The x-ray PIV method was improved for measuring quantitative velocity fields of real blood flows using a coherent synchrotron x-ray source. Without using any contrast media or seeding particles, this method can visualize flow pattern of blood by enhancing the phase-contrast and interference characteristics of blood cells based on a synchrotron x-ray imaging mechanism. The enhanced x-ray images were achieved by optimizing the sample-to-scintillator distance, the sample thickness, and hematocrit. The quantitative velocity fields of blood flows inside opaque tubes were obtained by applying a 2-frame PIV algorithm to the x-ray images of the blood flows. The measured velocity field data show typical features of blood flows such as the yield stress effect. The non-Newtonian flow characteristics of blood flows were analyzed using the x-ray PIV method and the experimental results were compared with hemodynamic models.

In this article we introduce computer models that have been developed in the past to determine the concentration of metabolic gases, the oxygen and carbon dioxide, along the pulmonary circulation. The terminal concentration of these gases in the arterial blood is related with the total change of the partial pressure of the same gases in the alveoli for the time beginning with inspiration and ending with expiration. It is affected not only by the ventilation-perfusion ratio and the gas diffusion capacity of the lung membrane but also by the pulmonary defect such as shunt, dead space, diffusion impairment and ventilation-perfusion mismatch. Some pathological pulmonary symptoms such as ARDS and CDPD can be understood through the mathematical models of these pulmonary dysfunctions. Quantitative study on the blood oxygenation process using various computer models is therefore of foremost importance in order to monitor not only the pulmonary health but also the cardiac output and cell metabolism. Reviewed in this paper include the basic and advanced methods that enable numerical study on the gas exchange and on the arterial oxygenation process, which might depend on the various heart and lung physiological conditions listed above.

Diabetes mellitus (DM) is a metabolic disorder, characterized by varying or persistent hyperglycemia, which induces several changes in the erythrocyte membrane and its cytoplasm, leading to alteration in the deformability. Techniques applied to measure this are based on filtration of erythrocyte suspension through a membrane and to obtain diffraction pattern under sheared conditions. Ektacytometry requiring less quantity of blood with disposable flow chamber used to measure the deformability of erythrocytes obtained from patients with diabetes and also associated with nephropathy and retinopathy. A decreasing trend of deformability in these patients is observed. The shape parameter form factor, as determined by image processing procedure, increases with the increased of blood glucose levels and shows a pattern similar to filtration time of erythrocyte suspensions through cellulose membranes. Further work is suggested to detect micro-level changes in cell membrane in diabetic patients

Background; Pleural micro-metastasis of lung cancer is detected by touch print cytology or pleural lavage cytology, but its prognostic impact has not elucidated yet. We hypothesize that recurrence may depend on the amount of tumor cells disseminated in pleural cavity, if the invasiveness of all cancer is the same. To predict the amount of tumor cells disseminated in pleural cavity, we need pleural surface area, distributed pattern of cells and concentration of cells per unit area. Human pleural surface area has not reported yet. In this report, we calculate the normal human pleural surface area using CT image data processing. Methods; Twenty persons were checked CT scan, and we obtained the data from each image. In order to calculate the pleural surface, the outline of lung was firstly extruded from CT image data using home-made Digitizer program. And the distance between CT images was calculated from the extruded outline. Finally a normal human pleural surface was calculated from function between the distance of consecutive CT images and the calculated length. Results; Their mean age is $65{\pm}12$ years old (range $26{\sim}77$), body weight is $62{\pm}9\;kg\;(48{\sim}80)$, and height is $167{\pm}6\;cm\;(156{\sim}176)$. The number of images used is $36{\pm}7\;(24{\sim}51)$. Pleural surface area is $211,888{\pm}35,756\;mm^2\;(143,880{\sim}279,576)$. Right-side pleural surface area is $107,932\;mm^2$ and Lt is $103,955\;mm^2$. Costal, mediastinal and diaphragmatic surfaces of right-side pleura are $77,483\;mm^2,\;39,057\;mm^2,\;and\;8,608\;mm^2$ respectively, and left-side are $72,497\;mm^2,\;35,578\;mm^2,\;and\;4,120\;mm^2$ respectively. Conclusion; Normal human pleural surface area is calculated using CT image data at first and the result is about $0.212\;m^2$.