Spectroscopic Filters for Vulnerable Plaque Detection
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Solution Overview
Problem
Current methods for analyzing blood vessel walls using near-infrared spectroscopy face challenges such as motion artifacts, variability in blood and fluid composition, and interference from intervening blood and fluid, which complicates the acquisition and interpretation of spectral data, leading to difficulties in accurately diagnosing atherosclerosis and predicting plaque rupture.
Innovation Solution
A system that uses preprocessing and filtering techniques, including orthogonal subspace projection and generalized least squares analysis, to remove unwanted spectral signals from blood and fluid, allowing for the extraction of the vessel wall's spectral response and subsequent chemometric analysis to assess the risk of heart attacks and characterize plaque types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If near-infrared spectroscopy is used to analyze blood vessel walls, then non-invasive assessment of atherosclerosis is achieved, but motion artifacts and interference from intervening blood and fluid complicate the spectral data
Solution Approach 1:
The patent extracts and removes unwanted spectral contributions from blood and fluid using chemometric filtering techniques. The system separates the spectral signal into desired (vessel wall) and unwanted (blood, fluid, motion artifacts) components, eliminating the harmful interference while preserving the diagnostic information about atherosclerosis and plaque characteristics.
Solution Approach 2:
The patent introduces chemometric analysis as an intermediary processing step between spectral acquisition and diagnosis. This mathematical mediator processes the raw spectral data, removing motion artifacts and interference from intervening substances, thereby enabling reliable diagnostic assessment despite the presence of harmful factors during data collection.
2Ease of operation
If spectral data are collected through intervening blood and fluid, then in vivo analysis is enabled, but the chemical composition variability of blood and fluid obscures the vessel wall signal
Solution Approach 1:
The patent extracts the unwanted spectral contributions from blood and fluid using reference spectra and chemometric filtering. By mathematically removing these interfering signals, the system recovers the underlying vessel wall spectral information, enabling precise measurement despite the presence of variable blood and fluid composition during in vivo analysis.
Solution Approach 2:
The patent uses reference spectra of blood and fluid as copies of the unwanted signal components. These reference copies are obtained separately and then subtracted from the measured spectral data, allowing the system to eliminate the obscuring effects of blood and fluid variability while maintaining the ability to perform in vivo analysis.
3Ease of operation
If the catheter head is not pinned during acquisition, then patient comfort and blood flow are maintained, but the path length of optical signal through blood becomes uncontrolled and increases interference
Solution Approach 1:
The patent employs chemometric analysis as a feedback mechanism that processes the acquired spectral data to compensate for uncontrolled path length variations. The system continuously adjusts the interpretation of spectral signals based on the actual measured data, removing the effects of variable blood path lengths and enabling accurate diagnosis despite catheter mobility during the procedure.
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
The system effectively reduces the impact of unwanted signals, enhancing the accuracy of spectral data analysis, enabling robust and sensitive diagnostic results for identifying vulnerable plaques and other tissue types within blood vessels, even in the presence of varying blood and fluid conditions.
Implementation Method 1
Near infrared (NIR) spectroscopy can be used to measure and mathematical, including statistical, techniques applied to extract information from the lower resolution NIR spectral data
Implementation Method 2
A critical challenge here, however, concerns the limited ability to control the conditions under which the spectral data are acquired. Motion artifacts arise due to the motion pumping action of the heart. Variability in the form of the intervening blood/body fluid, pressure, pH and oxygenation levels are some examples of elements that contribute to the complexity of the analysis
Implementation Method 3
Mathematical manipulations such as linear regression of the spectral band of interest and classic least squares and inverse least squares and other multivariate analysis tools are available for building quantitative calibrations as well as qualitative models for discriminant analysis
Data Source
AI summary
Spectral variation contributed from the absorbance of unwanted correlated signals, such as blood at variable pathlengths between an in vivo catheter optic probe and a coronary vessel wall is an obstacle in the detection of vulnerable plaque. Preprocessing methods are described to reduce the impact of blood upon the spectral signal, based on the principles of Orthogonal Subspace Projection (OSP) and Generalized Least Square (GLS). The multivariate discrimination models used on the processed spectral information reduce the number of independent factors that include contributions from blood. The disclosed chemometric processing including preprocessing methods provide for in vivo spectral detection of medical analytes within the human body and in particular within the coronary vessel wall. A demonstration of how the preprocessing methods impact a discrimination modeling technique is provided, how the blood filters were developed and optimized, and finally how the OSP and GLS blood filters correct the spectral signal and improve the discrimination results of the models.