Optoacoustic Imaging Fluence Normalization and Spectral Unmixing
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Solution Overview
Problem
Clinical optoacoustic imaging systems face challenges in accurately processing data due to limited view angles and the need for improved post-processing techniques, especially when dealing with larger anatomies and unanesthetized patients, which affects the precision of hemoglobin-related characteristic analysis.
Innovation Solution
An optoacoustic imaging system that includes light sources generating laser pulses, an OA probe with a transducer array to collect return signals, and processors to generate acoustic pressure data, identify non-hemoglobin chromophore extents, and compute hemoglobin concentrations, incorporating fluence normalization and spectral unmixing to improve image accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If conventional optoacoustic imaging is used to image larger anatomies, then the field of view is increased, but the view angle limitation reduces measurement precision
Solution Approach 1:
The patent segments the imaging process into multiple angular views by moving the transducer array relative to the region of interest. Instead of attempting to capture the entire anatomy from a single limited angle, the system acquires optoacoustic signals from multiple angles and reconstructs images by combining these segmented views, thereby maintaining measurement precision across a larger field of view
Solution Approach 2:
The patent employs dynamic movement of the transducer array to change the viewing angle during imaging. By dynamically adjusting the position and orientation of the transducer array, the system can capture optoacoustic signals from multiple angles, overcoming the static view angle limitation and improving measurement precision for larger anatomical structures
2Device complexity
If spectral unmixing is performed without accounting for non-hemoglobin chromophores, then processing complexity is reduced, but measurement precision of hemoglobin parameters deteriorates
Solution Approach 1:
The patent extracts and separately accounts for non-hemoglobin chromophore contributions in the spectral unmixing process. By identifying and removing the spectral signatures of non-hemoglobin chromophores (such as melanin, lipid, and water) from the total optoacoustic signal, the system can more accurately determine hemoglobin parameters without being confounded by these interfering absorbers
Solution Approach 2:
The patent introduces non-hemoglobin chromophore spectral signatures as intermediary reference data in the unmixing algorithm. These reference spectra serve as mediators that allow the system to distinguish between hemoglobin and non-hemoglobin absorption contributions, enabling more precise hemoglobin parameter measurement while maintaining manageable processing complexity through the use of established spectral libraries
3Measurement precision
If fluence normalization is applied to account for light attenuation, then measurement accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent performs fluence normalization as a preliminary step before spectral unmixing. By pre-calculating and applying fluence correction factors that account for light attenuation and scattering effects, the system prepares the optoacoustic signals in advance, ensuring that subsequent concentration calculations are based on corrected data. This preliminary action reduces the need for complex iterative corrections later in the processing chain
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
Enhances the specificity and sensitivity of optoacoustic imaging by accurately accounting for non-hemoglobin chromophores, leading to better anatomical and functional tissue assessment, improving cancer diagnosis and kidney fibrosis analysis.
Implementation Method 1
OA imaging uses pulsed laser light to illuminate biological tissue. When the incident light energy is absorbed by tissue molecules known as chromophores, they undergo transient thermoelastic expansion which gives rise to acoustic waves that can be detected by an array of ultrasound transducers.
Implementation Method 2
When the incident light energy is absorbed by tissue molecules known as chromophores, they undergo transient thermoelastic expansion which gives rise to acoustic waves
Implementation Method 3
the received array signals can be processed to create an image of the chromophore spatial distribution
Data Source
AI summary
Optoacoustic (OA) imaging systems and methods are described that obtain OA return signal data associated with a response of a sub-region of a region of interest (ROI) to laser light pulses having one or more predominant wavelengths. An acoustic pressure data set is generated based on the OA return signal data. The acoustic pressure data is dependent on a composition of a first chromophore of interest (COI) and one or more second chromophores not of interest (non-COI) in the sub-region. An extent of the one or more second chromophores within the sub-region is identified. A value is assigned to one or more second chromophore factors based on the extent of the one or more chromophores within the sub-region. An amount of the first chromophore in the sub-region is computed based on the acoustic pressure data and the value assigned to the one or more chromophore factors. The amount of the first chromophore is then utilized to compute parametric maps for display.