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.

多光谱光声成像（MPAI）是一种有前途的新兴诊断技术，但是注量伪影会降低设备性能。我们的目标是开发经过验证的基于幻像的测试方法，以评估和比较MPAI能量通量校正算法，包括启发式扩散近似，蒙特卡洛模拟以及基于扩散偶极子模型（DDM）的新颖应用开发的算法。Phantoms模拟了一系列模拟胸部的光学特性，并包含填充有生色团溶液（墨水，血红蛋白或硫酸铜）的通道，或与先前开发的提供可调氧饱和度（SO ₂）的血流回路连接的通道。DDM算法实现了相似的频谱恢复和SO ₂以较低的计算量实现基于蒙特卡洛的校正的测量精度，从而有可能提供一种准确的实时校正方法。算法对光学特性不确定性敏感，但是通过匹配幻像反照率将误差最小化。所开发的测试方法可以为MPAI通量校正算法性能的标准化评估提供基础。