Photoacoustic computed tomography (PACT) is an emerging biomedical imaging modality that uniquely combines high spatial resolution with deep penetration, holding great promise for non-invasive mapping of tissue oxygen saturation (sO2)—a critical biomarker in metabolism and pathophysiology. However, achieving accurate quantitative sO2 mapping is fundamentally challenged by the spatiotemporal heterogeneity of optical fluence, which leads to the spectral coloring effect and severely distorts measurements in deep tissue. This review systematically summarizes the evolution of quantitative PACT oximetry, critically analyzing techniques devised to overcome this bottleneck. We explore the limitations of linear unmixing and provide a focused analysis of advanced correction strategies, including photon transport modeling, acoustic-spectrum-based self-calibration, multimodality fusion, statistical inference, and learning-based approaches. By synthesizing and contrasting the strengths and weaknesses of these diverse approaches, this review aims to serve as a comprehensive reference for researchers, supporting the development of robust oximetry techniques and facilitating the clinical translation of PACT.
Liu et al. (Fri,) studied this question.