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Airborne microplastics (MPs) are important pollutants that have been present in the environment for many years and are characterized by their universality, persistence, and potential toxicity. This study investigated the effects of terrestrial and marine transport of MPs in the atmosphere of a coastal city and compared the difference between daytime and nighttime. Laser direct infrared imaging (LDIR) and polarized light microscopy were used to characterize the physical and chemical properties of MPs, including number concentration, chemical types, shape, and size. Backward trajectories were used to distinguish the air masses from marine and terrestrial transport. Twenty chemical types were detected by LDIR, with rubber (16.7%) and phenol-formaldehyde resin (PFR; 14.8%) being major components. Three main morphological types of MPs were identified, and fragments (78.1%) are the dominant type. MPs in the atmosphere were concentrated in the small particle size segment (20-50 µm). The concentration of MPs in the air mass from marine transport was 14.7 items/m3 - lower than that from terrestrial transport (32.0 items/m3). The number concentration of airborne MPs was negatively correlated with relative humidity. MPs from terrestrial transport were mainly rubber (20.2%), while those from marine transport were mainly PFR (18%). MPs in the marine transport air mass were more aged and had a lower number concentration than those in the terrestrial transport air mass. The number concentration of airborne MPs is higher during the day than at night. These findings could contribute to the development of targeted control measures and methods to reduce MP pollution.

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High-quality imaging of the retina is crucial to the diagnosis and monitoring of disease, as well as for evaluating the success of therapeutics in human patients and in preclinical animal models. Here, we describe the basic principles and methods for in vivo retinal imaging in rodents, including fundus imaging, fluorescein angiography, optical coherence tomography, fundus autofluorescence, and infrared imaging. After providing a concise overview of each method and detailing the retinal diseases and conditions that can be visualized through them, we will proceed to discuss the advantages and disadvantages of each approach. These protocols will facilitate the acquisition of optimal images for subsequent quantification and analysis. Additionally, a brief explanation will be given regarding the potential results and the clinical significance of the detected abnormalities.

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A central paradigm of moiré materials relies on the formation of superlattices that yield enlarged effective crystal unit cells. While a critical consequence of this phenomenon is the celebrated flat electronic bands that foster strong interaction effects, the presence of superlattices has further implications. Here we explore the advantages of moiré superlattices in twisted bilayer graphene (TBG) aligned with hexagonal boron nitride (hBN) for passively enhancing optical conductivity in the low-energy regime. To probe the local optical response of TBG/hBN double-moiré lattices, we use infrared (IR) nano-imaging in conjunction with nanocurrent imaging to examine local optical conductivity over a wide range of TBG twist angles. We show that interband transitions associated with the multiple moiré flat and dispersive bands produce tunable transparent IR responses even at finite carrier densities, which is in stark contrast to the previously limited metallic near transparency observed only in undoped pristine graphene.

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In this study, we explored the application of Short-Wave Infrared (SWIR) hyperspectral imaging combined with Competitive Adaptive Reweighted Sampling (CARS) and advanced regression models for the non-destructive assessment of protein content in dried laver. Utilizing a spectral range of 900-1700 nm, we aimed to refine the quality control process by selecting informative wavelengths through CARS and applying various preprocessing techniques (standard normal variate [SNV], Savitzky-Golay filtering [SG], Orthogonal Signal Correction [OSC], and StandardScaler [SS]) to enhance the model's accuracy. The SNV-OSC-StandardScaler- Support vector regression (SVR) model trained on CARS-selected wavelengths significantly outperformed the other configurations, achieving a prediction determination coefficient (Rp2) of 0.9673, root mean square error of prediction of 0.4043, and residual predictive deviation of 5.533. These results highlight SWIR hyperspectral imaging's potential as a rapid and precise tool for assessing dried laver quality, aiding food industry quality control and dried laver market growth.

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Microplastics (MPs) are a global concern as an emerging pollutant, and the investigation on MPs in Antarctic aids in informing their global pollution assessments. Therefore, there are urgent scientific concerns regarding the environmental behavior, origins, influencing factors, and potential hazards of MPs in Antarctica. This study presents the characteristics of MPs from one ornithogenic sediment profile (coded CC) and two ornithogenic soil profiles (coded MR1 and MR2) from ice-free areas on Ross Island, Antarctica. We explored the potential sources of MPs and the main influencing factors for deposition based on their distribution with depth in the profiles. Through laser-infrared imaging spectroscopy (LDIR), a total of 30 polymer types were identified in all samples, with polyethylene terephthalate (PET) and polyvinyl chloride (PVC) as the dominant types, accounting for more than 70% of the total. The abundance of MPs in the CC sediment profile ranged from 2.83 to 394.18 items/g, while in MR1 and MR2 soil profiles, the abundance ranged from 2.25 to 1690.11 and 8.24 to 168.27 items/g, respectively. The size of MPs was mainly concentrated in the range of 20-50 µm, and possible downward movement of certain polymer types was revealed. From the perspective of temporal variation, we suggest that MPs were heavily influenced by local human activities including scientific research, fishing, and tourism, balanced by protective regulations, while no solid evidence was obtained to support strong influence from biological transport through penguins. This research enhances our understanding on the environmental behavior of MPs in the terrestrial systems of remote polar regions.

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Autodynamic cancer therapy possesses tremendous potential for enhancing therapeutic efficacy by initiating the treatment process autonomously within targeted cells. However, challenges related to biocompatibility and targeted delivery have hindered its clinical translation owing to the induction of adverse effects and cytotoxicity in healthy cells. In this study, a novel approach for auto-initiated dynamic therapy by conjugating zwitterionic near-infrared fluorophores to a cell-penetrating peptide is proposed. This enables efficient cellular uptake and specific targeting of therapy to desired cells while avoiding off-target uptake. The zwitterionic bioconjugate causes cancer-specific toxicity following its internalization into the targeted cells, triggered by specific intracellular conditions in lysosomes. This innovative approach enables selective targeting of lysosomes in malignant cells while minimizing cytotoxic effects on normal cells. By targeting lysosomes, the method overcomes inherent risks and side effects associated with conventional cancer treatments, offering a selective and effective approach to cancer therapy.

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BACKGROUND: The quantitative interpretation of the radiometric information extracted from infrared (IR) images in individuals with and without type 2 diabetes mellitus (DM2) is an open problem yet to be solved. This is of particular value given that DM2 is a worldwide health problem and onset for evolution toward diabetic foot disease (DFD). Since DM2 causes changes at the vascular and neurological levels, the metabolic heat distribution on the outer skin is modified as a consequence of such alterations. Of particular interest in this contribution are those alterations displayed over the skin's heat patterns at the lower limbs. At the core of such alterations is the deterioration of the vascular and neurological networks responsible for procuring systemic thermoregulation. It is within this context that IR imaging is introduced as a likely aiding tool to assist with the clinical diagnosis of DM2 at stages early enough to prevent the evolution of the DFD. METHODS: IR images of lower limbs are acquired from a cohort of individuals clinically diagnosed with and without DM2. Additional inclusion criteria for patients are to be free from any visible wound or tissue-related trauma (e.g., injuries, edema, and so forth), and also free from non-metabolic comorbidities. All images and data are equally processed and analyzed using indices that evaluate the spatial and temporal evolution of temperature distribution in lower limbs. We studied the temporal response of individuals' legs after inducing an external stimulus. For this purpose, we combine the information of the asymmetry and thermal response index (ATR) and the thermal response index (TRI), computed using images at different times, improving the results previously obtained individually with ATR and TRI. RESULTS: A novel representation of the information extracted from IR images of the lower limbs in individuals with and without DM2 is presented. This representation was built using the ATR and TRI indices for the anterior and posterior views (PVs), individually and combining the information from both views. In all cases, the information of each index and each view presents linearity properties that allow said information to be interpreted quantitatively in a well-defined and limited space. This representation, built in a polar coordinate space, allows obtaining sensitivity values of 86%, 97%, and 97%, and specificity values of 83%, 72%, and 78% for the anterior view (AV), the PV, and the combined views, respectively. Additionally, it was observed that the angular variable that defines this new representation space allows to significantly (p < 0.01) differentiate the groups, while correlating with clinical variables of interest, such as glucose and glycated hemoglobin. CONCLUSION: The linearity properties that exist between the ATR and TRI indices allow a quantitative interpretation of the information extracted from IR images of the lower extremities of individuals with and without DM2, and allow the construction of a representation space that eliminates possible ambiguities in the interpretation, while simplifying it, making it accessible for clinical use.

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Significance: Single-chip imaging devices featuring vertically stacked photodiodes and pixelated spectral filters are advancing multi-dye imaging methods for cancer surgeries, though this innovation comes with a compromise in spatial resolution. To mitigate this drawback, we developed a deep convolutional neural network (CNN) aimed at demosaicing the color and near-infrared (NIR) channels, with its performance validated on both pre-clinical and clinical datasets. Aim: We introduce an optimized deep CNN designed for demosaicing both color and NIR images obtained using a hexachromatic imaging sensor. Approach: A residual CNN was fine-tuned and trained on a dataset of color images and subsequently assessed on a series of dual-channel, color, and NIR images to demonstrate its enhanced performance compared with traditional bilinear interpolation. Results: Our optimized CNN for demosaicing color and NIR images achieves a reduction in the mean square error by 37% for color and 40% for NIR, respectively, and enhances the structural dissimilarity index by 37% across both imaging modalities in pre-clinical data. In clinical datasets, the network improves the mean square error by 35% in color images and 42% in NIR images while enhancing the structural dissimilarity index by 39% in both imaging modalities. Conclusions: We showcase enhancements in image resolution for both color and NIR modalities through the use of an optimized CNN tailored for a hexachromatic image sensor. With the ongoing advancements in graphics card computational power, our approach delivers significant improvements in resolution that are feasible for real-time execution in surgical environments.

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BACKGROUND: Gastric cancer is a common malignant tumor of the digestive system worldwide, and its early diagnosis is crucial to improve the survival rate of patients. Indocyanine green fluorescence imaging (ICG-FI), as a new imaging technology, has shown potential application prospects in oncology surgery. The meta-analysis to study the application value of ICG-FI in the diagnosis of gastric cancer sentinel lymph node biopsy is helpful to comprehensively evaluate the clinical effect of this technology and provide more reliable guidance for clinical practice. AIM: To assess the diagnostic efficacy of optical imaging in conjunction with indocyanine green (ICG)-guided sentinel lymph node (SLN) biopsy for gastric cancer. METHODS: Electronic databases such as PubMed, Embase, Medline, Web of Science, and the Cochrane Library were searched for prospective diagnostic tests of optical imaging combined with ICG-guided SLN biopsy. Stata 12.0 software was used for analysis by combining the "bivariable mixed effect model" with the "midas" command. The true positive value, false positive value, false negative value, true negative value, and other information from the included literature were extracted. A literature quality assessment map was drawn to describe the overall quality of the included literature. A forest plot was used for heterogeneity analysis, and P < 0.01 was considered to indicate statistical significance. A funnel plot was used to assess publication bias, and P < 0.1 was considered to indicate statistical significance. The summary receiver operating characteristic (SROC) curve was used to calculate the area under the curve (AUC) to determine the diagnostic accuracy. If there was interstudy heterogeneity (I 2 > 50%), meta-regression analysis and subgroup analysis were performed. RESULTS: Optical imaging involves two methods: Near-infrared (NIR) imaging and fluorescence imaging. A combination of optical imaging and ICG-guided SLN biopsy was useful for diagnosis. The positive likelihood ratio was 30.39 (95%CI: 0.92-1.00), the sensitivity was 0.95 (95%CI: 0.82-0.99), and the specificity was 1.00 (95%CI: 0.92-1.00). The negative likelihood ratio was 0.05 (95%CI: 0.01-0.20), the diagnostic odds ratio was 225.54 (95%CI: 88.81-572.77), and the SROC AUC was 1.00 (95%CI: The crucial values were sensitivity = 0.95 (95%CI: 0.82-0.99) and specificity = 1.00 (95%CI: 0.92-1.00). The Deeks method revealed that the "diagnostic odds ratio" funnel plot of SLN biopsy for gastric cancer was significantly asymmetrical (P = 0.01), suggesting significant publication bias. Further meta-subgroup analysis revealed that, compared with fluorescence imaging, NIR imaging had greater sensitivity (0.98 vs 0.73). Compared with optical imaging immediately after ICG injection, optical imaging after 20 minutes obtained greater sensitivity (0.98 vs 0.70). Compared with that of patients with an average SLN detection number < 4, the sensitivity of patients with a SLN detection number ≥ 4 was greater (0.96 vs 0.68). Compared with hematoxylin-eosin (HE) staining, immunohistochemical (+ HE) staining showed greater sensitivity (0.99 vs 0.84). Compared with subserous injection of ICG, submucosal injection achieved greater sensitivity (0.98 vs 0.40). Compared with 5 g/L ICG, 0.5 and 0.05 g/L ICG had greater sensitivity (0.98 vs 0.83), and cT1 stage had greater sensitivity (0.96 vs 0.72) than cT2 to cT3 clinical stage. Compared with that of patients ≤ 26, the sensitivity of patients > 26 was greater (0.96 vs 0.65). Compared with the literature published before 2010, the sensitivity of the literature published after 2010 was greater (0.97 vs 0.81), and the differences were statistically significant (all P < 0.05). CONCLUSION: For the diagnosis of stomach cancer, optical imaging in conjunction with ICG-guided SLN biopsy is a therapeutically viable approach, especially for early gastric cancer. The concentration of ICG used in the SLN biopsy of gastric cancer may be too high. Moreover, NIR imaging is better than fluorescence imaging and may obtain higher sensitivity.

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Cyanine-based near-infrared (NIR) fluorescent probes have played vital roles in biological application due to their low interference from background fluorescence, deep tissue penetration, high sensitivity, and minimal photodamage to biological samples. They are widely utilized in molecular recognition, medical diagnosis, biomolecular detection, and biological imaging. Herein, we provide a review of recent advancements in cyanine-based NIR fluorescent probes for the detection of pH, cells, tumor as well as their application in photothermal therapy (PTT) and photodynamic therapy (PDT).

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Hydrogen sulfide (H2S) can act as a gaseous signaling mediator closely associated with inflammation development. In this work, we designed a fluorescence turn-on near-infrared (NIR) fluorescent probe CIT-H2S based on Intermolecular Charge Transfer (ICT) for the detection of H2S in living inflammatory cells and zebrafish. On this basis, a dicyanoisophorone fluorophore was chosen as the fluorescence signal reporting group of CIT-H2S, and an azide group was constructed as the recognition group of H2S. CIT-H2S is characterized by high selectivity and sensitivity for H2S over other interference species. The fluorescence intensity at 661 nm showed good linearity in the range of H2S concentration from 0 to 10 µM, with an excellent limit of detection (LOD) as low as 81.52 nM. Impressively, CIT-H2S has been visualized for detecting H2S in drug-induced inflammatory cell and zebrafish models, thus indicating that CIT-H2S is a robust tool with the ability to study the occurrence and development of hydrogen sulfide and inflammation.

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PURPOSE: Retinal displacement following rhegmatogenous retinal detachment (RRD) has been associated with inferior functional outcomes. Recent evidence using an overlay technique suggests that fundus-autofluorescence underestimates post-RRD repair retinal displacement. This study aims to validate the overlay technique in normal eyes and to determine its sensitivity and specificity at detecting retinal displacement. METHODS: We conducted a retrospective case series involving 66 normal eyes, each with at least two separate infrared (IR) images at different time points. Overlay of the two images was based on manual marking of choroidal and optic nerve head (ONH) landmarks. For each set of two IR images, computer code for homography generated two outputs, flipping view video and an overlay picture. First, validation of choroidal/ONH alignment was performed using the flipping view video to ensure accurate manual markings. Then, two different masked graders (AB + IM) evaluated the overlays for presence of retinal displacement. 16 control eyes following RRD repair with detected retinal displacement on FAF imaging assessed sensitivity and specificity of the technique. RESULTS: 94% of overlays were found to be well aligned (62/66). 11 cases exhibited errors on flipping view analysis (choroidal/ONH misalignment). Those 11 cases had a significantly higher rate of retinal displacement (false positives) compared to cases without errors (8/11,72% Vs 54/55,98%,P = 0.001). Sensitivity and specificity of the overlay technique for detecting retinal displacement considering only adequate flipping view cases (n = 55) were calculated as 100% and 98%, respectively. CONCLUSIONS: IR overlay emerges as a reliable and valid method for detecting retinal displacement, exhibiting excellent sensitivity and specificity.

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Although human core body temperature is known to decrease with age, the age dependency of facial temperature and its potential to indicate aging rate or aging-related diseases remains uncertain. Here, we collected thermal facial images of 2,811 Han Chinese individuals 20-90 years old, developed the ThermoFace method to automatically process and analyze images, and then generated thermal age and disease prediction models. The ThermoFace deep learning model for thermal facial age has a mean absolute deviation of about 5 years in cross-validation and 5.18 years in an independent cohort. The difference between predicted and chronological age is highly associated with metabolic parameters, sleep time, and gene expression pathways like DNA repair, lipolysis, and ATPase in the blood transcriptome, and it is modifiable by exercise. Consistently, ThermoFace disease predictors forecast metabolic diseases like fatty liver with high accuracy (AUC > 0.80), with predicted disease probability correlated with metabolic parameters.

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Infrared (IR) spectroscopic imaging is of potentially wide use in medical imaging applications due to its ability to capture both chemical and spatial information. This complexity of the data both necessitates using machine intelligence as well as presents an opportunity to harness a high-dimensionality data set that offers far more information than today's manually-interpreted images. While convolutional neural networks (CNNs), including the well-known U-Net model, have demonstrated impressive performance in image segmentation, the inherent locality of convolution limits the effectiveness of these models for encoding IR data, resulting in suboptimal performance. In this work, we propose an INfrared Spectroscopic imaging-based TRAnsformers for medical image Segmentation (INSTRAS). This novel model leverages the strength of the transformer encoders to segment IR breast images effectively. Incorporating skip-connection and transformer encoders, INSTRAS overcomes the issue of pure convolution models, such as the difficulty of capturing long-range dependencies. To evaluate the performance of our model and existing convolutional models, we conducted training on various encoder-decoder models using a breast dataset of IR images. INSTRAS, utilizing 9 spectral bands for segmentation, achieved a remarkable AUC score of 0.9788, underscoring its superior capabilities compared to purely convolutional models. These experimental results attest to INSTRAS's advanced and improved segmentation abilities for IR imaging.

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PURPOSE: The incomplete resection of non-muscle invasive bladder cancer (NMIBC) augments the risk of disease recurrence. Imaging-guided surgery by molecular probes represents a pivotal strategy for mitigating postoperative recurrence. Traditional optical molecular probes, primarily composed of antibodies/peptides targeting tumour cells and fluorescent groups, are challenged by the high heterogeneity of NMIBC cells, leading to inadequate probe sensitivity. We have developed a collagen-adhesive probe (CA-P) to target the collagen within the tumour microenvironment, aiming to address the issue of insufficient imaging sensitivity. METHODS: The distribution characteristics of collagen in animal bladder cancer models and human bladder cancer tissues were explored. The synthesis and properties of CA-P were validated. In animal models, the imaging performance of CA-P was tested and compared with our previously reported near-infrared probe PLSWT7-DMI. The clinical translational potential of CA-P was assessed using human ex vivo bladder tissues. RESULTS: The distribution of collagen on the surface of tumour cells is distinct from its expression in normal urothelium. In vitro studies have demonstrated the ability of the CA-P to undergo a "sol-gel" transition upon interaction with collagen. In animal models and human ex vivo bladder specimens, CA-P exhibits superior imaging performance compared to PLSWT7-DMI. The sensitivity of this probe is 94.1%, with a specificity of 81%. CONCLUSION: CA-P demonstrates the capability to overcome tumour cell heterogeneity and enhance imaging sensitivity, exhibiting favorable imaging outcomes in preclinical models. These findings provide a theoretical basis for the application of CA-P in intraoperative navigation for NMIBC.

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The integration of visual algorithms with infrared imaging technology has become an effective tool for industrial gas leak detection. However, existing research has mostly focused on simple scenarios where a gas plume is clearly visible, with limited studies on detecting gas in complex scenes where target contours are blurred and contrast is low. This paper uses a cooled mid-wave infrared (MWIR) system to provide high sensitivity and fast response imaging and proposes the MWIRGas-YOLO network for detecting gas leaks in mid-wave infrared imaging. This network effectively detects low-contrast gas leakage and segments the gas plume within the scene. In MWIRGas-YOLO, it utilizes the global attention mechanism (GAM) to fully focus on gas plume targets during feature fusion, adds a small target detection layer to enhance information on small-sized targets, and employs transfer learning of similar features from visible light smoke to provide the model with prior knowledge of infrared gas features. Using a cooled mid-wave infrared imager to collect gas leak images, the experimental results show that the proposed algorithm significantly improves the performance over the original model. The segment mean average precision reached 96.1% (mAP50) and 47.6% (mAP50:95), respectively, outperforming the other mainstream algorithms. This can provide an effective reference for research on infrared imaging for gas leak detection.

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Microplastics are widely distributed in ecosystems and are increasingly found in food. This poses a potential threat to human health. However, current detections of microplastic in food primarily focused on the simple matrices, such as water, milk, and beverages, with relatively few methods available for complex matrices. Due to the strong matrix interference, non-destructive detection of microplastics in food has always been challenging. Thus, in this study, infrared spectral imaging approach was employed in tandem with chemometrics to perform nondestructive and in-situ characterization of microplastics in twelve diverse Chinese diets including meat and seafood stuffs. Results demonstrate that the proposed method can efficiently characterize common microplastics, such as polypropylene (PP), polyethylene terephthalate (PET), and polyethylene (PE), etc., in various complex matrices. The IR spectral imaging was subsequently applied to the detection of microplastics in seafood samples collected from 24 provinces across China. Results revealed the widespread presence of microplastics in seafood diets with significant regional variations. Overall, this study offers an innovative and applicable means for detecting microplastics in complex foods and provides a reference for the rapid detection of microplastics in various materials.

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Introduction: Infrared thermography (IT) is a non-invasive real-time imaging technique with potential application in different areas of neurosurgery. Despite technological advances in the field, intraoperative IT (IIT) has been an underestimated tool with scarce reports on its usefulness during intracranial tumor resection. We aimed to evaluate the usefulness of high-resolution IIT with static and dynamic thermographic maps for transdural lesion localization, and diagnosis, to assess the extent of resection, and the occurrence of perioperative acute ischemia. Methods: In a prospective study, 15 patients affected by intracranial tumors (six gliomas, four meningiomas, and five brain metastases) were examined with a high-resolution thermographic camera after craniotomy, after dural opening, and at the end of tumor resection. Results: Tumors were transdurally located with 93.3% sensitivity and 100% specificity (p < 0.00001), as well as cortical arteries and veins. Gliomas were consistently hypothermic, while metastases and meningiomas exhibited highly variable thermographic maps on static (p = 0.055) and dynamic (p = 0.015) imaging. Residual tumors revealed non-specific static but characteristic dynamic thermographic maps. Ischemic injuries were significantly hypothermic (p < 0.001). Conclusions: High-resolution IIT is a non-invasive alternative intraoperative imaging method for lesion localization, diagnosis, assessing the extent of tumor resection, and identifying acute ischemia changes with static and dynamic thermographic maps.

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Objectives: Yasunari nodules are choroidal lesions observed in patients diagnosed with neurofibromatosis type 1 (NF-1) and characterized by relatively irregular dome-shaped, plaque-like, or patchy boundaries. The present study examines the multimodal imaging characteristics of Yasunari nodules and their value in the diagnosis of NF-1. Materials and Methods: Medical records including optical coherence tomography (OCT), enhanced depth imaging OCT, infrared reflectance (IR) imaging, OCT angiography, and color fundus images of NF-1 patients who were examined at the Department of Ophthalmology in Dokuz Eylül University Faculty of Medicine between January 2022 and December 2023 were retrospectively reviewed for the presence of Yasunari nodules. Results: A total of 54 eyes of 27 patients were included in the study. At least one choroidal nodule was detected on IR imaging in 52 eyes (96.3%). In 31 (72.1%) of the 43 eyes (79.6%) with available high-quality OCT angiography images, choroidal nodules were observed as areas showing a flow deficit in the choriocapillaris layer. Of the total 54 eyes included, Lisch nodules without choroidal nodules were observed in 2 eyes (3.7%). In 16 eyes (29.6%), Lisch nodules were not detected despite the presence of choroidal nodules. Both Lisch nodules and choroidal nodules were detected in the other 36 eyes (66.7%). Conclusion: Yasunari nodules are frequently observed in NF-1 cases and can be easily detected with multimodal imaging techniques, especially IR imaging. The ability to visualize choroidal nodules before the appearance of Lisch nodules demonstrates the importance of Yasunari nodules in the diagnosis of NF-1.

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Purpose: To report a case of bilateral acute macular neuroretinopathy (AMN) associated with COVID-19 infection presenting with central scotoma. Observation: A 26-year-old female presented with a chief complaint of bilateral central scotomas for the last seven days. She had a history of fever over the past ten days, and RT-PCR test for COVID-19 was positive on the second day of fever. She had been vaccinated against COVID-19 eight months prior. Her best corrected visual acuity was 6/6 in both eyes on the Snellen chart. Dilated fundus evaluation revealed subtle bilateral perifoveal grey macular lesions. Optical coherence tomography (OCT) demonstrated focal hyperreflectivity at the level of the outer nuclear and plexiform layer consistent with bilateral AMN. Near-infrared reflectance (NIR) and red-free (RF) imaging showed large, confluent hyporeflective lesions in the right eye and discrete petaloid lesions with apices pointing toward the fovea in the left eye. OCT angiography (OCTA) revealed decreased flow signal at the level of the deep capillary plexus (DCP) and choriocapillaris (CC) in both eyes. Automated visual field testing (Humprey Field Analyzer (HFA) 24-2) revealed bilateral central scotoma with depression of adjacent points. After two weeks, the patient had depressed visual fields on HFA 10-2. At two months of final follow-up, OCT macula, NIR and RF images revealed resolving AMN lesions in both eyes. OCTA showed an increase in perfusion at the level of the DCP. There was a decrease in scotoma density on HFA 10-2, suggestive of resolving AMN. Conclusion and importance: AMN with central scotoma as presenting feature of COVID-19 is rare. Fundus findings may be very subtle in AMN, but NIR and RF imaging delineate the lesions well. OCT, NIR imaging, OCTA and HFA 10-2 can be used to assess the clinical course of AMN.