Dual-modality imaging system for monitoring human heart organoids beating in vitro

Deep learning based characterization of human organoids using optical coherence tomography

Organoids, derived from human induced pluripotent stem cells (hiPSCs), are intricate three-dimensional in vitro structures that mimic many key aspects of the complex morphology and functions of in vivo organs such as the retina and heart. Traditional histological methods, while crucial, often fall short in analyzing these dynamic structures due to their inherently static and destructive nature. In this study, we leveraged the capabilities of optical coherence tomography (OCT) for rapid, non-invasive imaging of both retinal, cerebral, and cardiac organoids. Complementing this, we developed a sophisticated deep learning approach to automatically segment the organoid tissues and their internal structures, such as hollows and chambers. Utilizing this advanced imaging and analysis platform, we quantitatively assessed critical parameters, including size, area, volume, and cardiac beating, offering a comprehensive live characterization and classification of the organoids. These findings provide profound insights into the differentiation and developmental processes of organoids, positioning quantitative OCT imaging as a potentially transformative tool for future organoid research.

Dynamic contrast optical coherence tomography (DyC-OCT) for label-free live cell imaging

Dynamic contrast optical coherence tomography (DyC-OCT), an emerging imaging method, utilizes fluctuation patterns in OCT signals to enhance contrast, thereby enabling non-invasive label-free volumetric live cell imaging. In this mini review, we explain the core concepts behind DyC-OCT image formation and its system configurations, serving as practical guidance for future DyC-OCT users. Subsequently, we explore its applications in delivering high-quality, contrast-enhanced images of cellular morphology, as well as in monitoring changes in cellular activity/viability assay experiments.

Label-free visualization and quantification of the drug-type-dependent response of tumor spheroids by dynamic optical coherence tomography

We demonstrate label-free dynamic optical coherence tomography (D-OCT)-based visualization and quantitative assessment of patterns of tumor spheroid response to three anti-cancer drugs. The study involved treating human breast adenocarcinoma (MCF-7 cell-line) with paclitaxel (PTX), tamoxifen citrate (TAM), and doxorubicin (DOX) at concentrations of 0 (control), 0.1, 1, and 10 µM for 1, 3, and 6 days. In addition, fluorescence microscopy imaging was performed for reference. The D-OCT imaging was performed using a custom-built OCT device. Two algorithms, namely logarithmic intensity variance (LIV) and late OCT correlation decay speed (OCDS[Formula: see text]) were used to visualize the tissue dynamics. The spheroids treated with 0.1 and 1 µM TAM appeared similar to the control spheroid, whereas those treated with 10 µM TAM had significant structural corruption and decreasing LIV and OCDS[Formula: see text] over treatment time. The spheroids treated with PTX had decreasing volumes and decrease of LIV and OCDS[Formula: see text] signals over time at most PTX concentrations. The spheroids treated with DOX had decreasing and increasing volumes over time at DOX concentrations of 1 and 10 µM, respectively. Meanwhile, the LIV and OCDS[Formula: see text] signals decreased over treatment time at all DOX concentrations. The D-OCT, particularly OCDS[Formula: see text], patterns were consistent with the fluorescence microscopic patterns. The diversity in the structural and D-OCT results among the drug types and among the concentrations are explained by the mechanisms of the drugs. The presented results suggest that D-OCT is useful for evaluating the difference in the tumor spheroid response to different drugs and it can be a useful tool for anti-cancer drug testing.