Fluorescence Perfusion Imaging With Micro-Bolus Pattern Detection
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Solution Overview
Problem
Existing fluorescence-guided surgery methods struggle to objectively and quantitatively detect abnormal perfusion patterns, such as cancerous or inflammatory tissue, due to limitations in visual assessment and the inability to conduct multiple measurements without a washout period, leading to potential underestimation and increased surgical risks.
Innovation Solution
A system and method utilizing a series of controlled micro-boluses of fluorescent agents to create an oscillating input signal, allowing for continuous perfusion monitoring and real-time detection of abnormal perfusion patterns by analyzing the distortion of the input signal through body kernels, which can be superimposed onto white light images for surgical guidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If a large bolus of fluorescent agent is administered, then signal intensity is sufficient for visual inspection, but the ability to conduct multiple measurements is limited due to washout period requirements
Solution Approach 1:
The patent divides a single large bolus administration into multiple smaller boluses administered over time. This segmentation allows the system to maintain sufficient signal intensity for each measurement while enabling multiple measurements within a reasonable time frame, eliminating the need for long washout periods between measurements.
Solution Approach 2:
The system employs periodic administration of small boluses at controlled intervals. This periodic action creates a time-varying signal pattern that allows multiple measurements to be taken systematically, with each bolus providing a fresh signal event that can be measured before the next one is administered.
2Loss of information
If visual assessment of fluorescence inflow and outflow is used, then tissue perfusion information can be obtained, but quantitative assessment is impossible due to reliance on surgeon's visual judgment
Solution Approach 1:
The system implements automated feedback by capturing fluorescence images, processing them through deconvolution algorithms, and generating quantitative perfusion parameter maps. This feedback loop replaces subjective visual assessment with objective computational analysis, providing precise quantification of tissue perfusion characteristics.
Solution Approach 2:
The patent replaces the mechanical/visual assessment process with an automated computational system. Instead of relying on the surgeon's visual judgment and manual observation, the system uses image processing algorithms and deconvolution techniques to automatically extract and quantify perfusion information from fluorescence images.
3Device complexity
If only one predefined area is visualized per ICG assessment, then measurement process is simple, but the ability to detect abnormal tissue across the entire surgical field is limited
Solution Approach 1:
The system is designed to perform multiple functions simultaneously: it can analyze multiple regions of interest, generate perfusion parameter maps for the entire surgical field, and detect both normal and abnormal tissue characteristics. This multi-functionality allows comprehensive tissue assessment without significantly increasing operational complexity.
Solution Approach 2:
The patent transitions from analyzing a single predefined area to generating spatially-resolved perfusion parameter maps across the entire surgical field. By adding the spatial dimension to the analysis, the system can simultaneously evaluate multiple regions and identify abnormal tissue locations while maintaining a unified measurement approach.
4Loss of information
If multiple measurements are conducted with a large bolus dose, then comprehensive tissue assessment is possible, but considerable washout time is required between measurements
Solution Approach 1:
By segmenting the total contrast agent dose into multiple small boluses administered at intervals, the system enables comprehensive tissue assessment across multiple measurement time points without requiring long washout periods. Each small bolus provides sufficient signal for measurement while clearing quickly enough to allow rapid sequential measurements.
Solution Approach 2:
The periodic administration of small boluses creates a measurement protocol where each bolus serves as a discrete measurement event. This periodic structure allows the system to conduct multiple measurements systematically, with the timing optimized to capture perfusion dynamics without requiring extended washout periods between measurements.
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 real-time, continuous identification of abnormal perfusion patterns, reducing surgical risks and improving surgical precision by providing objective quantification and visual enhancement of abnormal tissue areas during surgery.
Implementation Method 1
fluorescence imaging agent, wherein the series of boluses is administered with a predefined and/or controlled duration between subsequent boluses
Data Source
AI summary
The present disclosure relates to systems and methods for continuously detecting, and optionally classifying, abnormal perfusion patterns in tissue by means of fluorescence imaging. One embodiment relates to a computer implemented method for detecting (and/or identifying) one or more areas having an abnormal perfusion pattern in tissue of a subject, for example during a medical procedure, the method comprising the steps of: continuously acquiring fluorescence images of the tissue, wherein the fluorescence images are associated with a fluorescent output signal correlated with an input signal defined by a series of boluses of at least one fluorescent imaging agent, and wherein the series of boluses is administered with a predefined and/or controlled duration between subsequent boluses, analysing the fluorescence images, identifying at least one tissue area with normal perfusion, defining a normal perfusion pattern (in an intensity domain and) in a time domain, and detecting, in the fluorescence images, possible tissue areas with abnormal (non-normal) perfusion pattern.