Quantitative Differential Interference Contrast Microscopy Research Articles

Single-exposure quantitative differential interference contrast microscopy using bandlimited image and its Fourier transform constraints

Phase microscopy that records the bandlimited image and its Fourier image simultaneously (BIFT) is a phase retrieval method with unique and rapid convergence. In this paper, we present a single-exposure quantitative differential interference contrast (DIC) microscopy based on BIFT method. The contrasts of the recorded DIC image and its Fourier image, analyzed by simulation and experiment, can be largely improved by the initial phase difference between two sheared lights (bias), however their trends with biases are opposite. By adding the optimized bias with the compromise of the contrasts in image and Fourier space, the phase sensitivity can be improved than BIFT method only. We have experimentally demonstrated that a sample of 25 nm height can be successfully recovered from a single exposure. The presented single-exposure quantitative DIC microscopy provides a promising technique for real-time phase imaging.

Sizing individual dielectric nanoparticles with quantitative differential interference contrast microscopy.

We report a method to measure the size of single dielectric nanoparticles with high accuracy and precision using quantitative differential interference contrast (DIC) microscopy. Dielectric nanoparticles are detected optically by the conversion of the optical phase change into an intensity change using DIC. Phase images of individual nanoparticles were retrieved from DIC by Wiener filtering, and a quantitative methodology to extract nanoparticle sizes was developed. Using polystyrene beads of 100 nm radius as size standard, we show that the method determines this radius within a few nm accuracy. The smallest detectable polystyrene bead is limited by background and shot-noise, which depend on acquisition and analysis parameters, including the objective numerical aperture, the DIC phase offset, and the refractive index contrast between particles and their surrounding. Measurements on small beads of 15 nm nominal radius are shown, and a sensitivity limit potentially reaching down to 1.8 nm radius was inferred. As application example, individual nanodiamonds with nominal sizes below 50 nm were measured, and were found to have a nearly exponential size distribution with 28 nm mean value. Considering the importance of dielectric nanoparticles in many fields, from naturally occurring virions to polluting nanoplastics, the proposed method could offer a powerful quantitative tool for nanoparticle analysis, combining accuracy, sensitivity and high-throughput with widely available and easy-to-use DIC microscopy.

Self-compensating quantitative differential interference contrast microscopy imaging system using liquid crystal shearing assembly

A quantitative differential interference contrast microscopy (DICM) using a liquid crystal shearing assembly (LCSA) is proposed and demonstrated experimentally. Differential interference contrast (DIC) imaging with arbitrary shearing amount and different shearing direction can be implemented by changing the driving voltage applied to the liquid crystal without mechanical devices. Moreover, by combining a quarter-wave plate and a mirror, not only the shearing amount is enlarged, but also the aberration and the additional phase shift induced by the refractive index difference between ordinary and extraordinary light can be compensated. Using the proposed LCSA/DICM system, we implement DIC imaging of a polystyrene microsphere crown and the quantitative differential phase measurement of an oral epithelial cell.

RETRACTED: Study of strain-driven martensitic phase transformation rate via data-driven approach

Abstract In the kinetic studies of martensitic phase transformation, the propagation velocity of the phase boundary is considered as the speed of transformation. But there is no interface at the beginning of phase transformation, we cannot track the development of the interface. Here we propose a new mathematical model that describes the rate of martensitic transformation by the data-driven method, which is based on the study of the change in area fraction in each phase. In this paper, the K-means clustering method is used to classify martensite and austenite through advanced quantitative differential interference contrast microscopy system. After classification, the clustering results are in good agreement with microscopic observations. The phase transformation rate for a set of tensile tests under various strain rates is determined. Our work provides a useful reference for modeling the strain-driven martensitic transformation rate.

Lipid Bilayer Thickness Measured by Quantitative DIC Reveals Phase Transitions and Effects of Substrate Hydrophilicity.

Quantitative differential interference contrast microscopy is demonstrated here as a label-free method, which is able to image and measure the thickness of lipid bilayers with 0.1 nm precision. We investigate the influence of the substrate on the thickness of fluid-phase 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC)-supported lipid bilayers and find a thinning of up to 10%, depending on substrate hydrophilicity, local bilayer coverage, and ionic strength of the medium. With fluorescently labeled lipid bilayers, we also observe changes in the bilayer thickness depending on the choice of fluorophore. Furthermore, liquid-ordered domains in bilayers, formed from DOPC, cholesterol, and sphingomyelin, are measured, and the corresponding thickness change between the liquid-ordered and liquid-disordered phases is accurately determined. Again, the thickness difference is found to be dependent on the presence of the fluorophore label, highlighting the need for quantitative label-free techniques.

Lung cancer diagnosis with quantitative DIC microscopy and a deep convolutional neural network.

We present a study on lung squamous cell carcinoma diagnosis using quantitative TI-DIC microscopy and a deep convolutional neural network (DCNN). The 2-D phase map of unstained tissue sections is first retrieved from through-focus differential interference contrast (DIC) images based on the transport of intensity equation (TIE). The spatially resolved optical properties are then computed from the 2-D phase map via the scattering-phase theorem. The scattering coefficient ( ) and the reduced scattering coefficient ( ) are found to increase whereas the anisotropy factor (g) is found to decrease with cancer. A DCNN classifier is developed afterwards to classify the tissue using either the DIC images or 2-D optical property maps of , and g. The DCNN classifier with the optical property maps exhibits high accuracy, significantly outperforming the same DCNN classifier on the DIC images. The label-free quantitative phase microscopy together with deep learning may emerge as a promising approach for in situ rapid cancer diagnosis.

Principal component analysis-based quantitative differential interference contrast microscopy.

Classical differential interference contrast (DIC) microscopy is an excellent tool for rendering high-contrast images to observe transparent specimen. Though the monochromatic shadow-cast image qualitatively reflects the specimen configuration, its phase can hardly be extracted, inevitably limiting its application in quantitative measurements. In order to extend its application, we propose a quantitative DIC (qDIC) microscopy technique, which can extract the specimen phase from phase-shifting beam-shearing interference images combining principal component analysis (PCA) and phase integration methods. Proved by both simulations and experiments, the PCA-based qDIC microscopy can rapidly and accurately retrieve the quantitative specimen phase. The new proposed technique shares with conventional DIC the advantage of high-contrast imaging, especially for transparent label-free specimens, but transforms DIC microscopy into a quantitative phase microscopy technique. We envision PCA-based qDIC microscopy as a future quantitative biological imaging modality.

Optical Quantification of Cellular Mass, Volume, and Density of Circulating Tumor Cells Identified in an Ovarian Cancer Patient

Clinical studies have demonstrated that circulating tumor cells (CTCs) are present in the blood of cancer patients with known metastatic disease across the major types of epithelial malignancies. Recent studies have shown that the concentration of CTCs in the blood is prognostic of overall survival in breast, prostate, colorectal, and non-small cell lung cancer. This study characterizes CTCs identified using the high-definition (HD)-CTC assay in an ovarian cancer patient with stage IIIC disease. We characterized the physical properties of 31 HD-CTCs and 50 normal leukocytes from a single blood draw taken just prior to the initial debulking surgery. We utilized a non-interferometric quantitative phase microscopy technique using brightfield imagery to measure cellular dry mass. Next we used a quantitative differential interference contrast microscopy technique to measure cellular volume. These techniques were combined to determine cellular dry mass density. We found that HD-CTCs were more massive than leukocytes: 33.6 ± 3.2 pg (HD-CTC) compared to 18.7 ± 0.6 pg (leukocytes), p < 0.001; had greater volumes: 518.3 ± 24.5 fL (HD-CTC) compared to 230.9 ± 78.5 fL (leukocyte), p < 0.001; and possessed a decreased dry mass density with respect to leukocytes: 0.065 ± 0.006 pg/fL (HD-CTC) compared to 0.085 ± 0.004 pg/fL (leukocyte), p < 0.006. Quantification of HD-CTC dry mass content and volume provide key insights into the fluid dynamics of cancer, and may provide the rationale for strategies to isolate, monitor or target CTCs based on their physical properties. The parameters reported here can also be incorporated into blood cell flow models to better understand metastasis.

Combination of Raman tweezers and quantitative differential interference contrast microscopy for measurement of dynamics and heterogeneity during the germination of individual bacterial spores

Raman tweezers and quantitative differential interference contrast (DIC) microscopy are combined to monitor the dynamic germination of individual bacterial spores of Bacillus species, as well as the heterogeneity in this process. The DIC bias phase is set properly such that the brightness of DIC images of individual spores is proportional to the dipicolinic acid (DPA) level of the spores, and an algorithm is developed to retrieve the phase image of an individual spore from its DIC image. We find that during germination, the rapid drop in both the intensity of the original DIC image and the intensity of the reconstructed phase image precisely corresponds to the release of all DPA from that spore. The summed pixel intensity of the DIC image of individual spores adhered on a microscope coverslip is not sensitive to the drift of the slide in both horizontal and vertical directions, which facilitates observation of the germination of thousands of individual spores for long periods of time. A motorized stage and synchronized image acquisition system is further developed to effectively expand the field of view of the DIC imaging. This quantitative DIC technique is used to track the germination of hundreds or thousands of individual spores simultaneously.

Quantitative differential interference contrast microscopy based on structured-aperture interference

We report a quantitative differential interference contrast (DIC) microscope based on a structured-aperture (SA) wavefront sensor. Unlike a conventional DIC microscope, the SA-DIC microscope can separate the amplitude and the phase gradient information of the image wavefront, and form quantitative intensity and DIC images of the sample with good resolution; our prototype achieved resolution ∼2 μm. Furthermore, due to the nonpolarization nature of the microscope, we were able to image birefringent samples without artifacts.