White Light Diffraction Phase Microscopy in Imaging of Breast and Colon Tissues.

This paper reports results obtained using white light diffraction phase microscopy (wDPM) on captured images of breast and colon tissue samples, marking a contribution to the advancement in biomedical imaging. Unlike conventional brightfield microscopy, wDPM offers the capability to capture intricate details of biological specimens with enhanced clarity and precision. It combines high resolution, enhanced contrast, and quantitative capabilities with non-invasive, label-free imaging. These features make it a useful tool for tissue imaging, providing detailed and accurate insights into tissue structure and dynamics without compromising the integrity of the samples. Our findings underscore the potential of quantitative phase imaging in histopathology, in the context of automating the process of tissue analysis and diagnosis. Of particular note are the insights gained from the reconstructed phase images, which provide physical data regarding peripheral glandular cell membranes. These observations serve to focus attention on pathologies involving the basal membrane, such as early invasive carcinoma. Through our analysis, we aim to contribute to catalyzing further advancements in tissue (breast and colon) imaging.

Non-invasive label-free imaging analysis pipeline for in situ characterization of 3D brain organoids.

Brain organoids provide a unique opportunity to model organ development in a system similar to human organogenesis in vivo. Brain organoids thus hold great promise for drug screening and disease modeling. Conventional approaches to organoid characterization predominantly rely on molecular analysis methods, which are expensive, time-consuming, labor-intensive, and involve the destruction of the valuable three-dimensional (3D) architecture of the organoids. This reliance on end-point assays makes it challenging to assess cellular and subcellular events occurring during organoid development in their 3D context. As a result, the long developmental processes are not monitored nor assessed. The ability to perform non-invasive assays is critical for longitudinally assessing features of organoid development during culture. In this paper, we demonstrate a label-free high-content imaging approach for observing changes in organoid morphology and structural changes occurring at the cellular and subcellular level. Enabled by microfluidic-based culture of 3D cell systems and a novel 3D quantitative phase imaging method, we demonstrate the ability to perform non-destructive high-resolution quantitative image analysis of the organoid. The highlighted results demonstrated in this paper provide a new approach to performing live, non-destructive monitoring of organoid systems during culture.

Off-axis digital lensless holographic microscopy based on spatially multiplexed interferometry.

Significance: Digital holographic microscopy (DHM) is a label-free microscopy technique that provides time-resolved quantitative phase imaging (QPI) by measuring the optical path delay of light induced by transparent biological samples. DHM has been utilized for various biomedical applications, such as cancer research and sperm cell assessment, as well as for in vitro drug or toxicity testing. Its lensless version, digital lensless holographic microscopy (DLHM), is an emerging technology that offers size-reduced, lightweight, and cost-effective imaging systems. These features make DLHM applicable, for example, in limited resource laboratories, remote areas, and point-of-care applications. Aim: In addition to the abovementioned advantages, in-line arrangements for DLHM also include the limitation of the twin-image presence, which can restrict accurate QPI. We therefore propose a compact lensless common-path interferometric off-axis approach that is capable of quantitative imaging of fast-moving biological specimens, such as living cells in flow. Approach: We suggest lensless spatially multiplexed interferometric microscopy (LESSMIM) as a lens-free variant of the previously reported spatially multiplexed interferometric microscopy (SMIM) concept. LESSMIM comprises a common-path interferometric architecture that is based on a single diffraction grating to achieve digital off-axis holography. From a series of single-shot off-axis holograms, twin-image free and time-resolved QPI is achieved by commonly used methods for Fourier filtering-based reconstruction, aberration compensation, and numerical propagation. Results: Initially, the LESSMIM concept is experimentally demonstrated by results from a resolution test chart and investigations on temporal stability. Then, the accuracy of QPI and capabilities for imaging of living adherent cell cultures is characterized. Finally, utilizing a microfluidic channel, the cytometry of suspended cells in flow is evaluated. Conclusions: LESSMIM overcomes several limitations of in-line DLHM and provides fast time-resolved QPI in a compact optical arrangement. In summary, LESSMIM represents a promising technique with potential biomedical applications for fast imaging such as in imaging flow cytometry or sperm cell analysis.

Quantitative phase imaging techniques for measuring scattering properties of cells and tissues: a review-part I.

Significance: Quantitative phase imaging (QPI) techniques offer intrinsic information about the sample of interest in a label-free, noninvasive manner and have an enormous potential for wide biomedical applications with negligible perturbations to the natural state of the sample in vitro. Aim: We aim to present an in-depth review of the scattering formulation of light-matter interactions as applied to biological samples such as cells and tissues, discuss the relevant quantitative phase measurement techniques, and present a summary of various reported applications. Approach: We start with scattering theory and scattering properties of biological samples followed by an exploration of various microscopy configurations for 2D QPI for measurement of structure and dynamics. Results: We reviewed 157 publications and presented a range of QPI techniques and discussed suitable applications for each. We also presented the theoretical frameworks for phase reconstruction associated with the discussed techniques and highlighted their domains of validity. Conclusions: We provide detailed theoretical as well as system-level information for a wide range of QPI techniques. Our study can serve as a guideline for new researchers looking for an exhaustive literature review of QPI methods and relevant applications.

Quantitative phase imaging techniques for measuring scattering properties of cells and tissues: a review-part II.

Significance: Quantitative phase imaging (QPI) is a non-invasive, label-free technique that provides intrinsic information about the sample under study. Such information includes the structure, function, and dynamics of the sample. QPI overcomes the limitations of conventional fluorescence microscopy in terms of phototoxicity to the sample and photobleaching of the fluorophore. As such, the application of QPI in estimating the three-dimensional (3D) structure and dynamics is well-suited for a range of samples from intracellular organelles to highly scattering multicellular samples while allowing for longer observation windows. Aim: We aim to provide a comprehensive review of 3D QPI and related phase-based measurement techniques along with a discussion of methods for the estimation of sample dynamics. Approach: We present information collected from 106 publications that cover the theoretical description of 3D light scattering and the implementation of related measurement techniques for the study of the structure and dynamics of the sample. We conclude with a discussion of the applications of the reviewed techniques in the biomedical field. Results: QPI has been successfully applied to 3D sample imaging. The scattering-based contrast provides measurements of intrinsic quantities of the sample that are indicative of disease state, stage of growth, or overall dynamics. Conclusions: We reviewed state-of-the-art QPI techniques for 3D imaging and dynamics estimation of biological samples. Both theoretical and experimental aspects of various techniques were discussed. We also presented the applications of the discussed techniques as applied to biomedicine and biology research.

Label-free three-dimensional imaging and quantitative analysis of living fibroblasts and myofibroblasts by holotomographic microscopy.

Holotomography (HT) is a cutting-edge fast live-cell quantitative label-free imaging technique. Based on the principle of quantitative phase imaging, it combines holography and tomography to record a three-dimensional map of the refractive index, used as intrinsic optical and quantitative imaging contrast parameter of biological samples, at a sub-micrometer spatial resolution. In this study HT has been employed for the first time to analyze the changes of fibroblasts differentiating towards myofibroblasts - recognized as the main cell player of fibrosis - when cultured in vitro with the pro-fibrotic factor, namely transforming growth factor-ß1. In parallel, F-actin, vinculin, α-smooth muscle actin, phospho-myosin light chain 2, type-1 collagen, peroxisome proliferator-activated receptor-gamma coactivator-1α expression and mitochondria were evaluated by confocal laser scanning microscopy. Plasmamembrane passive properties and transient receptor potential canonical channels' currents were also recorded by whole-cell patch-clamp. The fluorescence images and electrophysiological results have been compared to the data obtained by HT and their congruence has been discussed. HT turned out to be a valid approach to morphologically distinguish fibroblasts from well differentiated myofibroblasts while obtaining objective measures concerning volume, surface area, projection area, surface index and dry mass (i.e., the mass of the non-aqueous content inside the cell including proteins and subcellular organelles) of the entire cell, nuclei and nucleoli with the major advantage to monitor outer and inner features in living cells in a non-invasive, rapid and label-free approach. HT might open up new research opportunities in the field of fibrotic diseases. RESEARCH HIGHLIGHTS: Holotomography (HT) is a label-free laser interferometric imaging technology exploiting the intrinsic optical property of cells namely refractive index (RI) to enable a direct imaging and analysis of whole cells or intracellular organelles. HT turned out a valid approach to distinguish morphological features of living unlabeled fibroblasts from differentiated myofibroblasts. HT provided quantitative information concerning volume, surface area, projection area, surface index and dry mass of the entire fibroblasts/myofibroblasts, nuclei and nucleoli.

Correlative Raman Imaging: Development and Cancer Applications.

Despite extensive research efforts, cancer continues to stand as one of the leading causes of death on a global scale. To gain profound insights into the intricate mechanisms underlying cancer onset and progression, it is imperative to possess methodologies that allow the study of cancer cells at the single-cell level, focusing on critical parameters such as cell morphology, metabolism, and molecular characteristics. These insights are essential for effectively discerning between healthy and cancerous cells and comprehending tumoral progression. Recent advancements in microscopy techniques have significantly advanced the study of cancer cells, with Raman microspectroscopy (RM) emerging as a particularly powerful tool. Indeed, RM can provide both biochemical and spatial details at the single-cell level without the need for labels or causing disruptions to cell integrity. Moreover, RM can be correlated with other microscopy techniques, creating a synergy that offers a spectrum of complementary insights into cancer cell morphology and biology. This review aims to explore the correlation between RM and other microscopy techniques such as confocal fluoresce microscopy (CFM), atomic force microscopy (AFM), digital holography microscopy (DHM), and mass spectrometry imaging (MSI). Each of these techniques has their own strengths, providing different perspectives and parameters about cancer cell features. The correlation between information from these various analysis methods is a valuable tool for physicians and researchers, aiding in the comprehension of cancer cell morphology and biology, unraveling mechanisms underlying cancer progression, and facilitating the development of early diagnosis and/or monitoring cancer progression.

Enhanced Quantitative Wavefront Imaging for Nano-Object Characterization.

Quantitative phase imaging enables precise and label-free characterizations of individual nano-objects within a large volume, without a priori knowledge of the sample or imaging system. While emerging common path implementations are simple enough to promise a broad dissemination, their phase sensitivity still falls short of precisely estimating the mass or polarizability of vesicles, viruses, or nanoparticles in single-shot acquisitions. In this paper, we revisit the Zernike filtering concept, originally crafted for intensity-only detectors, with the aim of adapting it to wavefront imaging. We demonstrate, through numerical simulation and experiments based on high-resolution wavefront sensing, that a simple Fourier-plane add-on can significantly enhance phase sensitivity for subdiffraction objects─achieving over an order of magnitude increase (×12)─while allowing the quantitative retrieval of both intensity and phase. This advancement allows for more precise nano-object detection and metrology.

Capturing cell morphology dynamics with high temporal resolution using single-shot quantitative phase gradient imaging.

Significance: Label-free quantitative phase imaging can potentially measure cellular dynamics with minimal perturbation, motivating efforts to develop faster and more sensitive instrumentation. We characterize fast, single-shot quantitative phase gradient microscopy (ss-QPGM) that simultaneously acquires multiple polarization components required to reconstruct phase images. We integrate a computationally efficient least squares algorithm to provide real-time, video-rate imaging (up to 75 frames / s ). The developed instrument was used to observe changes in cellular morphology and correlate these to molecular measures commonly obtained by staining. Aim: We aim to characterize a fast approach to ss-QPGM and record morphological changes in single-cell phase images. We also correlate these with biochemical changes indicating cell death using concurrently acquired fluorescence images. Approach: Here, we examine nutrient deprivation and anticancer drug-induced cell death in two different breast cell lines, viz., M2 and MCF7. Our approach involves in-line measurements of ss-QPGM and fluorescence imaging of the cells biochemically labeled for viability. Results: We validate the accuracy of the phase measurement using a USAF1951 pattern phase target. The ss-QPGM system resolves 912.3 lp / mm , and our analysis scheme accurately retrieves the phase with a high correlation coefficient ( ∼ 0.99 ), as measured by calibrated sample thicknesses. Analyzing the contrast in phase, we estimate the spatial resolution achievable to be 0.55 µ m for this microscope. ss-QPGM time-lapse live-cell imaging reveals multiple intracellular and morphological changes during biochemically induced cell death. Inferences from co-registered images of quantitative phase and fluorescence suggest the possibility of necrosis, which agrees with previous findings. Conclusions: Label-free ss-QPGM with high-temporal resolution and high spatial fidelity is demonstrated. Its application for monitoring dynamic changes in live cells offers promising prospects.

Information-Distilled Generative Label-Free Morphological Profiling Encodes Cellular Heterogeneity.

Image-based cytometry faces challenges due to technical variations arising from different experimental batches and conditions, such as differences in instrument configurations or image acquisition protocols, impeding genuine biological interpretation of cell morphology. Existing solutions, often necessitating extensive pre-existing data knowledge or control samples across batches, have proved limited, especially with complex cell image data. To overcome this, "Cyto-Morphology Adversarial Distillation" (CytoMAD), a self-supervised multi-task learning strategy that distills biologically relevant cellular morphological information from batch variations, is introduced to enable integrated analysis across multiple data batches without complex data assumptions or extensive manual annotation. Unique to CytoMAD is its "morphology distillation", symbiotically paired with deep-learning image-contrast translation-offering additional interpretable insights into label-free cell morphology. The versatile efficacy of CytoMAD is demonstrated in augmenting the power of biophysical imaging cytometry. It allows integrated label-free classification of human lung cancer cell types and accurately recapitulates their progressive drug responses, even when trained without the drug concentration information. CytoMAD  also allows joint analysis of tumor biophysical cellular heterogeneity, linked to epithelial-mesenchymal plasticity, that standard fluorescence markers overlook. CytoMAD can substantiate the wide adoption of biophysical cytometry for cost-effective diagnosis and screening.

Eagle-Eye Inspired Meta-Device for Phase Imaging.

The dual-focus vision observed in eagles' eyes is an intriguing phenomenon captivates scientists since a long time. Inspired by this natural occurrence, the authors' research introduces a novel bifocal meta-device incorporating a polarized camera capable of simultaneously capturing images for two different polarizations with slightly different focal distances. This innovative approach facilitates the concurrent acquisition of underfocused and overfocused images in a single snapshot, enabling the effective extraction of quantitative phase information from the object using the transport of intensity equation. Experimental demonstrations showcase the application of quantitative phase imaging to artificial objects and human embryonic kidney cells, particularly emphasizing the meta-device's relevance in dynamic scenarios such as laser-induced ablation in human embryonic kidney cells. Moreover, it provides a solution for the quantification during the dynamic process at the cellular level. Notably, the proposed eagle-eye inspired meta-device for phase imaging (EIMPI), due to its simplicity and compact nature, holds promise for significant applications in fields such as endoscopy and headsets, where a lightweight and compact setup is essential.

Multimodal 2D and 3D microscopic mapping of growth cartilage by computational imaging techniques - a short review including new research.

Being able to image the microstructure of growth cartilage is important for understanding the onset and progression of diseases such as osteochondrosis and osteoarthritis, as well as for developing new treatments and implants. Studies of cartilage using conventional optical brightfield microscopy rely heavily on histological staining, where the added chemicals provide tissue-specific colours. Other microscopy contrast mechanisms include polarization, phase- and scattering contrast, enabling non-stained or 'label-free' imaging that significantly simplifies the sample preparation, thereby also reducing the risk of artefacts. Traditional high-performance microscopes tend to be both bulky and expensive.Computational imagingdenotes a range of techniques where computers with dedicated algorithms are used as an integral part of the image formation process. Computational imaging offers many advantages like 3D measurements, aberration correction and quantitative phase contrast, often combined with comparably cheap and compact hardware. X-ray microscopy is also progressing rapidly, in certain ways trailing the development of optical microscopy. In this study, we first briefly review the structures of growth cartilage and relevant microscopy characterization techniques, with an emphasis on Fourier ptychographic microscopy (FPM) and advanced x-ray microscopies. We next demonstrate with our own results computational imaging through FPM and compare the images with hematoxylin eosin and saffron (HES)-stained histology. Zernike phase contrast, and the nonlinear optical microscopy techniques of second harmonic generation (SHG) and two-photon excitation fluorescence (TPEF) are explored. Furthermore, X-ray attenuation-, phase- and diffraction-contrast computed tomography (CT) images of the very same sample are presented for comparisons. Future perspectives on the links to artificial intelligence, dynamic studies andin vivopossibilities conclude the article.

A human erythrocytes hologram dataset for learning-based model training.

This manuscript presents a paired dataset with experimental holograms and their corresponding reconstructed phase maps of human red blood cells (RBCs). The holographic images were recorded using an off-axis telecentric Digital Holographic Microscope (DHM). The imaging system consists of a 40 × /0.65NA infinity-corrected microscope objective (MO) lens and a tube lens (TL) with a focal distance of 200 mm, recording diffraction-limited holograms. A CMOS camera with dimensions of 1920 × 1200 pixels and a pixel pitch of 5.86 µm was located at the back focal plane of the TL lens, capturing image-plane holograms. The off-axis, telecentric, and diffraction-limited DHM system guarantees accurate quantitative phase maps. Initially comprising 300 holograms, the dataset was augmented to 36,864 instances, enabling the investigation (i.e., training and testing) of learning-based models to reconstruct aberration-free phase images from raw holograms. This dataset facilitates the training and testing of end-to-end models for quantitative phase imaging using DHM systems operating at the telecentric regime and non-telecentric DHM systems where the spherical wavefront has been compensated physically. In other words, this dataset holds promise for advancing investigations in digital holographic microscopy and computational imaging.

High-resolution cell imaging using white light phase shifting interferometry and iterative phase deconvolution.

An optimization algorithm is presented for the deconvolution of a complex field to improve the resolution and accuracy of quantitative phase imaging (QPI). A high-resolution phase map can be recovered by solving a constrained optimization problem of deconvolution using a complex gradient operator. The method is demonstrated on phase measurements of samples using a white light based phase shifting interferometry (WLPSI) method. The application of the algorithm on real and simulated objects shows a significant resolution and contrast improvement. Experiments performed on Escherichia coli bacterium have revealed its sub-cellular structures that were not visible in the raw WLPSI images obtained using a five phase shifting method. These features can give valuable insights into the structures and functioning of biological cells. The algorithm is simple in implementation and can be incorporated into other QPI modalities .

Stable Dual miR-143 and miR-506 Upregulation Inhibits Proliferation and Cell Cycle Progression.

The mainstays of lung cancer pathogenesis are cell cycle progression dysregulation, impaired apoptosis, and unregulated cell proliferation. While individual microRNA (miR) targeting or delivering is a promising approach that has been extensively studied, combination of miR targeting can enhance therapeutic efficacy and overcome limitations present in individual miR regulations. We previously reported on the use of a miR-143 and miR-506 combination via transient transfections against lung cancer. In this study, we evaluated the effect of miR-143 and miR-506 under stable deregulations in A549 lung cancer cells. We used lentiviral transductions to either up- or downregulate the two miRs individually or in combination. The cells were sorted and analyzed for miR deregulation via qPCR. We determined the miR deregulations' effects on the cell cycle, cell proliferation, cancer cell morphology, and cell motility. Compared to the individual miR deregulations, the combined miR upregulation demonstrated a miR-expression-dependent G2 cell cycle arrest and a significant increase in the cell doubling time, whereas the miR-143/506 dual downregulation demonstrated increased cellular motility. Furthermore, the individual miR-143 and miR-506 up- and downregulations exhibited cellular responses lacking an apparent miR-expression-dependent response in the respective analyses. Our work here indicates that, unlike the individual miR upregulations, the combinatorial miR treatment remained advantageous, even under prolonged miR upregulation. Finally, our findings demonstrate potential advantages of miR combinations vs. individual miR treatments.

Classifying breast cancer and fibroadenoma tissue biopsies from paraffined stain-free slides by fractal biomarkers in Fourier Ptychographic Microscopy.

Breast cancer is one of the most spread and monitored pathologies in high-income countries. After breast biopsy, histological tissue is stored in paraffin, sectioned and mounted. Conventional inspection of tissue slides under benchtop light microscopes involves paraffin removal and staining, typically with H&E. Then, expert pathologists are called to judge the stained slides. However, paraffin removal and staining are operator-dependent, time and resources consuming processes that can generate ambiguities due to non-uniform staining. Here we propose a novel method that can work directly on paraffined stain-free slides. We use Fourier Ptychography as a quantitative phase-contrast microscopy method, which allows accessing a very wide field of view (i.e., mm2) in one single image while guaranteeing high lateral resolution (i.e., 0.5 µm). This imaging method is multi-scale, since it enables looking at the big picture, i.e. the complex tissue structure and connections, with the possibility to zoom-in up to the single-cell level. To handle this informative image content, we introduce elements of fractal geometry as multi-scale analysis method. We show the effectiveness of fractal features in describing and classifying fibroadenoma and breast cancer tissue slides from ten patients with very high accuracy. We reach 94.0 ± 4.2% test accuracy in classifying single images. Above all, we show that combining the decisions of the single images, each patient's slide can be classified with no error. Besides, fractal geometry returns a guide map to help pathologist to judge the different tissue portions based on the likelihood these can be associated to a breast cancer or fibroadenoma biomarker. The proposed automatic method could significantly simplify the steps of tissue analysis and make it independent from the sample preparation, the skills of the lab operator and the pathologist.

Quantitative Phase Imaging as Sensitive Screening Method for Nanoparticle-Induced Cytotoxicity Assessment.

The assessment of nanoparticle cytotoxicity is challenging due to the lack of customized and standardized guidelines for nanoparticle testing. Nanoparticles, with their unique properties, can interfere with biochemical test methods, so multiple tests are required to fully assess their cellular effects. For a more reliable and comprehensive assessment, it is therefore imperative to include methods in nanoparticle testing routines that are not affected by particles and allow for the efficient integration of additional molecular techniques into the workflow. Digital holographic microscopy (DHM), an interferometric variant of quantitative phase imaging (QPI), has been demonstrated as a promising method for the label-free assessment of the cytotoxic potential of nanoparticles. Due to minimal interactions with the sample, DHM allows for further downstream analyses. In this study, we investigated the capabilities of DHM in a multimodal approach to assess cytotoxicity by directly comparing DHM-detected effects on the same cell population with two downstream biochemical assays. Therefore, the dry mass increase in RAW 264.7 macrophages and NIH-3T3 fibroblast populations measured by quantitative DHM phase contrast after incubation with poly(alkyl cyanoacrylate) nanoparticles for 24 h was compared to the cytotoxic control digitonin, and cell culture medium control. Viability was then determined using a metabolic activity assay (WST-8). Moreover, to determine cell death, supernatants were analyzed for the release of the enzyme lactate dehydrogenase (LDH assay). In a comparative analysis, in which the average half-maximal effective concentration (EC50) of the nanocarriers on the cells was determined, DHM was more sensitive to the effect of the nanoparticles on the used cell lines compared to the biochemical assays.

Perspective on quantitative phase imaging to improve precision cancer medicine.

Significance: Quantitative phase imaging (QPI) offers a label-free approach to non-invasively characterize cellular processes by exploiting their refractive index based intrinsic contrast. QPI captures this contrast by translating refractive index associated phase shifts into intensity-based quantifiable data with nanoscale sensitivity. It holds significant potential for advancing precision cancer medicine by providing quantitative characterization of the biophysical properties of cells and tissue in their natural states. Aim: This perspective aims to discuss the potential of QPI to increase our understanding of cancer development and its response to therapeutics. It also explores new developments in QPI methods towards advancing personalized cancer therapy and early detection. Approach: We begin by detailing the technical advancements of QPI, examining its implementations across transmission and reflection geometries and phase retrieval methods, both interferometric and non-interferometric. The focus then shifts to QPI's applications in cancer research, including dynamic cell mass imaging for drug response assessment, cancer risk stratification, and in-vivo tissue imaging. Results: QPI has emerged as a crucial tool in precision cancer medicine, offering insights into tumor biology and treatment efficacy. Its sensitivity to detecting nanoscale changes holds promise for enhancing cancer diagnostics, risk assessment, and prognostication. The future of QPI is envisioned in its integration with artificial intelligence, morpho-dynamics, and spatial biology, broadening its impact in cancer research. Conclusions: QPI presents significant potential in advancing precision cancer medicine and redefining our approach to cancer diagnosis, monitoring, and treatment. Future directions include harnessing high-throughput dynamic imaging, 3D QPI for realistic tumor models, and combining artificial intelligence with multi-omics data to extend QPI's capabilities. As a result, QPI stands at the forefront of cancer research and clinical application in cancer care.

CellSNAP: a fast, accurate algorithm for 3D cell segmentation in quantitative phase imaging.

Significance: Three-dimensional quantitative phase imaging (QPI) has rapidly emerged as a complementary tool to fluorescence imaging, as it provides an objective measure of cell morphology and dynamics, free of variability due to contrast agents. It has opened up new directions of investigation by providing systematic and correlative analysis of various cellular parameters without limitations of photobleaching and phototoxicity. While current QPI systems allow the rapid acquisition of tomographic images, the pipeline to analyze these raw three-dimensional (3D) tomograms is not well-developed. We focus on a critical, yet often underappreciated, step of the analysis pipeline that of 3D cell segmentation from the acquired tomograms. Aim: We report the CellSNAP (Cell Segmentation via Novel Algorithm for Phase Imaging) algorithm for the 3D segmentation of QPI images. Approach: The cell segmentation algorithm mimics the gemstone extraction process, initiating with a coarse 3D extrusion from a two-dimensional (2D) segmented mask to outline the cell structure. A 2D image is generated, and a segmentation algorithm identifies the boundary in the x-y plane. Leveraging cell continuity in consecutive z-stacks, a refined 3D segmentation, akin to fine chiseling in gemstone carving, completes the process. Results: The CellSNAP algorithm outstrips the current gold standard in terms of speed, robustness, and implementation, achieving cell segmentation under 2 s per cell on a single-core processor. The implementation of CellSNAP can easily be parallelized on a multi-core system for further speed improvements. For the cases where segmentation is possible with the existing standard method, our algorithm displays an average difference of 5% for dry mass and 8% for volume measurements. We also show that CellSNAP can handle challenging image datasets where cells are clumped and marred by interferogram drifts, which pose major difficulties for all QPI-focused AI-based segmentation tools. Conclusion: Our proposed method is less memory intensive and significantly faster than existing methods. The method can be easily implemented on a student laptop. Since the approach is rule-based, there is no need to collect a lot of imaging data and manually annotate them to perform machine learning based training of the model. We envision our work will lead to broader adoption of QPI imaging for high-throughput analysis, which has, in part, been stymied by a lack of suitable image segmentation tools.

Label-Free Visualization and Morphological Profiling of Neuronal Differentiation and Axonal Degeneration through Quantitative Phase Imaging.

Understanding the intricate processes of neuronal growth, degeneration, and neurotoxicity is paramount for unraveling nervous system function and holds significant promise in improving patient outcomes, especially in the context of chemotherapy-induced peripheral neuropathy (CIPN). These processes are influenced by a broad range of entwined events facilitated by chemical, electrical, and mechanical signals. The progress of each process is inherently linked to phenotypic changes in cells. Currently, the primary means of demonstrating morphological changes rely on measurements of neurite outgrowth and axon length. However, conventional techniques for monitoring these processes often require extensive preparation to enable manual or semi-automated measurements. Here, a label-free and non-invasive approach is employed for monitoring neuronal differentiation and degeneration using quantitative phase imaging (QPI). Operating on unlabeled specimens and offering little to no phototoxicity and photobleaching, QPI delivers quantitative maps of optical path length delays that provide an objective measure of cellular morphology and dynamics. This approach enables the visualization and quantification of axon length and other physical properties of dorsal root ganglion (DRG) neuronal cells, allowing greater understanding of neuronal responses to stimuli simulating CIPN conditions. This research paves new avenues for the development of more effective strategies in the clinical management of neurotoxicity.