Localization of unlabeled bepirovirsen antisense oligonucleotide in murine tissues using in situ hybridization and CARS imaging.

Current methods for detecting unlabeled antisense oligonucleotide (ASO) drugs rely on immunohistochemistry (IHC) and/or conjugated molecules, which lack sufficient sensitivity, specificity, and resolution to fully investigate their biodistribution. Our aim was to demonstrate the qualitative and quantitative distribution of unlabeled bepirovirsen, a clinical stage ASO, in livers and kidneys of dosed mice using novel staining and imaging technologies at subcellular resolution. ASOs were detected in formalin-fixed paraffin-embedded (FFPE) and frozen tissues using an automated chromogenic in situ hybridization (ISH) assay: miRNAscope. This was then combined with immunohistochemical detection of cell lineage markers. ASO distribution in hepatocytes versus nonparenchymal cell lineages was quantified using HALO AI image analysis. To complement this, hyperspectral coherent anti-Stokes Raman scattering (HS-CARS) imaging microscopy was used to specifically detect the unique cellular Raman spectral signatures following ASO treatment. Bepirovirsen was localized primarily in nonparenchymal liver cells and proximal renal tubules. Codetection of ASO with distinct cell lineage markers of liver and kidney populations aided target cell identity facilitating quantification. Positive liver signal was quantified using HALO AI, with 12.9% of the ASO localized to the hepatocytes and 87.1% in nonparenchymal cells. HS-CARS imaging specifically detected ASO fingerprints based on the unique vibrational signatures following unlabeled ASO treatment in a totally nonperturbative manner at subcellular resolution. Together, these novel detection and imaging modalities represent a significant increase in our ability to detect unlabeled ASOs in tissues, demonstrating improved levels of specificity and resolution. These methods help us understand their underlying mechanisms of action and ultimately improve the therapeutic potential of these important drugs for treating globally significant human diseases.

Weakly Supervised Identification and Localization of Drug Fingerprints Based on Label-Free Hyperspectral CARS Microscopy.

Understanding drug fingerprints in complex biological samples is essential for the development of a drug. Hyperspectral coherent anti-Stokes Raman scattering (HS-CARS) microscopy, a label-free nondestructive chemical imaging technique, can profile biological samples based on their endogenous vibrational contrast. Here, we propose a deep learning-assisted HS-CARS imaging approach for the investigation of drug fingerprints and their localization at single-cell resolution. To identify and localize drug fingerprints in complex biological systems, an attention-based deep neural network, hyperspectral attention net (HAN), was developed. By formulating the task to a multiple instance learning problem, HAN highlights informative regions through the attention mechanism when being trained on whole-image labels. Using the proposed technique, we investigated the drug fingerprints of a hepatitis B virus therapy in murine liver tissues. With the increase in drug dosage, higher classification accuracy was observed, with an average area under the curve (AUC) of 0.942 for the high-dose group. Besides, highly informative tissue structures predicted by HAN demonstrated a high degree of similarity with the drug localization shown by the in situ hybridization staining results. These results demonstrate the potential of the proposed deep learning-assisted optical imaging technique for the label-free profiling, identification, and localization of drug fingerprints in biological samples, which can be extended to nonperturbative investigations of complex biological systems under various biological conditions.

Label-free visualization and characterization of extracellular vesicles in breast cancer.

Despite extensive interest, extracellular vesicle (EV) research remains technically challenging. One of the unexplored gaps in EV research has been the inability to characterize the spatially and functionally heterogeneous populations of EVs based on their metabolic profile. In this paper, we utilize the intrinsic optical metabolic and structural contrast of EVs and demonstrate in vivo/in situ characterization of EVs in a variety of unprocessed (pre)clinical samples. With a pixel-level segmentation mask provided by the deep neural network, individual EVs can be analyzed in terms of their optical signature in the context of their spatial distribution. Quantitative analysis of living tumor-bearing animals and fresh excised human breast tissue revealed abundance of NAD(P)H-rich EVs within the tumor, near the tumor boundary, and around vessel structures. Furthermore, the percentage of NAD(P)H-rich EVs is highly correlated with human breast cancer diagnosis, which emphasizes the important role of metabolic imaging for EV characterization as well as its potential for clinical applications. In addition to the characterization of EV properties, we also demonstrate label-free monitoring of EV dynamics (uptake, release, and movement) in live cells and animals. The in situ metabolic profiling capacity of the proposed method together with the finding of increasing NAD(P)H-rich EV subpopulations in breast cancer have the potential for empowering applications in basic science and enhancing our understanding of the active metabolic roles that EVs play in cancer progression.

Single-photon peak event detection (SPEED): a computational method for fast photon counting in fluorescence lifetime imaging microscopy.

Fluorescence lifetime imaging microscopy (FLIM) characterizes samples by examining the temporal properties of fluorescence emission, providing useful contrast within samples based on the local physical and biochemical environment of fluorophores. Despite this, FLIM applications have been limited in scope by either poor accuracy or long acquisition times. Here, we present a method for computational single-photon counting of directly sampled time-domain FLIM data that is capable of accurate fluorescence lifetime and intensity measurements while acquiring over 160 Mega-counts-per-second with sub-nanosecond time resolution between consecutive photon counts. We demonstrate that our novel method of Single-photon PEak Event Detection (SPEED) is more accurate than direct pulse sampling and faster than established photon counting FLIM methods. We further show that SPEED can be implemented for imaging and quantifying samples that benefit from higher -throughput and -dynamic range imaging with real-time GPU-accelerated processing and use this capability to examine the NAD(P)H-related metabolic dynamics of apoptosis in human breast cancer cells. Computational methods for photon counting such as SPEED open up more opportunities for fast and accurate FLIM imaging and additionally provide a basis for future innovation into alternative FLIM techniques.

Computational adaptive optics for polarization-sensitive optical coherence tomography.

Defocus aberration in optical systems, including optical coherence tomography (OCT) systems employing Gaussian illumination, gives rise to the well-known compromise between transverse resolution and depth-of-field. This results in blurry images when out-of-focus, whilst other low-order aberrations (e.g., astigmatism, coma, etc.) present in both the OCT system and biological samples further reduce image resolution and contrast. Computational adaptive optics (CAO) is a computed optical interferometric imaging technique that modifies the phase of the OCT data in the spatial frequency domain to correct optical aberrations and provide improvement of the image quality throughout the three-dimensional (3D) volume. In this Letter, we report the first implementation of CAO for polarization-sensitive OCT to correct defocus and other low-order aberrations, providing enhanced polarization-sensitive imaging contrast (i.e., intensity and phase retardation) on a 3D OCT phantom, molded plastics, ex vivo chicken breast tissue, and ex vivo human breast cancer tissue.

Intraoperative Label-Free Multimodal Nonlinear Optical Imaging for Point-of-Procedure Cancer Diagnostics.

Intraoperative imaging in surgical oncology can provide information about the tumor microenvironment as well as information about the tumor margin. Visualizing microstructural features and molecular and functional dynamics may provide important diagnostic and prognostic information, especially when obtained in real-time at the point-of-procedure. A majority of current intraoperative optical techniques are based on the use of the labels, such as fluorescent dyes. However, these exogenous agents disrupt the natural microenvironment, perturb biological processes, and alter the endogenous optical signatures that cells and the microenvironment can provide. Portable nonlinear imaging systems have enabled intraoperative imaging for real-time detection and diagnosis of tissue. We review the development of a label-free multimodal nonlinear optical imaging technique that was adapted into a portable imaging system for intraoperative optical assessment of resected human breast tissue. New developments have applied this technology to assessing needle-biopsy specimens. Needle-biopsy procedures most always precede surgical resection and serve as the first sampling of suspicious masses for diagnosis. We demonstrate the diagnostic feasibility of imaging core needle-biopsy specimens during veterinary cancer surgeries. This intraoperative label-free multimodal nonlinear optical imaging technique can potentially provide a powerful tool to assist in cancer diagnosis at the point-of-procedure.

Compressive sensing for polarization sensitive optical coherence tomography.

In this report, we report on the implementation of compressive sensing (CS) and sparse sampling in polarization sensitive optical coherence tomography (PS-OCT) to reduce the number of B-scans (frames consisting of an array of A-scans, where each represents a single depth profile of reflections) required for effective volumetric (3D dataset composed of an array of B-scans) PS-OCT measurements (i.e. OCT intensity, and phase retardation) reconstruction. Sparse sampling of PS-OCT is achieved through randomization of step sizes along the slow-axis of PS-OCT imaging, covering the same spatial ranges as those with equal slow-axis step sizes, but with a reduced number of B-scans. Tested on missing B-scan rates of 25%, 50% and 75%, we found CS could reconstruct reasonably good (as evidenced by a correlation coefficient >0.6) PS-OCT measurements with a maximum reduced B-scan rate of 50%, thereby accelerating and doubling the rate of volumetric PS-OCT measurements.

Label-Free Multimodal Multiphoton Intravital Imaging.

Label-free intravital optical imaging is an emergent visualization tool that is not only useful for basic biological research, but also for preclinical research with potential translational clinical applications. The complete absence of exogenous labeling or genetic alterations avoids plausible harmful perturbation to biological processes and the pristine physiological environment, as the endogenous biomolecules enable intrinsic imaging contrasts to interrogate various live multicellular organisms of interest. This tool has evolved from single-modality, single-photon imaging into multimodal multiphoton imaging, in order to gain different contrasts simultaneously during imaging sessions, and permit long-term time-lapse studies that have begun to spawn more diverse applications.

In vivo characterization of minipig skin as a model for dermatological research using multiphoton microscopy.

Minipig skin is one of the most widely used non-rodent animal skin models for dermatological research. A thorough characterization of minipig skin is essential for gaining deeper understanding of its structural and functional similarities with human skin. In this study, three-dimensional (3-D) in vivo images of minipig skin was obtained non-invasively using a multimodal optical imaging system capable of acquiring two-photon excited fluorescence (TPEF) and fluorescence lifetime imaging microscopy (FLIM) images simultaneously. The images of the structural features of different layers of the minipig skin were qualitatively and quantitatively compared with those of human skin. Label-free imaging of skin was possible due to the endogenous fluorescence and optical properties of various components in the skin such as keratin, nicotinamide adenine dinucleotide phosphate (NAD(P)H), melanin, elastin, and collagen. This study demonstrates the capability of optical biopsy techniques, such as TPEF and FLIM, for in vivo non-invasive characterization of cellular and functional features of minipig skin, and the optical image-based similarities of this commonly utilized model of human skin. These optical imaging techniques have the potential to become promising tools in dermatological research for developing a better understanding of animal skin models, and for aiding in translational pre-clinical to clinical studies.

Characterization of Magnetic Nanoparticle-Seeded Microspheres for Magnetomotive and Multimodal Imaging.

Magnetic iron-oxide nanoparticles have been developed as contrast agents in magnetic resonance imaging (MRI) and as therapeutic agents in magnetic hyperthermia. They have also recently been demonstrated as contrast and elastography agents in magnetomotive optical coherence tomography and elastography (MM-OCT and MM-OCE, respectively). Protein-shell microspheres containing suspensions of these magnetic nanoparticles in lipid cores, and with functionalized outer shells for specific targeting, have also been demonstrated as efficient contrast agents for imaging modalities such as MM-OCT and MRI, and can be easily modified for other modalities such as ultrasound, fluorescence, and luminescence imaging. By leveraging the benefits of these various imaging modalities with the use of only a single agent, a magnetic microsphere, it becomes possible to use a widefield imaging method (such as MRI or small animal fluorescence imaging) to initially locate the agent, and then use MM-OCT to obtain dynamic contrast images with cellular level morphological resolution. In addition to multimodal contrast-enhanced imaging, these microspheres could serve as drug carriers for targeted delivery under image guidance. Although the preparation and surface modifications of protein microspheres containing iron oxide nanoparticles has been previously described and feasibility studies conducted, many questions regarding their production and properties remain. Since the use of multifunctional microspheres could have high clinical relevance, here we report a detailed characterization of their properties and behavior in different environments to highlight their versatility. The work presented here is an effort for the development and optimization of nanoparticle-based microspheres as multi-modal contrast agents that can bridge imaging modalities on different size scales, especially for their use in MM-OCT and MRI imaging.

Intraoperative optical coherence tomography for soft tissue sarcoma differentiation and margin identification.

BACKGROUND AND OBJECTIVE: Sarcomas are rare but highly aggressive tumors, and local recurrence after surgical excision can occur in up to 50% cases. Therefore, there is a strong clinical need for accurate tissue differentiation and margin assessment to reduce incomplete resection and local recurrence. The purpose of this study was to investigate the use of optical coherence tomography (OCT) and a novel image texture-based processing algorithm to differentiate sarcoma from muscle and adipose tissue. STUDY DESIGN AND METHODS: In this study, tumor margin delineation in 19 feline and canine veterinary patients was achieved with intraoperative OCT to help validate tumor resection. While differentiation of lower-scattering adipose tissue from higher-scattering muscle and tumor tissue was relatively straightforward, it was more challenging to distinguish between dense highly scattering muscle and tumor tissue types based on scattering intensity and microstructural features alone. To improve tissue-type differentiation in a more objective and automated manner, three descriptive statistical metrics, namely the coefficient of variation (CV), standard deviation (STD), and Range, were implemented in a custom algorithm applied to the OCT images. RESULTS: Over 22,800 OCT images were collected intraoperatively from over 38 sites on 19 ex vivo tissue specimens removed during sarcoma surgeries. Following the generation of an initial set of OCT images correlated with standard hematoxylin and eosin-stained histopathology, over 760 images were subsequently used for automated analysis. Using texture-based image processing metrics, OCT images of sarcoma, muscle, and adipose tissue were all found to be statistically different from one another (P ≤ 0.001). CONCLUSION: These results demonstrate the potential of using intraoperative OCT, along with an automated tissue differentiation algorithm, as a guidance tool for soft tissue sarcoma margin delineation in the operating room. Lasers Surg. Med. 49:240-248, 2017. © 2017 Wiley Periodicals, Inc.

Longitudinal in vivo tracking of adverse effects following topical steroid treatment.

Topical steroids are known for their anti-inflammatory properties and are commonly prescribed to treat many adverse skin conditions such as eczema and psoriasis. While these treatments are known to be effective, adverse effects including skin atrophy are common. In this study, the progression of these effects is investigated in an in vivo mouse model using multimodal optical microscopy. Utilizing a system capable of performing two-photon excitation fluorescence microscopy (TPEF) of reduced nicotinamide adenine dinucleotide (NADH) to visualize the epidermal cell layers and second harmonic generation (SHG) microscopy to identify collagen in the dermis, these processes can be studied at the cellular level. Fluorescence lifetime imaging microscopy (FLIM) is also utilized to image intracellular NADH levels to obtain molecular information regarding metabolic activity following steroid treatment. In this study, fluticasone propionate (FP)-treated, mometasone furoate (MF)-treated and untreated animals were imaged longitudinally using a custom-built multimodal optical microscope. Prolonged steroid treatment over the course of 21 days is shown to result in a significant increase in mean fluorescence lifetime of NADH, suggesting a faster rate of maturation of epidermal keratinocytes. Alterations to collagen organization and the structural microenvironment are also observed. These results give insight into the structural and biochemical processes of skin atrophy associated with prolonged steroid treatment.

Intraoperative optical coherence tomography for assessing human lymph nodes for metastatic cancer.

BACKGROUND: Evaluation of lymph node (LN) status is an important factor for detecting metastasis and thereby staging breast cancer. Currently utilized clinical techniques involve the surgical disruption and resection of lymphatic structure, whether nodes or axillary contents, for histological examination. While reasonably effective at detection of macrometastasis, the majority of the resected lymph nodes are histologically negative. Improvements need to be made to better detect micrometastasis, minimize or eliminate lymphatic disruption complications, and provide immediate and accurate intraoperative feedback for in vivo cancer staging to better guide surgery. METHODS: We evaluated the use of optical coherence tomography (OCT), a high-resolution, real-time, label-free imaging modality for the intraoperative assessment of human LNs for metastatic disease in patients with breast cancer. We assessed the sensitivity and specificity of double-blinded trained readers who analyzed intraoperative OCT LN images for presence of metastatic disease, using co-registered post-operative histopathology as the gold standard. RESULTS: Our results suggest that intraoperative OCT examination of LNs is an appropriate real-time, label-free, non-destructive alternative to frozen-section analysis, potentially offering faster interpretation and results to empower superior intraoperative decision-making. CONCLUSIONS: Intraoperative OCT has strong potential to supplement current post-operative histopathology with real-time in situ assessment of LNs to preserve both non-cancerous nodes and their lymphatic vessels, and thus reduce the associated risks and complications from surgical disruption of lymphoid structures following biopsy.

Magnetomotive Optical Coherence Elastography for Magnetic Hyperthermia Dosimetry Based on Dynamic Tissue Biomechanics.

Magnetic nanoparticles (MNPs) have been used in many diagnostic and therapeutic biomedical applications over the past few decades to enhance imaging contrast, steer drugs to targets, and treat tumors via hyperthermia. Optical coherence tomography (OCT) is an optical biomedical imaging modality that relies on the detection of backscattered light to generate high-resolution cross-sectional images of biological tissue. MNPs have been utilized as imaging contrast and perturbative mechanical agents in OCT in techniques called magnetomotive OCT (MM-OCT) and magnetomotive elastography (MM-OCE), respectively. MNPs have also been independently used for magnetic hyperthermia treatments, enabling therapeutic functions such as killing tumor cells. It is well known that the localized tissue heating during hyperthermia treatments result in a change in the biomechanical properties of the tissue. Therefore, we propose a novel dosimetric technique for hyperthermia treatment based on the viscoelasticity change detected by MM-OCE, further enabling the theranostic function of MNPs. In this paper, we first review the basic principles and applications of MM-OCT, MM-OCE, and magnetic hyperthermia, and present new preliminary results supporting the concept of MM-OCE-based hyperthermia dosimetry.

Optical parametrically gated microscopy in scattering media.

High-resolution imaging in turbid media has been limited by the intrinsic compromise between the gating efficiency (removal of multiply-scattered light background) and signal strength in the existing optical gating techniques. This leads to shallow depths due to the weak ballistic signal, and/or degraded resolution due to the strong multiply-scattering background--the well-known trade-off between resolution and imaging depth in scattering samples. In this work, we employ a nonlinear optics based optical parametric amplifier (OPA) to address this challenge. We demonstrate that both the imaging depth and the spatial resolution in turbid media can be enhanced simultaneously by the OPA, which provides a high level of signal gain as well as an inherent nonlinear optical gate. This technology shifts the nonlinear interaction to an optical crystal placed in the detection arm (image plane), rather than in the sample, which can be used to exploit the benefits given by the high-order parametric process and the use of an intense laser field. The coherent process makes the OPA potentially useful as a general-purpose optical amplifier applicable to a wide range of optical imaging techniques.

Label-free nonlinear optical signatures of extracellular vesicles in liquid and tissue biopsies of human breast cancer.

Extracellular vesicles (EVs) have been implicated in metastasis and proposed as cancer biomarkers. However, heterogeneity and small size makes assessments of EVs challenging. Often, EVs are isolated from biofluids, losing spatial and temporal context and thus lacking the ability to access EVs in situ in their native microenvironment. This work examines the capabilities of label-free nonlinear optical microscopy to extract biochemical optical metrics of EVs in ex vivo tissue and EVs isolated from biofluids in cases of human breast cancer, comparing these metrics within and between EV sources. Before surgery, fresh urine and blood serum samples were obtained from human participants scheduled for breast tumor surgery (24 malignant, 6 benign) or healthy participants scheduled for breast reduction surgery (4 control). EVs were directly imaged both in intact ex vivo tissue that was removed during surgery and in samples isolated from biofluids by differential ultracentrifugation. Isolated EVs and freshly excised ex vivo breast tissue samples were imaged with custom nonlinear optical microscopes to extract single-EV optical metabolic signatures of NAD(P)H and FAD autofluorescence. Optical metrics were significantly altered in cases of malignant breast cancer in biofluid-derived EVs and intact tissue EVs compared to control samples. Specifically, urinary isolated EVs showed elevated NAD(P)H fluorescence lifetime in cases of malignant cancer, serum-derived isolated EVs showed decreased optical redox ratio in stage II cancer, but not earlier stages, and ex vivo breast tissue showed an elevated number of EVs in cases of malignant cancer. Results further indicated significant differences in the measured optical metabolic signature based on EV source (urine, serum and tissue) within individuals.

Probing delivery of a lipid nanoparticle encapsulated self-amplifying mRNA vaccine using coherent Raman microscopy and multiphoton imaging.

The COVID-19 pandemic triggered the resurgence of synthetic RNA vaccine platforms allowing rapid, scalable, low-cost manufacturing, and safe administration of therapeutic vaccines. Self-amplifying mRNA (SAM), which self-replicates upon delivery into the cellular cytoplasm, leads to a strong and sustained immune response. Such mRNAs are encapsulated within lipid nanoparticles (LNPs) that act as a vehicle for delivery to the cell cytoplasm. A better understanding of LNP-mediated SAM uptake and release mechanisms in different types of cells is critical for designing effective vaccines. Here, we investigated the cellular uptake of a SAM-LNP formulation and subsequent intracellular expression of SAM in baby hamster kidney (BHK-21) cells using hyperspectral coherent anti-Stokes Raman scattering (HS-CARS) microscopy and multiphoton-excited fluorescence lifetime imaging microscopy (FLIM). Cell classification pipelines based on HS-CARS and FLIM features were developed to obtain insights on spectral and metabolic changes associated with SAM-LNPs uptake. We observed elevated lipid intensities with the HS-CARS modality in cells treated with LNPs versus PBS-treated cells, and simultaneous fluorescence images revealed SAM expression inside BHK-21 cell nuclei and cytoplasm within 5 h of treatment. In a separate experiment, we observed a strong correlation between the SAM expression and mean fluorescence lifetime of the bound NAD(P)H population. This work demonstrates the ability and significance of multimodal optical imaging techniques to assess the cellular uptake of SAM-LNPs and the subsequent changes occurring in the cellular microenvironment following the vaccine expression.

Three-dimensional optical coherence tomography for optical biopsy of lymph nodes and assessment of metastatic disease.

BACKGROUND: Numerous techniques have been developed for localizing lymph nodes before surgical resection and for their histological assessment. Nondestructive high-resolution transcapsule optical imaging of lymph nodes offers the potential for in situ assessment of metastatic involvement, potentially during surgical procedures. METHODS: Three-dimensional optical coherence tomography (3-D OCT) was used for imaging and assessing resected popliteal lymph nodes from a preclinical rat metastatic tumor model over a 9-day time-course study after tumor induction. The spectral-domain OCT system utilized a center wavelength of 800 nm, provided axial and transverse resolutions of 3 and 12 µm, respectively, and performed imaging at 10,000 axial scans per second. RESULTS: OCT is capable of providing high-resolution label-free images of intact lymph node microstructure based on intrinsic optical scattering properties with penetration depths of ~1-2 mm. The results demonstrate that OCT is capable of differentiating normal, reactive, and metastatic lymph nodes based on microstructural changes. The optical scattering and structural changes revealed by OCT from day 3 to day 9 after the injection of tumor cells into the lymphatic system correlate with inflammatory and immunological changes observed in the capsule, precortical regions, follicles, and germination centers found during histopathology. CONCLUSIONS: We report for the first time a longitudinal study of 3-D transcapsule OCT imaging of intact lymph nodes demonstrating microstructural changes during metastatic infiltration. These results demonstrate the potential of OCT as a technique for intraoperative, real-time in situ 3-D optical biopsy of lymph nodes for the intraoperative staging of cancer.

In vivo magnetomotive optical molecular imaging using targeted magnetic nanoprobes.

Dynamic magnetomotion of magnetic nanoparticles (MNPs) detected with magnetomotive optical coherence tomography (MM-OCT) represents a new methodology for contrast enhancement and therapeutic interventions in molecular imaging. In this study, we demonstrate in vivo imaging of dynamic functionalized iron oxide MNPs using MM-OCT in a preclinical mammary tumor model. Using targeted MNPs, in vivo MM-OCT images exhibit strong magnetomotive signals in mammary tumor, and no significant signals were measured from tumors of rats injected with nontargeted MNPs or saline. The results of in vivo MM-OCT are validated by MRI, ex vivo MM-OCT, Prussian blue staining of histological sections, and immunohistochemical analysis of excised tumors and internal organs. The MNPs are antibody functionalized to target the human epidermal growth factor receptor 2 (HER2 neu) protein. Fc-directed conjugation of the antibody to the MNPs aids in reducing uptake by macrophages in the reticulo-endothelial system, thereby increasing the circulation time in the blood. These engineered magnetic nanoprobes have multifunctional capabilities enabling them to be used as dynamic contrast agents in MM-OCT and MRI.

Deep convolutional neural networks for detection of abnormalities in chest X-rays trained on the very large dataset.

One of the main challenges in the current pandemic is the detection of coronavirus. Conventional techniques (PT-PCR) have their limitations such as long response time and limited accessibility. On the other hand, X-ray machines are widely available and they are already digitized in the health systems. Thus, their usage is faster and more available. Therefore, in this research, we evaluate how well deep CNNs do when it comes to classifying normal versus pathological chest X-rays. Compared to the previous research, we trained our network on the largest number of images, 103,468 in total, including 5 classes such as COPD signs, COVID, normal, others and Pneumonia. We achieved COVID accuracy of 97% and overall accuracy of 81%. Additionally, we achieved classification accuracy of 84% for categorization into normal (78%) and abnormal (88%).