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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.

The intrinsic markers of nanoscale morphological alteration in fixed tissue biopsy referred to as disorder strength and local correlation length, which can be easily and time-efficiently obtained from quantitative phase images, are introduced. After presenting how to extract these markers from quantitative phase images obtained by highly sensitive quantitative phase imaging system, spatial light interference microscopy (SLIM), we demonstrate the effectiveness of these markers for diagnosis of benign and malignant breast tissues.

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.

Understanding cell mechanotransduction is important for discerning matrix structure-cell function relationships underlying health and disease. Despite the crucial role of mechanochemical signaling in phenomena such as cell migration, proliferation, and differentiation, measuring the cell-generated forces at the interface with the extracellular matrix during these biological processes remains challenging. An ideal method would provide continuous, non-destructive images of the force field applied by cells, over broad spatial and temporal scales, while simultaneously revealing the cell biological process under investigation. Toward this goal, we present the integration of a new real-time traction stress imaging modality, Hilbert phase dynamometry (HPD), with the technique of spatial light interference microscopy (SLIM) for label free monitoring of cell growth. HPD relies on extracting the displacement field in a deformable substrate, which is chemically patterned with a fluorescent grid. The displacements introduced by the cell are captured by thephaseof the periodic signal associated with the grid, borrowing concepts from holography. The displacement field is uniquely converted into forces by solving an elasticity inverse problem. Because the measurement of displacement only uses the epi-fluorescence channel of an inverted microscope, we can simultaneously achieve measurements in transmission. We performed SLIM and extracted cell mass on the same field of view in addition to the measured displacement field. We used this technique to study mesenchymal stem cells and found that cells undergoing osteogenesis and adipogenesis exerted larger and more dynamic stresses than their precursor. Our results indicate that the MSCs develop the smallest forces and growth rates. We anticipate that simultaneous cell growth and traction measurements will improve our understanding of mechanotransduction, particularly during dynamic processes where the matrix properties provide context to guide cells towards a physiological or pathological outcome, e.g., tissue morphogenesis, or cancer metastasis.

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).

The standard method for cancer diagnosis is the microscopic investigation of tissue biopsies. Because the tissues do not significantly absorb and scatter light, traditionally, the observation is performed using bright-field microscopy after staining. Although this approach has been widely adopted all over the world for 100 years, it generally takes a long preparation time and sometimes the early carcinogenesis is missed due to a variation in a quality of a staining. Quantitative phase imaging (QPI) can access objective information on thickness and refractive index changes from an unstained tissue slice, which cannot be observed by conventional microscopes. This can be an attractive advantage in the field of a medical diagnosis, especially since QPI can access the tissue architecture information with nanoscale sensitivity. In this paper, we used quantitative phase imaging to measure the tissue disorder strength, which is known as one of the effective markers of early carcinogenesis. We retrieved the disorder parameter from the local refractive index fluctuation map obtained by spatial light interference microscopy (SLIM). We show that SLIM imaging combined with the disorder analysis is a valuable approach for screening of benign and malignant breast tissue biopsies.

Quantitative phase imaging (QPI) can access quantitative information on thickness and/or refractive index changes of weakly absorbing and scattering objects, which normally require staining prior to observation. The quantitative phase image itself yields significant information for a medical diagnosis, particularly in cancer biopsies. Previously, several parameters such as a local standard deviation of refractive index have been utilized as a marker of diseases. We focus on the local spatial autocorrelation length, which is calculated at each point in the field of view. The local spatial autocorrelation length is defined as the standard deviation of the local spatial autocorrelation function and reveals the local and directional disorder information of tissues. However, generally, a direct calculation of the local spatial autocorrelation length take an immense amount of time. In this paper, we propose a high-throughput calculation procedure of a local spatial autocorrelation length, by exploiting frequency-domain calculations. After deriving a simple equation to calculate the local spatial autocorrelation length map in a short time, we perform label-free screening of benign and malignant breast tissue biopsies using this parameter as a marker.

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.

Tissue refractive index provides important information about morphology at the nanoscale. Since the malignant transformation involves both intra- and inter-cellular changes in the refractive index map, the tissue disorder measurement can be used to extract important diagnosis information. Quantitative phase imaging (QPI) provides a practical means of extracting this information as it maps the optical path-length difference (OPD) across a tissue sample with sub-wavelength sensitivity. In this work, we employ QPI to compare the tissue disorder strength between benign and malignant breast tissue histology samples. Our results show that disease progression is marked by a significant increase in the disorder strength. Since our imaging system can be added as an upgrading module to an existing microscope, we anticipate that it can be integrated easily in the pathology work flow.

Tissue refractive index provides important information about morphology at the nanoscale. Since the malignant transformation involves both intra- and inter-cellular changes in the refractive index map, the tissue disorder measurement can be used to extract important diagnosis information. Quantitative phase imaging (QPI) provides a practical means of extracting this information as it maps the optical path-length difference (OPD) across a tissue sample with sub-wavelength sensitivity. In this work, we employ QPI to compare the tissue disorder strength between benign and malignant breast tissue histology samples. Our results show that disease progression is marked by a significant increase in the disorder strength. Since our imaging system can be added as an upgrading module to an existing microscope, we anticipate that it can be integrated easily in the pathology work flow.

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...

Tumor progression in breast cancer is significantly influenced by its interaction with the surrounding stromal tissue. Specifically, the composition, orientation, and alignment of collagen fibers in tumor-adjacent stroma affect tumor growth and metastasis. Most of the work done on measuring this prognostic marker has involved imaging of collagen fibers using second-harmonic generation microscopy (SHGM), which provides label-free specificity. Here, we show that spatial light interference microscopy (SLIM), a label-free quantitative phase imaging technique, is able to provide information on collagen-fiber orientation that is comparable to that provided by SHGM. Due to its wide-field geometry, the throughput of the SLIM system is much higher than that of SHGM and, because of the linear imaging, the equipment is simpler and significantly less expensive. Our results indicate that SLIM images can be used to extract important prognostic information from collagen fibers in breast tissue, potentially providing a convenient high throughput clinical tool for assessing patient prognosis.

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.

While automated blood cell counters have made great progress in detecting abnormalities in blood, the lack of specificity for a particular disease, limited information on single cell morphology and intrinsic uncertainly due to high throughput in these instruments often necessitates detailed inspection in the form of a peripheral blood smear. Such tests are relatively time consuming and frequently rely on medical professionals tally counting specific cell types. These assays rely on the contrast generated by chemical stains, with the signal intensity strongly related to staining and preparation techniques, frustrating machine learning algorithms that require consistent quantities to denote the features in question. Instead we opt to use quantitative phase imaging, understanding that the resulting image is entirely due to the structure (intrinsic contrast) rather than the complex interplay of stain and sample. We present here our first steps to automate peripheral blood smear scanning, in particular a method to generate the quantitative phase image of an entire blood smear at high throughput using white light diffraction phase microscopy (wDPM), a single shot and common path interferometric imaging technique.

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.

Spatiotemporal patterns of intracellular transport are very difficult to quantify and, consequently, continue to be insufficiently understood. While it is well documented that mass trafficking inside living cells consists of both random and deterministic motions, quantitative data over broad spatiotemporal scales are lacking. We studied the intracellular transport in live cells using spatial light interference microscopy, a high spatiotemporal resolution quantitative phase imaging tool. The results indicate that in the cytoplasm, the intracellular transport is mainly active (directed, deterministic), while inside the nucleus it is both active and passive (diffusive, random). Furthermore, we studied the behavior of the two-dimensional mass density over 30 h in HeLa cells and focused on the active component. We determined the standard deviation of the velocity distribution at the point of cell division for each cell and compared the standard deviation velocity inside the cytoplasm and the nucleus. We found that the velocity distribution in the cytoplasm is consistently broader than in the nucleus, suggesting mechanisms for faster transport in the cytosol versus the nucleus. Future studies will focus on improving phase measurements by applying a fluorescent tag to understand how particular proteins are transported inside the cell.

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.