Evaluation of Fluence Correction Algorithms in Multispectral Photoacoustic Imaging

• Published in: Photoacoustics (Munich) Vol. 19; no. C; p. 100181
• Main Authors: Zhou, Xuewen, Akhlaghi, Nima, Wear, Keith A., Garra, Brian S., Pfefer, T. Joshua, Vogt, William C.
• Format: Journal Article
• Language: English
• Published: Germany Elsevier GmbH 01.09.2020; Elsevier
• Subjects: diffusion theory; Monte Carlo; oximetry; oxygen saturation; spectral coloring; tissue phantoms; diffusion theory; tissue phantoms; oximetry; oxygen saturation; Monte Carlo; spectral coloring
• ISSN: 2213-5979; 2213-5979
• DOI: 10.1016/j.pacs.2020.100181

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.