We proposed a neural network to generate volumetric dynamic optical coherence tomography (DOCT) from small-number OCT frames. In this study, we used a DOCT method (i.e., logarithmic OCT intensity variance; LIV) and it is applied to tumor spheroid samples. A U-Net-based NN model was trained to generate a LIV image from only 4 OCT frames. The NN-generated LIV was subjectively and objectively compared with conventional LIV images generated from 32 frames. The comparison showed a high similarity between the NN-generated LIV and the conventional LIV. This NN-based method enabled volumetric DOCT with only 6.55 s acquisition time.
We demonstrate longitudinal drug response imaging of tumor spheroids by integrating a spheroid cultivation chamber and the dynamic optical coherence tomography (DOCT) system. The cultivation chamber supports the spheroids with 5 % of CO2 and a temperature of 37 0C. In contrast to our previous cross-sectional time-course imaging method, this newly integrated system enabled longitudinal time-course imaging of a single sample, and hence enabled measuring large number of time-points of the same spheroid. It successfully revealed the temporal property of human breast cancer (MCF-7 cell-line) spheroid’s response to paclitaxel (PTX) and doxorubicin (DOX) with high-temporal-resolution.
Dynamic optical coherence tomography (DOCT) is a method to visualize intratissue activities by analyzing the time sequence of OCT images. We previously established two DOCT contrasts, logarithmic intensity variance (LIV) and late OCT correlation decay speed (OCDSl), and applied them to several medical and pharmaceutical studies. However, these DOCT contrasts have two problems, which are a measurement time dependency of LIV and a difficulty of interpretation of OCDSl. Here we present a new DOCT algorithm which solves these two problems. The new method first computes several LIV values with multiple time window sizes. This LIV shows a monotonically increasing saturation curve. The saturation level and saturation speed, which are named authentic LIV (ALIV) and swiftness, are obtained by fitting the LIVs with a saturation function. Numerical simulation revealed that ALIV is sensitive to the occupancy of the dynamic scatterers over all dynamic and static scatterers, while swiftness is sensitive to the speed of the dynamic scatterers. According to the principle and experimental results using tumor spheroids, ALIV and swiftness are more quantitative and easier to interpret than our previous DOCT methods.
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