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Retrieving electrical impedance maps at the nanoscale rapidly via nondestructive inspection with a high signal-to-noise ratio is an unmet need, likely to impact various applications from biomedicine to energy conversion. In this study, we develop a multimodal functional imaging instrument that is characterized by the dual capability of impedance mapping and phase quantitation, high spatial resolution, and low temporal noise. To achieve this, we advance a quantitative phase imaging system, referred to as epi-magnified image spatial spectrum microscopy combined with electrical actuation, to provide complementary maps of the optical path and electrical impedance. We demonstrate our system with high-resolution maps of optical path differences and electrical impedance variations that can distinguish nanosized, semi-transparent, structured coatings involving two materials with relatively similar electrical properties. We map heterogeneous interfaces corresponding to an indium tin oxide layer exposed by holes with diameters as small as ~550 nm in a titanium (dioxide) over-layer deposited on a glass support. We show that electrical modulation during the phase imaging of a macro-electrode is decisive for retrieving electrical impedance distributions with submicron spatial resolution and beyond the limitations of electrode-based technologies (surface or scanning technologies). The findings, which are substantiated by a theoretical model that fits the experimental data very well enable achieving electro-optical maps with high spatial and temporal resolutions. The virtues and limitations of the novel optoelectrochemical method that provides grounds for a wider range of electrically modulated optical methods for measuring the electric field locally are critically discussed., Microscopy: phased-in approach puts nanoscale electrical impedance on the map A microscope capable of real-time, label-free analysis of nanoscale structures and their associated electrical properties could find applications in both biology and materials science. High-resolution microscopy methods that detect variations in the phase of a laser as it passes through samples are helping researchers overcome the limits of traditional optical imaging. In a joint effort, the groups led by Eugen Gheorghiu from the International Centre of Biodynamics in Bucharest, Romania, and by Gabriel Popescu from the University of Illinois at Urbana Champaign have now developed an instrument that combines phase imaging with alternating voltage perturbations to measure a target’s refractive index and electrical impedance maps that can reveal properties including tumors in human tissue, or defects on coating surfaces. The team’s microscope proved capable of distinguishing the impedance contrasts and geometry of different nanostructures on a macroelectrode with submicron resolution.

Histological staining of tissue samples is one of the most helpful tools in diagnosing and prognosing various cancers. However, in order to prepare the slide for a histopathologist to examine, the tissue must first undergo a series of time-consuming processes, such as a staining technique to visually differentiate features in the sample. In this study, we use a label-free method to generate a virtually-stained microscopic image using a single spatial light interference microscopy (SLIM) image of an unlabeled tissue sample, therefore eliminating the need for standard histochemical administration. This novel approach will render histopathological practices faster and more cost-effective, while providing medically relevant dry mass information associated with SLIM images.

Breast cancer is the most common type of cancer among women worldwide. The standard histopathology of breast tissue, the primary means of disease diagnosis, involves manual microscopic examination of stained tissue by a pathologist. Because this method relies on qualitative information, it can result in inter-observer variation. Furthermore, for difficult cases the pathologist often needs additional markers of malignancy to help in making a diagnosis, a need that can potentially be met by novel microscopy methods. We present a quantitative method for label-free breast tissue evaluation using Spatial Light Interference Microscopy (SLIM). By extracting tissue markers of malignancy based on the nanostructure revealed by the optical path-length, our method provides an objective, label-free and potentially automatable method for breast histopathology. We demonstrated our method by imaging a tissue microarray consisting of 68 different subjects −34 with malignant and 34 with benign tissues. Three-fold cross validation results showed a sensitivity of 94% and specificity of 85% for detecting cancer. Our disease signatures represent intrinsic physical attributes of the sample, independent of staining quality, facilitating classification through machine learning packages since our images do not vary from scan to scan or instrument to instrument.

Tissue biopsy evaluation in the clinic is in need of quantitative disease markers for diagnosis and, most importantly, prognosis. Among the new technologies, quantitative phase imaging (QPI) has demonstrated promise for histopathology because it reveals intrinsic tissue nanoarchitecture through the refractive index. However, a vast majority of past QPI investigations have relied on imaging unstained tissues, which disrupts the established specimen processing. Here we present color spatial light interference microscopy (cSLIM) as a new whole-slide imaging modality that performs interferometric imaging on stained tissue, with a color detector array. As a result, cSLIM yields in a single scan both the intrinsic tissue phase map and the standard color bright-field image, familiar to the pathologist. Our results on 196 breast cancer patients indicate that cSLIM can provide stain-independent prognostic information from the alignment of collagen fibers in the tumor microenvironment. The effects of staining on the tissue phase maps were corrected by a mathematical normalization. These characteristics are likely to reduce barriers to clinical translation for the new cSLIM technology.

Phase-contrast microscopy converts the phase shift of light passing through a transparent specimen, e.g., a biological cell, into brightness variations in an image. This ability to observe structures without destructive fixation or staining has been widely utilized for applications in materials and life sciences. Despite these advantages, phase-contrast microscopy lacks the ability to reveal molecular information. To address this gap, we developed a bond-selective transient phase (BSTP) imaging technique that excites molecular vibrations by infrared light, resulting in a transient change in phase shift that can be detected by a diffraction phase microscope. By developing a time-gated pump–probe camera system, we demonstrate BSTP imaging of live cells at a 50 Hz frame rate with high spectral fidelity, sub-microsecond temporal resolution, and sub-micron spatial resolution. Our approach paves a new way for spectroscopic imaging investigation in biology and materials science., Imaging: probing chemical bonds A phase imaging technique that provides spectroscopic chemical information could bring new opportunities for studying biology and materials science. Delong Zhang, Lu Lan, and coworkers from Boston, Illinois and Shanghai have developed a scheme called bond-selective transient phase (BSTP) imaging. The approach uses nanosecond pulses of mid-infrared pump laser light to excite molecular vibrations in the sample. The mid-infrared light absorption causes a small temperature change in the sample which results in a change of refractive index and thus a transient phase shift, which is read out by a burst of visible probe pulses and a CMOS camera. Tests with samples including a thin oil film, polyurethane beads, living cells, and the interface between two liquids (olive oil and dimethyl sulfoxide) indicate that BSTP imaging can operate with sub-microsecond temporal resolution and sub-micrometer spatial resolution.

We propose a new intrinsic cancer marker in fixed tissue biopsy slides, which is based on the local spatial autocorrelation length obtained from quantitative phase images. The spatial autocorrelation length in a small region of the tissue phase image is sensitive to the nanoscale cellular morphological alterations and can hence inform on carcinogenesis. Therefore, this metric can potentially be used as an intrinsic cancer marker in histopathology. Typically, these correlation length maps are calculated by computing 2D Fourier transforms over image sub-regions – requiring long computational times. In this paper, we propose a more time efficient method of computing the correlation map and demonstrate its value for diagnosis of benign and malignant breast tissues. Our methodology is based on highly sensitive quantitative phase imaging data obtained by spatial light interference microscopy (SLIM).

Histopathology of breast tissue typically involves labelling of a tissue section with the Hematoxylin and Eosin (H&E) counter stain. The contrast generated by the stain allows pathologists to extract both diagnostic and prognostic information (such as malignancy, grade and stage) during microscopic examination. Despite being the most frequent assessment method in use today, this procedure provides limited information and is subject to observer bias due to its qualitative nature. While commercial tissue slide scanners promise to improve the throughput of this method in the coming years, quantitative evaluation of tissue remains a challenge. In this work, we propose a method for simultaneously extracting color bright field and phase images of stained breast tissue biopsies using Spatial Light Interference Microscopy (SLIM) coupled with an RGB camera. The amplitude information allows standard qualitative histopathology while the quantitative phase information can be used, after normalizing for the staining, to extract physical markers characterizing patient health. We demonstrate this by imaging an H&E stained tissue microarray and showing that the normalized phase values can be exploited to classify benign and malignant tissue. Furthermore, we demonstrate that these images allow quantitation of tumor-adjacent collagen structure - an important prognostic marker for breast cancer. Extraction of these biomarkers requires measurement of the tissue optical path-length map which is not available in standard tissue evaluation. Our method, therefore, expands on the current diagnostic pipeline by complementing standard histopathology with quantitative tissue biomarkers, all obtainable in a single scan.

Breast cancer is the most common type of cancer among women worldwide. The standard histopathology of breast tissue, the primary means of disease diagnosis, involves manual microscopic examination of stained tissue by a pathologist. Because this method relies on qualitative information, it can result in inter-observer variation. Furthermore, for difficult cases the pathologist often needs additional markers of malignancy to help in making a diagnosis. We present a quantitative method for label-free tissue screening using Spatial Light Interference Microscopy (SLIM). By extracting tissue markers of malignancy based on the nanostructure revealed by the optical path-length, our method provides an objective and potentially automatable method for rapidly flagging suspicious tissue. We demonstrated our method by imaging a tissue microarray comprising 68 different subjects - 34 with malignant and 34 with benign tissues. Three-fold cross validation results showed a sensitivity of 94% and specificity of 85% for detecting cancer. The quantitative biomarkers we extract provide a repeatable and objective basis for determining malignancy. Thus, these disease signatures can be automatically classified through machine learning packages, since our images do not vary from scan to scan or instrument to instrument, i.e., they represent intrinsic physical attributes of the sample, independent of staining quality., Comment: 5 figures

Breast cancer is a major public health problem worldwide, being the most common type of cancer among women according to the World Health Organization (WHO). The WHO has further stressed the importance of an early determination of the disease course through prognostic markers. Recent studies have shown that the alignment of collagen fibers in tumor adjacent stroma correlate with poorer health outcomes in patients. Such studies have typically been carried out using Second-Harmonic Generation (SHG) microscopy. SHG images are very useful for quantifying collagen fiber orientation due their specificity to non-centrosymmetric structures in tissue, leading to high contrast in collagen rich areas. However, the imaging throughput in SHG microscopy is limited by its point scanning geometry. In this work, we show that SLIM, a wide-field high-throughput QPI technique, can be used to obtain the same information on collagen fiber orientation as is obtainable through SHG microscopy. We imaged a tissue microarray containing both benign and malignant cores using both SHG microscopy and SLIM. The cellular (non-collagenous) structures in the SLIM images were next segmented out using an algorithm developed in-house. Using the previously published Fourier Transform Second Harmonic Generation (FT-SHG) tool, the fiber orientations in SHG and segmented SLIM images were then quantified. The resulting histograms of fiber orientation angles showed that both SHG and SLIM generate similar measurements of collagen fiber orientation. The SLIM modality, however, can generate these results at much higher throughput due to its wide-field, whole-slide scanning capabilities.

Traditionally the measurement of electrical activity in neurons has been carried out using microelectrode arrays that require the conducting elements to be in contact with the neuronal network. This method, also referred to as “electrophysiology”, while being excellent in terms of temporal resolution is limited in spatial resolution and is invasive. An optical microscopy method for measuring electrical activity is thus highly desired. Common-path quantitative phase imaging (QPI) systems are good candidates for such investigations as they provide high sensitivity (on the order of nanometers) to the plasma membrane fluctuations that can be linked to electrical activity in a neuronal circuit. In this work we measured electrical activity in a culture of rat cortical neurons using MISS microscopy, a high-speed common-path QPI technique having an axial resolution of around 1 nm in optical path-length, which we introduced at PW BIOS 2016. Specifically, we measured the vesicular cycling (endocytosis and exocytosis) occurring at axon terminals of the neurons due to electrical activity caused by adding a high K+ solution to the cell culture. The axon terminals were localized using a micro-fluidic device that separated them from the rest of the culture. Stacks of images of these terminals were acquired at 826 fps both before and after K+ excitation and the temporal standard deviation maps for the two cases were compared to measure the membrane fluctuations. Concurrently, the existence of vesicular cycling was confirmed through fluorescent tagging and imaging of the vesicles at and around the axon terminals.

We derive analytic expressions for the polarization characteristics of light emerging from a magneto-optical medium possessing arbitrary contributions from linear and circular birefringence as well...

Optical microscopy is an indispensable diagnostic tool in modern healthcare. As a prime example, pathologists rely exclusively on light microscopy to investigate tissue morphology in order to make a diagnosis. While advances in light microscopy and contrast markers allow pathologists to visualize cells and tissues in unprecedented detail, the interpretation of these images remains largely subjective, leading to inter- and intra-observer discrepancy. Furthermore, conventional microscopy images capture qualitative information which makes it difficult to automate the process, reducing the throughput achievable in the diagnostic workflow. Quantitative Phase Imaging (QPI) techniques have been advanced in recent years to address these two challenges. By quantifying physical parameters of cells and tissues, these systems remove subjectivity from the disease diagnosis process and allow for easier automation to increase throughput. In addition to providing quantitative information, QPI systems are also label-free and can be easily assimilated into the current diagnostic workflow in the clinic. In this paper we review the advances made in disease diagnosis by QPI techniques. We focus on the areas of hematological diagnosis and cancer pathology, which are the areas where most significant advances have been made to date. [Image adapted from Y. Park, M. Diez-Silva, G. Popescu, G. Lykotrafitis, W. Choi, M. S. Feld, and S. Suresh, Proc. Natl. Acad. Sci. 105, 13730-13735 (2008).].

Diffraction Phase Microscopy (DPM) is a common-path, single shot QPI technique that has found applications in studies of red blood cell morphology and dynamics, cell growth measurement, as well as in Fourier Transform Light Scattering. In DPM, the phase is retrieved by interfering two orders of diffraction from a grating placed at the image plane. The reference field has been, in the past, generated by low pass filtering the zero order via a pinhole placed in the Fourier plane. For achieving the desired spatial coherence, the pinhole is often only 5-10 µm in diameter, making the system difficult to align every time an imaging study is performed. In this work, we eliminated the pinhole from the DPM optical path and generated instead the reference field by magnifying strongly the zero order. We show that a gradient-index (GRIN) lens (effective focal length of 300 µm) can be used to magnify the Fourier transform of the zero order to the point where the DC component fills the camera sensor. We show that the resulting Magnified Object Spectrum Interference Microscopy (MOSIM) system can successfully reconstruct quantitative phase images, without the need for tedious alignment. Because it conserves the common path geometry, MOSIM is characterized by 1.1 nm spatiotemporal pathlength noise. Since it is single shot, we demonstrated 400 frames/s acquisition. We anticipate that this new method can potentially lead to a more robust and less vibration sensitive QPI instrument for carrying out biological studies at various spatiotemporal scales.

Traction force microscopy is the most widely used technique for studying the forces exerted by cells on deformable substrates. However, the method is computationally intense and cells have to be detached from the substrate prior to measuring the displacement map. We have developed a new method, referred to as Hilbert phase dynamometry (HPD), which yields real-time force fields and, simultaneously, cell dry mass and growth information. HPD operates by imaging cells on a deformable substrate that is patterned with a grid of fluorescent proteins. A Hilbert transform is used to extract the phase map associated with the grid deformation, which provides the displacement field. By combining this information with substrate stiffness, an elasticity model was developed to measure forces exerted by cells with high spatial resolution. In our study, we prepared 10kPa gels and them with a 2-D grid of FITC-conjugated fibrinogen/fibronectin mixture, an extracellular matrix protein to which cells adhere. We cultured undifferentiated mesenchymal stem cells (MSC), and MSCs that were in the process of undergoing adipogenesis and osteogenesis. The cells were measured over the course of 24 hours using Spatial Light Interference Microscopy (SLIM) and wide-field epi-fluorescence microscopy allowing us to simultaneously measure cell growth and the forces exerted by the cells on the substrate.

The current tissue evaluation method for breast cancer would greatly benefit from higher throughput and less inter-observer variation. Since quantitative phase imaging (QPI) measures physical parameters of tissue, it can be used to find quantitative markers, eliminating observer subjectivity. Furthermore, since the pixel values in QPI remain the same regardless of the instrument used, classifiers can be built to segment various tissue components without need for color calibration. In this work we use a texton-based approach to segment QPI images of breast tissue into various tissue components (epithelium, stroma or lumen). A tissue microarray comprising of 900 unstained cores from 400 different patients was imaged using Spatial Light Interference Microscopy. The training data were generated by manually segmenting the images for 36 cores and labelling each pixel (epithelium, stroma or lumen.). For each pixel in the data, a response vector was generated by the Leung-Malik (LM) filter bank and these responses were clustered using the k-means algorithm to find the centers (called textons). A random forest classifier was then trained to find the relationship between a pixel’s label and the histogram of these textons in that pixel’s neighborhood. The segmentation was carried out on the validation set by calculating the texton histogram in a pixel’s neighborhood and generating a label based on the model learnt during training. Segmentation of the tissue into various components is an important step toward efficiently computing parameters that are markers of disease. Automated segmentation, followed by diagnosis, can improve the accuracy and speed of analysis leading to better health outcomes.

Label-free imaging of rapidly moving, sub-diffraction sized structures has important applications in both biology and material science, as it removes the limitations associated with fluorescence tagging. However, unlabeled nanoscale particles in suspension are difficult to image due to their transparency and fast Brownian motion. Here we describe a novel interferometric imaging technique referred to as Magnified Image Spatial Spectrum (MISS) microscopy, which overcomes these challenges. The MISS microscope provides quantitative phase information and enables dynamic light scattering investigations with an overall optical path length sensitivity of 0.95 nm at 833 frames per second acquisition rate. Using spatiotemporal filtering, we find that the sensitivity can be further pushed down to 0.001-0.01 nm. We demonstrate the instrument's capability through colloidal nanoparticle sizing down to 20 nm diameter and measurements of live neuron membrane dynamics. MISS microscopy is implemented as an upgrade module to an existing microscope, which converts it into a powerful light scattering instrument. Thus, we anticipate that MISS will be adopted broadly for both material and life sciences applications.

We investigate the uniqueness of the plane-wave decomposition of temporally deterministic, spatially random fields. Specifically, we consider the decomposition of spatially ergodic and, thus, statistically homogeneous fields. We show that when the spatial power spectrum is injective, the plane waves are the only possible coherent modes. Furthermore, the randomness of such fields originates in the spatial spectral phase, i.e., the phase associated with the coefficients of each plane wave in the expansion. By contrast, the spectral amplitude is deterministic and is specified by the spatial power spectrum. We end with a discussion showing how the results can be translated in full to the time domain.

The standard practice in histopathology of breast cancers is to examine a hematoxylin and eosin (H&E) stained tissue biopsy under a microscope to diagnose whether a lesion is benign or malignant. This determination is made based on a manual, qualitative inspection, making it subject to investigator bias and resulting in low throughput. Hence, a quantitative, label-free, and high-throughput diagnosis method is highly desirable. We present here preliminary results showing the potential of quantitative phase imaging for breast cancer screening and help with differential diagnosis. We generated phase maps of unstained breast tissue biopsies using spatial light interference microscopy (SLIM). As a first step toward quantitative diagnosis based on SLIM, we carried out a qualitative evaluation of our label-free images. These images were shown to two pathologists who classified each case as either benign or malignant. This diagnosis was then compared against the diagnosis of the two pathologists on corresponding H&E stained tissue images and the number of agreements were counted. The agreement between SLIM and H&E based diagnosis was 88% for the first pathologist and 87% for the second. Our results demonstrate the potential and promise of SLIM for quantitative, label-free, and high-throughput diagnosis.

We provide a quantitative model for image formation in common-path QPI systems under partially coherent illumination. Our model is capable of explaining the phase reduction phenomenon and halo effect in phase measurements. We further show how to fix these phenomena with a novel iterative post-processing algorithm. Halo-free and correct phase images of nanopillars and live cells are used to demonstrate the validity of our method.

The standard practice in the histopathology of breast cancers is to examine a hematoxylin and eosin (H&E) stained tissue biopsy under a microscope. The pathologist looks at certain morphological features, visible under the stain, to diagnose whether a tumor is benign or malignant. This determination is made based on qualitative inspection making it subject to investigator bias. Furthermore, since this method requires a microscopic examination by the pathologist it suffers from low throughput. A quantitative, label-free and high throughput method for detection of these morphological features from images of tissue biopsies is, hence, highly desirable as it would assist the pathologist in making a quicker and more accurate diagnosis of cancers. We present here preliminary results showing the potential of using quantitative phase imaging for breast cancer screening and help with differential diagnosis. We generated optical path length maps of unstained breast tissue biopsies using Spatial Light Interference Microscopy (SLIM). As a first step towards diagnosis based on quantitative phase imaging, we carried out a qualitative evaluation of the imaging resolution and contrast of our label-free phase images. These images were shown to two pathologists who marked the tumors present in tissue as either benign or malignant. This diagnosis was then compared against the diagnosis of the two pathologists on H&E stained tissue images and the number of agreements were counted. In our experiment, the agreement between SLIM and H&E based diagnosis was measured to be 88%. Our preliminary results demonstrate the potential and promise of SLIM for a push in the future towards quantitative, label-free and high throughput diagnosis.

White light diffraction microscopy (wDPM) is a quantitative phase imaging method that benefits from both temporal and spatial phase sensitivity, granted, respectively, by the common-path geometry and white light illumination. However, like all off-axis quantitative phase imaging methods, wDPM is characterized by a reduced space-bandwidth product compared to phase shifting approaches. This happens essentially because the ultimate resolution of the image is governed by the period of the interferogram and not just the diffraction limit. As a result, off-axis techniques generates single-shot, i.e., high time-bandwidth, phase measurements, at the expense of either spatial resolution or field of view. Here, we show that combining phase-shifting and off-axis, the original space-bandwidth is preserved. Specifically, we developed phase-shifting diffraction phase microscopy with white light, in which we measure and combine two phase shifted interferograms. Due to the white light illumination, the phase images are characterized by low spatial noise, i.e.

We report systematically acquired data on the Verdet constant of terbium gallium garnet for wavelengths ranging from visible to near-infrared (405-830 nm) regime. Our experimental method of Stokes polarimetry is based on the Fourier decomposition of the received light intensity and allows unambiguous determination of both the Faraday rotation and the ellipticity of the emergent light. Temperature-dependent investigations in the range of 8-300 K extend earlier reports and verify the Verdet's constant direct dependence on the magnetization, whose first-order approximation is simply a manifestation of the Curie's law. Further, a least-squares fitting of the experimental data correlates well with theoretical predictions. At a wavelength of 405 nm and temperature of 8 K, the rotation is approximately 500°.

We report the complete determination of the polarization changes caused in linearly polarized incident light due to propagation in a magneto-optically active terbium gallium garnet (TGG) single crystal, at temperatures ranging from 6.3 to 300 K. A 28-fold increase in the Verdet constant of the TGG crystal is seen as its temperature decreases to 6.3 K. In contrast with polarimetry of light emerging from a Faraday material at room temperature, polarimetry at cryogenic temperatures cannot be carried out using the conventional fixed polarizer-analyzer technique because the assumption that ellipticity is negligible becomes increasingly invalid as temperature is lowered. It is shown that complete determination of light polarization in such a case requires the determination of its Stokes parameters, otherwise inaccurate measurements will result with negative implications for practical devices.