Influence of Tissue Curvature on the Absolute Quantification in Frequency-Domain Diffuse Optical Spectroscopy

Accurate estimation of optical properties and hemodynamic parameters is critical for advancing frequency-domain diffuse optical spectroscopy (FD-DOS) techniques in clinical neuroscience. However, conventional FD-DOS models often assume planar air–tissue interfaces, introducing errors in anatomically curved regions such as the forehead or infant heads. This study evaluates the impact of incorporating tissue curvature into forward models for FD-DOS analysis. Using simulations and optical phantoms, we demonstrate that curved models reduce errors in absorption coefficient estimation from 20% to less than 10% in high-curvature scenarios. Within the curvatures tested, even minor curvature mismatches resulted in errors significantly lower than those observed from planar approximations (p < 0.001). In low-curvature regions, curved models yielded errors comparable to planar models (<5% in both cases). When applied to human data, our proposed curved model increased absorption and hemoglobin concentration estimates by 10–15% compared to standard semi-infinite models, closer to physiological expectations. Overall, these results quantitatively demonstrate that accounting for tissue curvature in FD-DOS forward models significantly improves the accuracy of optical property estimation. We propose a numerical framework that achieves this in a fast and reliable manner, advancing FD-DOS as a robust tool for clinical and research applications in anatomically complex regions.