Hyeokjun Byeon

Effect of diabetic duration on hemorheological properties and platelet aggregation in streptozotocin-induced diabetic rats

Diabetes mellitus with abnormal glucose concentration is associated with changes in hemorheological properties, endothelial function, and platelets hyperactivity. Disturbances may significantly be responsible for diabetes-related vascular complications. In this study, hemorheological and hemodynamic properties were measured according to diabetic duration after streptozotocin treatment in rats. For ex vivo measurements, an extracorporeal model was adopted. Flow rate and blood viscosity were measured using a microfluidic device. Erythrocyte aggregation and morphological parameters of erythrocytes were measured by modified erythrocyte sedimentation rate and the phase-contrast holography under in vitro conditions. The platelet aggregation and mean pressure in the femoral artery were estimated under ex vivo conditions. Hemorheological properties including blood viscosity, erythrocyte aggregation and shape parameters for the control group are significantly different with those for diabetic groups. The changes with respect to diabetic duration were relatively unnoticeable. However, the platelet aggregation is strongly dependent on the diabetic duration. Based on these results, hyperglycemia exposure may induce hemorheological variations in early stages of diabetes mellitus. High platelet aggregation may become more pronounced according to the diabetic duration caused by variations in hemorheological properties resulting in endothelial dysfunction. This study would be helpful in understanding the effects of diabetic duration on biophysical properties.

Focusing and alignment of erythrocytes in a viscoelastic medium

Viscoelastic fluid flow-induced cross-streamline migration has recently received considerable attention because this process provides simple focusing and alignment over a wide range of flow rates. The lateral migration of particles depends on the channel geometry and physicochemical properties of particles. In this study, digital in-line holographic microscopy (DIHM) is employed to investigate the lateral migration of human erythrocytes induced by viscoelastic fluid flow in a rectangular microchannel. DIHM provides 3D spatial distributions of particles and information on particle orientation in the microchannel. The elastic forces generated in the pressure-driven flows of a viscoelastic fluid push suspended particles away from the walls and enforce erythrocytes to have a fixed orientation. Blood cell deformability influences the lateral focusing and fixed orientation in the microchannel. Different from rigid spheres and hardened erythrocytes, deformable normal erythrocytes disperse from the channel center plane, as the flow rate increases. Furthermore, normal erythrocytes have a higher angle of inclination than hardened erythrocytes in the region near the side-walls of the channel. These results may guide the label-free diagnosis of hematological diseases caused by abnormal erythrocyte deformability.

Precise measurement of orientations of transparent ellipsoidal particles through digital holographic microscopy.

A method to measure the orientations of transparent ellipsoidal particles using digital holographic microscopy (DHM) is proposed in this study. This approach includes volumetric recording and numerical reconstruction at different depths. Distinctive light scatterings from an ellipsoid with different angles of orientation are analyzed. A focus function is applied to obtain a reconstructed image that contains a bright line parallel to the major axis of the projected particle, which provides in-plane orientation information. An intensity profile is collected along the major axis of the projected particle in the direction of the optical axis, and this profile is then utilized to measure the out-of-plane orientation of the ellipsoid. After being verified for an ellipsoid with known orientations, the proposed method is applied to ellipsoids suspended in a pipe flow with random orientations. This DHM method can extract the essential information of ellipsoids and therefore has great potential applications in particle dynamics.

Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning

Cell types of erythrocytes should be identified because they are closely related to their functionality and viability. Conventional methods for classifying erythrocytes are time consuming and labor intensive. Therefore, an automatic and accurate erythrocyte classification system is indispensable in healthcare and biomedical fields. In this study, we proposed a new label-free sensor for automatic identification of erythrocyte cell types using a digital in-line holographic microscopy (DIHM) combined with machine learning algorithms. A total of 12 features, including information on intensity distributions, morphological descriptors, and optical focusing characteristics, is quantitatively obtained from numerically reconstructed holographic images. All individual features for discocytes, echinocytes, and spherocytes are statistically different. To improve the performance of cell type identification, we adopted several machine learning algorithms, such as decision tree model, support vector machine, linear discriminant classification, and k-nearest neighbor classification. With the aid of these machine learning algorithms, the extracted features are effectively utilized to distinguish erythrocytes. Among the four tested algorithms, the decision tree model exhibits the best identification performance for the training sets (n = 440, 98.18%) and test sets (n = 190, 97.37%). This proposed methodology, which smartly combined DIHM and machine learning, would be helpful for sensing abnormal erythrocytes and computer-aided diagnosis of hematological diseases in clinic.

Holographic analysis on deformation and restoration of malaria-infected red blood cells by antimalarial drug

Abstract. Malaria parasites induce morphological, biochemical, and mechanical changes in red blood cells (RBCs). Mechanical variations are closely related to the deformability of individual RBCs. The deformation of various RBCs, including healthy and malaria-infected RBCs (iRBCs), can be directly observed through quantitative phase imaging (QPI). The effects of chloroquine treatment on the mechanical property variation of iRBCs were investigated using time-resolved holographic QPI of single live cells on a millisecond time scale. The deformabilities of healthy RBCs, iRBCs, and drug-treated iRBCs were compared, and the effect of chloroquine on iRBC restoration was experimentally examined. The present results are beneficial to elucidate the dynamic characteristics of iRBCs and the effect of the antimalarial drug on iRBCs.

Machine learning-based in-line holographic sensing of unstained malaria-infected red blood cells

Accurate and immediate diagnosis of malaria is important for medication of the infectious disease. Conventional methods for diagnosing malaria are time consuming and rely on the skill of experts. Therefore, an automatic and simple diagnostic modality is essential for healthcare in developing countries that lack the expertise of trained microscopists. In the present study, a new automatic sensing method using digital in-line holographic microscopy (DIHM) combined with machine learning algorithms was proposed to sensitively detect unstained malaria-infected red blood cells (iRBCs). To identify the RBC characteristics, 13 descriptors were extracted from segmented holograms of individual RBCs. Among the 13 descriptors, 10 features were highly statistically different between healthy RBCs (hRBCs) and iRBCs. Six machine learning algorithms were applied to effectively combine the dominant features and to greatly improve the diagnostic capacity of the present method. Among the classification models trained by the 6 tested algorithms, the model trained by the support vector machine (SVM) showed the best accuracy in separating hRBCs and iRBCs for training (n = 280, 96.78%) and testing sets (n = 120, 97.50%). This DIHM-based artificial intelligence methodology is simple and does not require blood staining. Thus, it will be beneficial and valuable in the diagnosis of malaria.

Hybrid bright-field and hologram imaging of cell dynamics

Volumetric observation is essential for understanding the details of complex biological phenomena. In this study, a bright-field microscope, which provides information on a specific 2D plane, and a holographic microscope, which provides information spread over 3D volumes, are integrated to acquire two complementary images simultaneously. The developed system was successfully applied to capture distinct T-cell adhesion dynamics on inflamed endothelial layers, including capture, rolling, crawling, transendothelial migration, and subendothelial migration.

Flow characteristics around a deformable stenosis under pulsatile flow condition

A specific portion of a vulnerable stenosis is deformed periodically under a pulsatile blood flow condition. Detailed analysis of such deformable stenosis is important because stenotic deformation can increase the likelihood of rupture, which may lead to sudden cardiac death or stroke. Various diagnostic indices have been developed for a nondeformable stenosis by using flow characteristics and resultant pressure drop across the stenosis. However, the effects of the stenotic deformation on the flow characteristics remain poorly understood. In this study, the flows around a deformable stenosis model and two different rigid stenosis models were investigated under a pulsatile flow condition. Particle image velocimetry was employed to measure flow structures around the three stenosis models. The deformable stenosis model was deformed to achieve high geometrical slope and height when the flow rate was increased. The deformation of the stenotic shape enhanced jet deflection toward the opposite vessel wall of the...