Evaluation of Fluence Correction Algorithms in Multispectral Photoacoustic Imaging

Multispectral photoacoustic imaging (MPAI) is a promising emerging diagnostic technology, but fluence artifacts can degrade device performance. Our goal was to develop well-validated phantom-based test methods for evaluating and comparing MPAI fluence correction algorithms, including a heuristic dif...

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Bibliographic Details
Published in:Photoacoustics (Munich) 2020-09, Vol.19 (C), p.100181-100181, Article 100181
Main Authors: Zhou, Xuewen, Akhlaghi, Nima, Wear, Keith A., Garra, Brian S., Pfefer, T. Joshua, Vogt, William C.
Format: Article
Language:English
Subjects:
diffusion theory
Monte Carlo
oximetry
oxygen saturation
spectral coloring
tissue phantoms
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Summary:Multispectral photoacoustic imaging (MPAI) is a promising emerging diagnostic technology, but fluence artifacts can degrade device performance. Our goal was to develop well-validated phantom-based test methods for evaluating and comparing MPAI fluence correction algorithms, including a heuristic diffusion approximation, Monte Carlo simulations, and an algorithm we developed based on novel application of the diffusion dipole model (DDM). Phantoms simulated a range of breast-mimicking optical properties and contained channels filled with chromophore solutions (ink, hemoglobin, or copper sulfate) or connected to a previously developed blood flow circuit providing tunable oxygen saturation (SO2). The DDM algorithm achieved similar spectral recovery and SO2 measurement accuracy to Monte Carlo-based corrections with lower computational cost, potentially providing an accurate, real-time correction approach. Algorithms were sensitive to optical property uncertainty, but error was minimized by matching phantom albedo. The developed test methods may provide a foundation for standardized assessment of MPAI fluence correction algorithm performance.
ISSN:2213-5979
2213-5979
DOI:10.1016/j.pacs.2020.100181