White-light quantitative phase imaging unit

Baek, YoonSeok; Lee, KyeoReh; Yoon, Jonghee; K, Kim; Park, YongKeun

doi:10.1364/oe.24.009308

Cited by 59 publications

(26 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A miniaturised QPI unit 57–59 can convert conventional bright field microscopy into a QPI system by simply attaching the unit to a microscope body with light source adjustment. QPI techniques employing DMD-based illumination schemes 60 or graphic-processing units 61 allow real-time visualisation of a 3-D microscopic object, and are expected to become an attractive imaging tool for investigating live cell dynamics.…”

Section: Resultsmentioning

confidence: 99%

Refractive index tomograms and dynamic membrane fluctuations of red blood cells from patients with diabetes mellitus

Lee

Park

et al. 2017

Sci Rep

Self Cite

View full text Add to dashboard Cite

In this paper, we present the optical characterisations of diabetic red blood cells (RBCs) in a non-invasive manner employing three-dimensional (3-D) quantitative phase imaging. By measuring 3-D refractive index tomograms and 2-D time-series phase images, the morphological (volume, surface area and sphericity), biochemical (haemoglobin concentration and content) and mechanical (membrane fluctuation) parameters were quantitatively retrieved at the individual cell level. With simultaneous measurements of individual cell properties, systematic correlative analyses on retrieved RBC parameters were also performed. Our measurements show there exist no statistically significant alterations in morphological and biochemical parameters of diabetic RBCs, compared to those of healthy (non-diabetic) RBCs. In contrast, membrane deformability of diabetic RBCs is significantly lower than that of healthy, non-diabetic RBCs. Interestingly, non-diabetic RBCs exhibit strong correlations between the elevated glycated haemoglobin in RBC cytoplasm and decreased cell deformability, whereas diabetic RBCs do not show correlations. Our observations strongly support the idea that slow and irreversible glycation of haemoglobin and membrane proteins of RBCs by hyperglycaemia significantly compromises RBC deformability in diabetic patients.

show abstract

Section: Resultsmentioning

confidence: 99%

Refractive index tomograms and dynamic membrane fluctuations of red blood cells from patients with diabetes mellitus

Lee

Park

et al. 2017

Sci Rep

Self Cite

View full text Add to dashboard Cite

show abstract

“…With capabilities enabling quantitative measurements of individual microscopic cells under biocompatible conditions, we envision that QPI methodologies could shed light on unresolved areas of diabetes mellitus. A miniaturised QPI unit [57][58][59] can convert conventional bright field microscopy into a QPI system by simply attaching the unit to a microscope body with light source adjustment. QPI techniques employing DMD-based illumination schemes 60 or graphic-processing units 61 allow real-time visualisation of a 3-D microscopic object, and are expected to become an attractive imaging tool for investigating live cell dynamics.…”

Section: Resultsmentioning

confidence: 99%

Refractive Index Tomograms and Dynamic Membrane Fluctuations of Red Blood Cells from Patients with Diabetes Mellitus

Lee

Park

Jang

et al. 2016

Blood

View full text Add to dashboard Cite

Background: Diabetic effects on blood rheology are important topics and have been extensively investigated. In particular, it has been known that diabetic RBCs exhibit significantly deteriorated deformability compared to healthy RBCs. Despite the importance of previously measured mechanical properties of diabetic RBCs, several problems remain to be elucidated. First, conventional techniques have difficulties in measuring intrinsic properties of individual cells. Detailed quantification of diabetic alteration in RBCs at the individual cell level is also hard to achieve. Accordingly, previous approaches do not allow the systematical correlative analyses to be performed on simultaneously measured various cell parameters. As a consequence, there are still no general agreements on the integrated effects of diabetic complications or hyperglycemia on individual human RBCs. Methods: To effectively settle the arisen problems, we quantitatively and non-invasively measured the individual RBCs from diabetic and healthy blood donors to figure out the characteristics of diabetic RBCs by employing the quantitative phase imaging (QPI) technique. From the reconstructed three-dimensional (3-D) refractive index (RI) tomogram and the time-series of 2-D phase map of individual RBCs, the morphological (volume, surface area, and sphericity), biochemical (Hb concentration and Hb content), and mechanical (membrane fluctuation) parameters were retrieved. Systematic correlative analyses among measured six RBC parameters and independently determined HbA1c level, defined as the ratio of HbA1c to total Hb, were also performed. In measuring red cells, only gently sedimented RBCs of discocytes were selected. After excluding erroneously measured RBCs, 40, 40, 40, 38, 39, 40 control RBCs of six healthy donors and 40, 40, 40, 40, 40, 40 diabetic RBCs of six diabetic patients were finally analyzed respectively for the study of diabetic effects on characteristics of individual human RBCs. Results: HbA1c level is defined as a percentage of HbA1c, the majority of glycated Hbs in RBC, to total Hb contents in blood. Because HbA1c is formed through 120-days long, non-enzymatic glycation process of Hb, HbA1c level has been perceived as an effective mean to estimate mean glucose concentration of individuals for the last three months. In other words, HbA1c reflects the degree of hyperglycemia. The most noticeable alterations in diabetic RBCs can be found when mean RBC membrane fluctuations of individuals are rearranged in the increasing order of the measured HbA1c levels. The mean values of membrane fluctuations for RBCs are 59.7 ¡¾ 6.2, 58.3 ¡¾ 4.9, 55.0 ¡¾ 5.4, 57.1 ¡¾ 7.4, 51.0 ¡¾ 6.8, and 49.6 ¡¾ 4.6 nm for healthy volunteers, and 45.1 ¡¾ 4.0, 46.9 ¡¾ 3.4, 48.8 ¡¾ 4.0, 47.6 ¡¾ 4.2, 43.0 ¡¾ 4.1, and 48.0 ¡¾ 5.0 nm for diabetic patients, in order of increasing HbA1c. As shown in Fig. 4, mean membrane fluctuation of non-diabetic RBCs tends to decrease as the HbA1c level increases (Pearson correlation coefficient of -0.87 with a p-value of 0.02). Beyond this level of HbA1c, RBCs from diabetic patients exhibit significantly decreased and settled membrane fluctuation. This observed negative correlation between RBC membrane fluctuation and HbA1 is also conceptually in accordance with the report of the previous study. Conclusions: We quantitatively and non-invasively characterize the morphological, biochemical, and mechanical alterations of individual RBCs by diabetes mellitus. HbA1c levels of subjects, which reflect one's mean blood glucose concentration of last three months, were also determined using hematology analyzers. Accordingly, correlative analyses among the retrieved individual RBC parameters and HbA1c level were performed to search unique features which cannot be addressed by conventional techniques with incapability of simultaneous measurement of those parameters. Figure Box plot of membrane fluctuation for measured RBCs from six healthy controls and diabetic patients in increasing order of HbA1c. Boxes, median values with upper and lower quartiles. Short horizontal lines and error bars in each box plot denote the mean values and standard deviations, respectively. Figure. Box plot of membrane fluctuation for measured RBCs from six healthy controls and diabetic patients in increasing order of HbA1c. Boxes, median values with upper and lower quartiles. Short horizontal lines and error bars in each box plot denote the mean values and standard deviations, respectively. Disclosures No relevant conflicts of interest to declare.

show abstract

“…The second limitation is that only fluids with distinct RI values can be visualized; fluids with similar RI values may be difficult to image with quantitative phase microscopes, which have a limited phase sensitivity, especially when speckle noise exists. However, this phase sensitivity issue can be remedied by exploiting low-coherent light, such as white light illumination or speckle illumination [34][35][36][37]. Third, different fluids with the same RI values cannot be distinguished with the present method because this approach does not provide molecular specificity.…”

Section: Discussionmentioning

confidence: 97%

Visualization and label-free quantification of microfluidic mixing using quantitative phase imaging

et al. 2017

Self Cite

View full text Add to dashboard Cite

Microfluidic mixing plays a key role in various fields, including biomedicine and chemical engineering. To date, although various approaches for imaging microfluidic mixing have been proposed, they provide only quantitative imaging capability and require exogenous labeling agents. Quantitative phase imaging techniques, however, circumvent these problems and offer label-free quantitative information about concentration maps of microfluidic mixing. We present the quantitative phase imaging of microfluidic mixing in various types of polydimethylsiloxane microfluidic channels with different geometries; the feasibility of the present method was validated by comparing it with the results obtained by theoretical calculation based on Fick's law.

show abstract

White-light quantitative phase imaging unit

Cited by 59 publications

References 38 publications

Refractive index tomograms and dynamic membrane fluctuations of red blood cells from patients with diabetes mellitus

Refractive index tomograms and dynamic membrane fluctuations of red blood cells from patients with diabetes mellitus

Refractive Index Tomograms and Dynamic Membrane Fluctuations of Red Blood Cells from Patients with Diabetes Mellitus

Visualization and label-free quantification of microfluidic mixing using quantitative phase imaging

Contact Info

Product

Resources

About