Improved Photoacoustic-Based Oxygen Saturation Estimation With SNR-Regularized Local Fluence Correction

Area of Science:

• Biomedical imaging
• Optical imaging
• Medical physics

Background:

• Photoacoustic (PA) imaging is emerging in clinical applications.
• Accurate quantification of physiological parameters like oxygen saturation (SO2) is vital for PA imaging's clinical utility.
• Existing PA methods may face challenges in precise SO2 estimation due to factors like light fluence variations.

Purpose of the Study:

• To develop and validate a novel method for accurate tissue oxygen saturation (SO2) estimation using PA imaging.
• To improve the accuracy of PA-based SO2 measurements by addressing light fluence variations.
• To assess the performance of the developed method in both ex vivo and in vivo settings.

Main Methods:

• A method combining finite-element-based local fluence correction (LFC) with signal-to-noise-ratio (SNR) regularization was developed.
• The LFC approach was validated using data from a Vevo LAZR system.
• Performance was assessed using ex vivo blood targets (37.6%-99.6% SO2) and in vivo rat arteries.

Main Results:

• The developed LFC method significantly reduced estimation error for absolute SO2 and changes in SO2.
• Absolute SO2 estimation error decreased from 10.1% to 2.8% with LFC.
• SO2 change estimation error reduced from 6.4% to 2.0% with LFC.
• The accuracy of the LFC method was found to be correlated with the number of wavelengths used in the PA acquisition.

Conclusions:

• The study demonstrates the necessity of SNR-regularized LFC for accurate SO2 quantification in PA imaging.
• The developed method offers improved accuracy for in vivo and ex vivo PA-based SO2 measurements.
• This work contributes to advancing the clinical applicability of PA imaging through enhanced quantitative metrics.