NIR Autofluorescence Plaque Imaging for Early Risk Region Detection
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Solution Overview
Problem
Current imaging approaches fail to adequately characterize high-risk atherosclerotic plaques before ischemic events, leading to potential tissue ischemia and infarction, and lack predictive power to identify plaque-specific complications.
Innovation Solution
Near-infrared autofluorescence imaging systems and methods that utilize excitation sources and detectors to emit and capture light within specific wavelength ranges, enabling identification of high-risk atherosclerotic plaque regions by analyzing relationships between NIRAF signals, insoluble lipids, iron, and oxidative stress markers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current imaging approaches are used, then imaging capability is provided, but characterization of high-risk atherosclerotic plaques is insufficient
Solution Approach 1:
The imaging system segments the atherosclerotic plaque into distinct regions based on NIRAF signal intensity, identifying high-risk regions with elevated insoluble lipid and iron content separately from low-risk regions. This segmentation enables precise characterization of plaque heterogeneity and identification of vulnerable segments that would be missed in conventional uniform imaging approaches.
Solution Approach 2:
The patent introduces near-infrared autofluorescence (NIRAF) imaging as an intermediary technique that detects endogenous fluorophores (insoluble lipids and iron) within the plaque. This intermediary approach provides indirect but specific information about plaque composition and risk, bridging the gap between conventional imaging and direct tissue analysis.
2Reliability
If stents and interventional techniques are deployed, then blood flow is restored, but tissue damage has already occurred
Solution Approach 1:
The NIRAF imaging system performs preliminary identification of high-risk plaques before ischemic events occur. By detecting elevated insoluble lipid and iron content that precede plaque rupture, the system enables early intervention and prevention strategies, allowing clinical action to be taken before tissue damage occurs rather than after.
Solution Approach 2:
The imaging system provides feedback about plaque risk characteristics (insoluble lipid content, iron content, oxidative stress markers) that guides clinical decision-making. This feedback loop enables physicians to identify patients who would benefit from aggressive risk factor modification or preventive interventions, creating a feedback-driven prevention strategy.
3Measurement precision
If conventional imaging is used, then general imaging is provided, but predictive power for plaque-specific complications is lacking
Solution Approach 1:
The imaging system applies local quality analysis by evaluating specific compositional properties (insoluble lipid content, iron content, oxidative stress) at different locations within the plaque. Rather than providing a single uniform assessment, the system characterizes local variations in plaque composition that correlate with specific complication risks, enabling location-specific risk prediction.
Solution Approach 2:
The system utilizes NIRAF signal intensity variations (analogous to color changes) to differentially identify plaque components. High-risk regions exhibit distinct NIRAF characteristics due to elevated concentrations of autofluorescent molecules, creating a visual or quantitative 'color map' of plaque vulnerability that predicts specific complications based on local compositional anomalies.
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 early diagnosis of severe atherosclerotic plaques by identifying risk regions based on lipid and iron content, oxidative stress, and plaque stability, facilitating timely interventions.
Implementation Method 1
Near-infrared autofluorescence imaging systems and methods that utilize excitation sources and detectors to emit and capture light within specific wavelength ranges, enabling identification of high-risk atherosclerotic plaque regions by analyzing relationships between NIRAF signals, insoluble lipids, iron, and oxidative stress markers
Data Source
AI summary
A computer-implemented method for diagnosing a medical condition of a patient is provided. The method can include causing, using one or more processors, an excitation source to emit an excitation light towards a region of interest of an artery, receiving, using the one or more processors and a detector, imaging data of the region of interest of the artery, generating, using the one or more processors and the imaging data, an image of the region of interest, determining, using the one or more processors, a risk region of an atheromatous plaque, based on the imaging data, and determining, using the one or more processors, that the patient has a severe case of an atheromatous plaque, based on the determined risk region of the atheromatous plaque.