Monitoring oxygen saturation (SO2) in microcirculation is effective for understanding disease dynamics. We have developed an SO2 estimation method, sidestream dark-field (SDF) oximetry, based on SDF imaging. SDF imaging is a noninvasive and clinically applicable technique to observe microcirculation. We report the first in vivo experiment observing the changes in SO2 of microcirculation using SDF oximetry. First, heat from the light-emitting diodes used for the SDF imaging might affect hemodynamics in microcirculation, hence, we performed an experiment to evaluate the influence of that on the SDF oximetry. The result suggested that SDF oximetry had enough stability for long-term experiments. Then, to evaluate the sensitivity of SDF oximetry to alterations in the hemodynamics of the microcirculation, we observed the time-lapsed SO2 changes in the dermis microcirculation of rats under hypoxic stimulation. We confirmed that the SO2 estimated by SDF oximetry was in accordance with changes in the fraction of inspired oxygen (FiO2). Thus, SDF oximetry is considered to be able to observe SO2 changes that occur in accordance with alteration of the microcirculation.
The sidestream dark-field (SDF) imaging allows direct visualization of red blood cells in microvessels near tissue surfaces. We have developed an image-based oximetry method using two-band images obtained by SDF imaging (SDF oximetry) and a trial SDF device with light-emitting diodes to obtain band images. In this study, we propose a technique of producing oxygen saturation (SO<sub>2</sub>) maps from SDF images and perform animal experiments in vivo. To produce SO<sub>2</sub> maps, we use spectral analysis using two band images obtained with our SDF device. As an image processing, the combination of both the Hessian-based and pixel value-based techniques as blood vessel extraction from an SDF image is used. From the experiment with the surface of rat small intestines, we can produce SO<sub>2</sub> maps and find that the map represents arterioles and venules those were determined based on the blood ow from SDF images. Moreover, we find the variation of SO<sub>2</sub> along a blood vessel running direction.
Septic shock induces organ dysfunction by microcirculatory disturbance. Observation and quantification of microcirculation are expected to be effective for the diagnosis of septic shock. Sidestream dark-filed (SDF) imaging is a suitable technique for observation of microcirculation. It can noninvasively visualize red blood cells (RBCs) of microcirculation. We are developing early diagnostic criteria for septic shock from microcirculation SDF images. As an initial study, we use the blood flow velocity estimated from the images as a diagnostic criteria. However, low contrast quality and subject’s movement disturb the blood flow velocity estimation. In this paper, we present a procedure of image processing for a stable estimation of the blood flow velocity. In the procedure, we first perform a robust principal component analysis (RPCA) as a preprocessing. RPCA decomposes a motion picture into a low-rank (L) component and a sparse (S) component. The S component images clearly expresses RBCs flow and is used for the velocity estimation. The temporal change of the intensity profile along the vessel was analyzed by Hough transform to estimate the blood flow velocity is. The proposed procedure was examined with dorsal microcirculation of septic model rats and a sham rat. As a result, the decrease in blood flow velocity of the septic rats after 17 hours was greater than that of the sham. It was also suggested that blood flow velocity might be faster index of septic shock reaction earlier than lactic acid value. These results suggest that the velocity estimation is reasonable for diagnosis of septic shock.