The complete blood count (CBC) is a foundational diagnostic test, but its accessibility is limited due to the blood draw, expensive laboratory equipment, and trained personnel required. Here, we present a cell phone microscope design for achieving phase contrast in high resolution capillary imaging, which allows individual blood cells to be imaged for a non-invasive CBC. The cell phone microscope uses a reversed lens as an objective to maintain a high resolution. Relay lenses create space for incorporation of an offset LED that can be critically imaged to produce oblique back illumination, resulting in phase contrast.
Urinalysis is an essential diagnostic tool in evaluating health and disease of the genitourinary tract. A urinalysis typically consists of dipstick testing, which can detect red blood cells, white blood cells, and bacteria, and microscopic evaluation of urine sediment after centrifugation, which further reveals other biomarkers such as crystals and casts. In the in-patient hospital setting, urinalysis is typically ordered after disease is suspected, drawing urine from the collection bag of a foley catheter and sending the sample to a core laboratory for analysis. To improve access to urine biomarkers, we propose a holographic lens free imaging (LFI) system that could allow automated bedside urine screening. LFI is uniquely suited for this task due to its low-cost, compact nature, and its ability to reconstruct large volumes from a single hologram without the depth-of-field trade-off of conventional microscopy. Here, we build and demonstrate an LFI system capable of detecting important biomarkers such as E. Coli in PBS and red blood cells, casts, and crystals in urinalysis control phantoms. In the future, this compact system could be connected to the drainage tube of a patient's foley catheter to enable real-time screening of urine at the bedside.
Oblique back-illumination capillaroscopy (OBC) has recently demonstrated clear images of unlabeled human blood cells in vivo. Combined with deep learning-based algorithms, this technology may enable non-invasive blood cell counting and analysis as flowing red blood cells, platelets, and white blood cells can be observed in their native environment. To harness the full potential of OBC, new techniques and methods must be developed that provide ground truth data using human blood cells. Here we present such a model, where human blood cells with paired ground truth information are imaged flowing in a custom tissue-mimicking micro fluidic device. This model enables the acquisition of OBC datasets that will help with both training and validating machine learning models for applications including the complete blood count, specific blood cell classification, and the study of hematologic disorders such as anemia.
Some tumor resection procedures, such as Mohs surgery, utilize intraoperative histology for tumor margin assessments. Gold standard rapid histology methods are time-consuming for patients under anesthetic and rapid freezing techniques are prone to artifacts. The recent development of microscopy with ultraviolet surface excitation (MUSE) introduces a new possibility for the rapid imaging of the cut tissue surface using fluorescent dyes. The high attenuation of ultraviolet light limits MUSE signals to thicknesses close to typical histology sections. To generate MUSE images with familiar H&E-like contrast, recent work has explored the transformation of MUSE images to “virtual” H&E-like images using unsupervised deep learning models trained on unpaired images of separate tissues treated with each stain. Here, we present a method for acquiring registered images of the same tissue with MUSE and real H&E imaging using sequential staining and dye removal. Tissue blocks are flash frozen and sectioned for mounting onto slides and staining with MUSE fluorescent dyes. After MUSE imaging, a sequential immersion of the slides in increasing concentrations of ethyl alcohol followed by rehydration, similar to steps in paraffin-based histology processing, is sufficient to remove all fluorescent dyes. Rinsed tissue slides are then subjected to traditional H&E staining and brightfield imaging. Data of registered image fields of skin and pancreas are presented along with initial machine learning-based transformations from MUSE to H&E contrast. This protocol will be useful to obtain paired images for training, testing, and quantitative validation of virtual H&E reconstructions from MUSE images.
Oblique plane microscopy (OPM) is a powerful tool for monitoring biological processes due to its capability for highresolution, rapid, optically-sectioned imaging through a single objective lens. Recently, our group has demonstrated scattering-contrast OPM (sOPM) as a technique to image blood cells in situ and in vivo. In order to classify blood cells visualized with sOPM, scattering data could be further leveraged and better understood. We present here a visualization and analysis of the scattering signal by masking and imaging the final Fourier plane of the sOPM system. We demonstrate the angular distribution of the scattering signal and image with several aperture masks. Microsphere phantoms are imaged in the image plane and Fourier plane to demonstrate the change in scattering behavior for Mie scatterers with large (4 micron) diameters and small (190 nm), Rayleigh-like scatterers similar to subcellular features such as granules. Circular apertures were used to isolate the side scattering centered at 90 degrees compared to the angular extremes. A Michelson contrast of 0.20-0.25 was observed for 4 micron diameter spheres and 0.05-0.10 for 190 nm diameter spheres using a split aperture. Microsphere sizes are classified from images using split aperture contrast and confirmed by fluorescence. Leveraging differential scattering angle contrast will enable the visual classification of blood cells, particularly white blood cells where granules and other organelles present distinct side scattering signals. Finally, the quantitative nature of the differential scattering angle contrast may enable machine-learning based classification and cell counting.
Oblique back-illumination capillaroscopy (OBC) has recently demonstrated high resolution, label-free images of human blood cells in vivo. This technology shows promise for a new chapter in blood analysis, where blood cell counts, morphology, and dynamics can be probed non-invasively. OBC provides high quality blood cell images when applied to the ventral tongue, where capillaries are superficial and melanin is minimal. However, the anatomy of this location has a unique and challenging constraints due to the highly muscular and mobile nature of the tongue, and its presence within the oral cavity. This manuscript presents a portable and ergonomic dual- channel OBC system that is optimized for imaging the ventral tongue. The portable OBC system uses pneumatic stabilization to reduce capillary motion and is built upon an ophthalmic slit lamp housing to allow comfortable stabilization of the head and fine, 3-axis translation of the imaging probe. The signal from two diametrically opposed LEDs (530nm and 650nm) are imaged onto two time-synchronized CMOS sensors, providing combined phase-weighted and absorption-weighted contrast of blood cells at 200 Hz with a 165 x 220μm field-of-view. This functional implementation of OBC technology will enable high resolution blood cell imaging of patients with hematologic disease.
The increasing performance and ubiquity of mobile phone cameras has led to several emerging opportunities for their use in global health and point-of-care diagnostics. High-resolution, low-cost microscopy can be achieved by pairing the cell phone lens with a second, identical lens in a reversed orientation, allowing 1x magnification over a large field of view. In previous work, we showed that reverse lens mobile phone capillaroscopy can visualize optical absorption gaps (OAGs) in nailfold capillaries. The frequency of these OAGs is known to be inversely correlated with degree of neutropenia. To extend this concept and enable the direct visualization of both red and white blood cells for more complete blood analysis, there is a need for improved resolution and phase contrast. Here, we present a design for a reverse lens mobile phone capillaroscope that pairs two different cell phone lenses to increase magnification for enhanced visualization. From an iPhone 12 Pro, the telephoto and wide cameras are combined with reversed wide and ultrawide lenses. The lens pairs provide magnification up to 4.02x and resolution up to approximately 1.49 μm, whereas the previous design only yielded a resolution of 3.75 μm. We use this system to image human blood in a microfluidic capillary phantom.
Diffuser-based sensing has shown potentials in inexpensive and compact optical systems. Here we demonstrate a low-cost diffuser-based computational funduscope that can recover pathological features of the model eye fundus. Our system implements an infinite-conjugate design by relaying the ocular lens onto the diffuser which provides shift-invariance across a wide field-of-view (FOV). Our experiments show that fundus images can be reconstructed over 33 degree FOV and our device is robust to 4D refractive error using a single point-spread-function.
Capillaroscopy is a simple microscopy technique able to measure important clinical biomarkers non-invasively. For example, optical absorption gaps between red blood cells in capillary vessels of the nailfold have been shown to correlate with severity of neutropenia. The direct visualization of individual white blood cells with capillaroscopic techniques is elusive because it is challenging to generate epiillumination phase contrast in thick turbid media. Here, we evaluate white blood cell visibility with graded-field capillaroscopy in a flow phantom. We fabricate capillary phantoms with soft photolithography using PDMS doped with TiO2 and India ink to emulate skin optical properties. These glass-free phantoms feature channels embedded in scattering media at controlled depths (70-470 μm), as narrow as 15 x 15 μm, and permit blood flow up to 6 mm/s. We optimize the contrast of the graded-field capillaroscope in these tissue-realistic phantoms and demonstrate high speed imaging (200 Hz) of blood cells flowing through scattering media.
Automated segmentation of tissue and cellular structure in H&E images is an important first step towards automated histopathology slide analysis. For example, nuclei segmentation can aid with detecting pleomorphism and epithelium segmentation can aid in identification of tumor infiltrating lymphocytes etc. Existing deep learning-based approaches are often trained organ-wise and lack diversity of training data for multi-organ segmentation networks. In this work, we propose to augment existing nuclei segmentation datasets using cycleGANs. We learn an unpaired mapping from perturbed randomized polygon masks to pseudo-H&E images. We generate over synthetic H&E patches from several different organs for nuclei segmentation. We then use an adversarial U-Net with spectral normalization for increased training stability for segmentation. This paired image-to-image translation style network not only learns the mapping form H&E patches to segmentation masks but also learns an optimal loss function. Such an approach eliminates the need for a hand-crafted loss which has been explored significantly for nuclei segmentation. We demonstrate that the average accuracy for multi-organ nuclei segmentation increases to 94.43% using the proposed synthetic data generation and adversarial U-Net-based segmentation pipeline as compared to 79.81% when no synthetic data and adversarial loss was used.
Febrile neutropenia (FN) is a common cause of hospitalization for cancer patients undergoing chemotherapy treatment. To screen for FN, patients require invasive blood draws and complete blood cell counts, which increases risk of nosocomial infection while in an immunocompromised state. There is a pressing clinical need for non-invasive, point-of-care technology to frequently screen for FN, which, if detected early, can be prophylactically managed. A promising approach to address this need is capillaroscopy, through which blood cells are imaged in capillaries non-invasively. Visualization of shadows caused by absorption of individual red blood cells is currently achievable, and correlation between the absence of optical absorption gaps and severe neutropenia has been observed. However, a completely accurate identification of the physical origin of these optical absorption gaps for conclusive neutropenia diagnosis remains an elusive task. Here we present scattering oblique plane microscopy as a means of imaging moving scattering particles within a turbid medium with the goal of eventually imaging and characterizing blood cells in vivo flowing in superficial capillaries. Our imaging system illuminates an oblique light sheet through a capillary bed and collects back-scatter using a single objective at frame rates of >200 Hz. To validate this system, we develop phantoms mimicking capillaries with 200 μm diameter lumens embedded deep in silicone doped with TiO2 and India ink. Single 3 μm diameter polystyrene beads flowing through the capillaries are resolved with a signal to noise ratio of approximately 5:1 at a depth of 1 mean free path.
Wavefront sensing is typically accomplished with a Shack-Hartmann wavefront sensor (SHWS), where a CCD or CMOS is placed at the focal plane of a periodic, microfabricated lenslet array. Tracking the displacement of the resulting spots in the presence of an aberrated wavefront yields measurement of the relative wavefront introduced. A SHWS has a fundamental tradeoff between sensitivity and range, determined by the pitch and focal length of its lenslet array, such that the number of resolvable tilts is a constant. Recently, diffuser wavefront sensing (DWS) has been demonstrated by measuring the lateral shift of a coherent speckle pattern using the concept of the diffuser memory effect. Here we demonstrate that tracking distortions of the non-periodic caustic pattern produced by a holographic diffuser allows accurate autorefraction of a model eye with a number of resolvable tilts that extends beyond the fundamental limit of a SHWS. Using a multi-level Demon’s image registration algorithm, we are able to demonstrate that a DWS demonstrates a 2.5x increase in number of resolvable prescriptions as compared to a conventional SHWS while maintaining acceptable accuracy and repeatability for eyeglass prescriptions. We evaluate the performance of a DWS and SHWS in parallel with a coherent laser diode without (LD) and with a laser speckle reducer (LD+LSR), and an incoherent light-emitting diode (LED), demonstrating caustic-tracking is compatible with coherent and incoherent sources. Additionally, the DWS diffuser costs 40x less than a SHWS lenslet array, enabling affordable large-dynamic range autorefraction without moving parts.
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