Medical Fluorescence Imaging for Delayed Tissue Perfusion Detection
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Solution Overview
Problem
Existing medical imaging systems struggle to accurately predict surgical complications due to inadequate assessment of tissue perfusion, which can lead to issues like tissue necrosis and other complications during surgeries.
Innovation Solution
The system assesses tissue perfusion by analyzing the relative onset fluorescence delay (ROFD) of fluorescence agents in tissue images, identifying areas of concern with delayed fluorescence onset, and calculating the time difference to predict potential complications, providing notifications for adjusting surgical plans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fluorescence imaging is used to assess tissue perfusion, then the ability to predict surgical complications is improved, but the complexity of the imaging system and analysis increases
Solution Approach 1:
The tissue imaging area is divided into multiple regions of interest (ROIs), with each ROI further segmented into perfused and non-perfused sub-regions based on fluorescence intensity thresholds. This segmentation enables detailed analysis of perfusion patterns without requiring complex overall system changes.
Solution Approach 2:
The system performs preliminary classification of tissue regions into perfused and non-perfused categories before calculating relative onset fluorescence delay. By pre-identifying areas of concern based on fluorescence intensity thresholds, the system simplifies subsequent timing analysis and improves prediction reliability.
2Measurement precision
If real-time fluorescence monitoring is performed to detect delayed perfusion, then surgical complication prediction is improved, but the measurement and detection complexity increases
Solution Approach 1:
The system continuously monitors fluorescence intensity over time and provides real-time feedback on perfusion status. By comparing current fluorescence levels against threshold values and calculating relative onset delays, the system delivers precise perfusion assessment with automated alerts for delayed areas.
Solution Approach 2:
The system uses multiple fluorescence intensity thresholds (first threshold for perfused region identification, second threshold for non-perfused region identification) to detect perfusion status. By monitoring changes in these parameters over time, the system achieves precise measurement without complex detection mechanisms.
3Measurement precision
If multiple fluorescence thresholds are used to identify perfused and non-perfused regions, then tissue perfusion assessment accuracy is improved, but the data processing complexity increases
Solution Approach 1:
The fluorescence image data is segmented into distinct regions based on intensity thresholds. The first threshold identifies perfused regions, while the second threshold identifies non-perfused regions. This segmentation approach enables accurate perfusion assessment through straightforward comparative analysis.
Solution Approach 2:
The system applies multiple threshold comparisons to ensure accurate region classification. By using both a first threshold and a second threshold to define perfused and non-perfused regions respectively, the system achieves high detection accuracy through systematic partial analysis of the fluorescence data.
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 clinicians to predict and prevent surgical complications by adjusting surgical plans based on tissue perfusion issues, reducing tissue necrosis and other complications through timely interventions.
Implementation Method 1
Fluorescence imaging generally involves the administration of a bolus of an imaging agent that circulates throughout the subject's tissue and emits a fluorescence signal when illuminated with the appropriate excitation light
Data Source
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Figure 3A~3B
AI summary
Disclosed herein are systems and methods that can assess whether there is an issue with tissue perfusion, which can help a clinician better predict any surgical complications that may arise. Fluorescence images of the tissue of a subject can continuously be observed until a portion of the tissue that first perfused with blood containing one or more fluorescent agents is at peak fluorescence. Any areas of the tissue from the fluorescence images that remain dark can be further observed until these areas of concern show their first sign of fluorescence. The time it takes for these areas of concern to show their first signs of fluorescence since the first onset of fluorescence in the tissue can be referred to as the relative onset fluorescence delay. If the relative onset fluorescence delay time is greater than a predetermined threshold, the clinician can alter or change the surgical plan.