accuracy despite variations in fluorescence characteristics
2Adaptability or versatility
If fixed threshold is used for tumor marking, then device complexity is reduced, but adaptability deteriorates due to individual variations in fluorescence characteristics
Solution Approach 1:
The patent transforms the boundary detection approach by calculating the slope of fluorescence intensity change rather than using fixed thresholds. This parameter change enables the system to adapt to individual patient variations in fluorescence characteristics while maintaining relatively simple device architecture
Solution Approach 2:
The patent introduces dynamic adaptability by using the slope calculation method that automatically adjusts to different fluorescence intensity profiles of individual patients and tumors. This dynamic approach allows the system to accommodate individual variations without requiring complex customization or multiple device configurations
3Measurement precision
If simple threshold method is used, then ease of operation is improved, but measurement precision worsens in mixed regions with transitioning colors
Solution Approach 1:
The patent improves edge region boundary accuracy by changing from absolute intensity thresholding to slope-based detection. This parameter transformation enables precise identification of boundaries in mixed regions where fluorescence intensity transitions from red to blue, as the slope method can detect the transition point even when absolute intensity values are ambiguous
Solution Approach 2:
The patent replaces the simple threshold comparison mechanism with a derivative-based detection mechanism. By substituting the direct intensity threshold method with a slope calculation approach, the system achieves higher precision in edge region detection while maintaining computational efficiency and operational simplicity
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 enables precise marking of tumor edges, aiding surgeons in balancing tumor removal with preservation of healthy tissue by using specific intensity profiles characteristic to each patient, thereby improving surgical accuracy.
Implementation Method 1
the accumulation of the natural, fluorescent metabolite protoporphyrin IX (PpIX) serves to delimit the tumor tissue from healthy brain regions. In this case, PpIX accumulates in the tumor and is identifiable as a red fluorescent region on a blue background if suitable excitation light and a suitable filter in the observation beam path are used.
Data Source
AI summary
The invention relates to a computer-implemented method for identifying a region (21) of a tumour (23) in a tissue-field image (27), which image shows a tissue region (25) having a tumour (23) and has been obtained by means of light reflected or emitted by the tissue region (25). In the method, the region (21) of the tumour (23) in the tissue-field image (27) is identified on the basis of a characteristic value for the intensity of at least one component of the light reflected or emitted by the tissue region (25). The characteristic value is determined using the intensity of the at least one component in an image detail of the tissue-field image (27), which image detail corresponds to a tissue portion (36, 36′) of the tissue region (25) at which at least one piece of histological information was obtained.