Abstract
SIGNIFICANCE: Hepatocyte spheroids (HCSs) are three-dimensional (3D) in vitro models that exhibit a multilayered structure with site-dependent cell viability. The non-invasive identification of HCS structure and viability variation is essential in fully exploiting the potential of HCS as a model for liver disease research. AIM: We aim to achieve long-term, non-invasive monitoring and quantification of HCS cell viability based on dynamic optical coherence tomography (D-OCT) and enhance visualization of HCS internal activity with D-OCT pseudo-color images. APPROACH: We employed D-OCT based on power spectrum analysis with an appropriate optical coherence tomography time-series image acquisition rate to obtain the motion frequency distribution of cells within HCS, thus distinguishing and segmenting the viable and necrotic cell layers based on the average frequency of cellular activity, and quantify the tissue activity using the pixel ratio of the segmented viable region to the total spheroid region. Meanwhile, we used the hue saturation value color mapping method to enable enhanced visualization and high-precision segmentation of viable and necrotic cell layers in HCS. RESULTS: The feasibility of the D-OCT method was verified experimentally with three sets of HCS samples (HCS-2000, HCS-5000, and HCS-10000) by comparison with a confocal laser scanning microscope. The cells in C3A-HCS were found to be active mainly in the range of 8 to 13 Hz by D-OCT detection. 3D D-OCT pseudo-color images of HCS with a maximum diameter of 450 μm were displayed, and the 3D structures of necrotic and viable cell layers were identified by mask segmentation based on the average cell activity frequency threshold (10.5 Hz). The longitudinal necrotic process of three sets of HCS samples with differing inoculated cell numbers was monitored and quantified over 29 days. CONCLUSIONS: The employed D-OCT method can be used to quantitatively evaluate the site-dependent cell viability in HCS and possesses the potential for long-term, non-invasive monitoring and quantification of HCS viability.