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Pancreaticobiliary carcinomas is a highly malignant gastrointestinal tumor. Most pancreaticobiliary cancers arise from epithelial proliferation within the pancreaticobiliary ducts, referred to as pancreatic intraepithelial neoplasias (PanINs). Some PanINs are benign metaplasia, while others progress to invasive duct adenocarcinoma (IDAC). However, there is no standard program to diagnose the progression from PanINs to IDAC. In this study, we present a tri-modality imaging system, which integrates ultrasound (US), optical coherence tomography (OCT), and near-infrared fluorescence (NIRF) for pancreaticobiliary duct imaging. This system can obtain OCT, US, and NIRF images in real-time with a frame rate of 30 frames per second. For the endoscopy probe with an outer diameter of 0.9 mm, the US transducer and fiber ball lens were placed back to back. In vivo experiments were performed on the rectums of Sprague–Dawley rats to demonstrate the imaging performance of US, OCT, and fluorescence angiography. An ex vivo experiment on a human pancreatic duct was performed for a more accurate assessment of the pancreaticobiliary duct. The tomography images of rat rectums and human pancreatic ducts were correlated with hematoxylin and eosin (H&E) histology to check the measurement accuracy. The integrated tri-modality system has great clinical potential in mechanism studies, early diagnosis, and prognosis evaluation of malignant pancreaticobiliary carcinomas. [ABSTRACT FROM AUTHOR]

Purpose: To demonstrate the value of the laser-scanning optical-resolution (LSOR)-photoacoustic (PA) microscopy (PAM) system and the conventional multimodal imaging techniques in the evaluation of laser-induced retinal injury and choroidal neovascularization (CNV) in rats. Methods: Different degrees of retinal injury were induced using laser photocoagulation. We compared the LSOR-PAM system with conventional imaging techniques in evaluating retinal injury with or without CNV. Six additional rats, treated with an anti-VEGF antibody or immunoglobulin G immediately after photocoagulation, were imaged 7 and 14 days after injection, and CNV lesion areas were compared. Results: In the retinal injury model, fundus autofluorescence showed well-defined hyperreflection, while the lesion displayed abundant PA signals demonstrating nonuniform melanin distribution in retinal pigment epithelium (RPE). RPE was detected with higher contrast in the PAM B-scan image than optical coherence tomography (OCT). Additionally, the CNV lesion was present with multiple PA signal intensities which distinctly characterized the location and area of CNV as found in fundus fluorescein angiography. Furthermore, the decreased PA signals extending from the CNV lesion were similar to those of the vascular bud in ex vivo imaging, which was invisible in other in vivo images. When treated with anti-VEGF agents, statistically significant differences can be demonstrated by PAM similar to other modalities. Conclusions: LSOR-PAM can detect the melanin distribution of RPE in laser-induced retinal injury and CNV in rats. PAM imaging provides a potential new tool to evaluate the vitality and functionality of RPE in vivo as well as to monitor the development and treatment of CNV. [ABSTRACT FROM AUTHOR]

We report the virtual instrumentation of both time-domain (TD) and spectral-domain (SD) optical coherence tomography (OCT) systems. With a virtual partial coherence source from either a simulated or measured spectrum, the OCT signals of both A-scan and B-scan were demonstrated. The spectrometric detector's pixel number, dynamic range, noise, as well as spectral resolution can be simulated in the virtual spectral domain (SD-OCT). The virtual-OCT system provides an environment for parameter evaluation and algorithm optimization for experimental OCT instrumentation, and promotes the understanding of OCT imaging and signal post-processing processes. [ABSTRACT FROM AUTHOR]

Abstract: We propose a united theory that describes the two-center recording system by taking scattering noise into account. The temporal evolution of the signal-to-noise ratio in doubly doped photorefractive crystals is described based on jointly solving material equations and coupled-wave equations with the fourth-order Runge–Kutta method. Roles of microcosmic optical parameters of dopants on the signal-to-noise ratio are discussed in detail. The theoretical results can confirm and predict experimental results. [Copyright &y& Elsevier]

Abstract: The formation of the non-uniformity of the non-volatile volume grating in doubly doped LiNbO3 crystals is studied in detail. We find that the non-uniformity of the grating is mainly caused by strong ultraviolet light absorption, and the average saturation space-charge field is small and the diffraction efficiency is low as a result of the non-uniformity of the grating. In order to optimize the uniformity of the grating, we propose the recording scheme by using two sensitizing beams simultaneously from the two opposite sides of the crystals. Theoretical simulations and experimental verifications are performed. Results show that the well uniformed grating with high diffraction efficiency can be obtained by using this optimization scheme. [Copyright &y& Elsevier]

Diabetic retinopathy (DR) is one of the major causes of visual impairment in adults with diabetes. Optical coherence tomography angiography (OCTA) is nowadays widely used as the golden criterion for diagnosing DR. Recently, wide-field OCTA (WF-OCTA) provided more abundant information including that of the peripheral retinal degenerative changes and it can contribute in accurately diagnosing DR. The need for an automatic DR diagnostic system based on WF-OCTA pictures attracts more and more attention due to the large diabetic population and the prevalence of retinopathy cases. In this study, automatic diagnosis of DR using vision transformer was performed using WF-OCTA images (12 mm × 12 mm single-scan) centered on the fovea as the dataset. WF-OCTA images were automatically classified into four classes: No DR, mild nonproliferative diabetic retinopathy (NPDR), moderate to severe NPDR, and proliferative diabetic retinopathy (PDR). The proposed method for detecting DR on the test set achieves accuracy of 99.55%, sensitivity of 99.49%, and specificity of 99.57%. The accuracy of the method for DR staging reaches up to 99.20%, which has been proven to be higher than that attained by classical convolutional neural network models. Results show that the automatic diagnosis of DR based on vision transformer and WF-OCTA pictures is more effective for detecting and staging DR. [ABSTRACT FROM AUTHOR]

Objective. The high-precision segmentation of retinal vessels in fundus images is important for the early diagnosis of ophthalmic diseases. However, the extraction for microvessels is challenging due to their characteristics of low contrast and high structural complexity. Although some works have been developed to improve the segmentation ability in thin vessels, they have only been successful in recognizing small vessels with relatively high contrast. Approach. Therefore, we develop a deep learning (DL) framework with a multi-stage and dual-channel network model (MSDC_NET) to further improve the thin-vessel segmentation with low contrast. Specifically, an adaptive image enhancement strategy combining multiple preprocessing and the DL method is firstly proposed to elevate the contrast of thin vessels; then, a two-channel model with multi-scale perception is developed to implement whole- and thin-vessel segmentation; and finally, a series of post-processing operations are designed to extract more small vessels in the predicted maps from thin-vessel channels. Main results. Experiments on DRIVE, STARE and CHASE_DB1 demonstrate the superiorities of the proposed MSDC_NET in extracting more thin vessels in fundus images, and quantitative evaluations on several parameters based on the advanced ground truth further verify the advantages of our proposed DL model. Compared with the previous multi-branch method, the specificity and F1 score are improved by about 2.18%, 0.68%, 1.73% and 2.91%, 0.24%, 8.38% on the three datasets, respectively. Significance. This work may provide richer information to ophthalmologists for the diagnosis and treatment of vascular-related ophthalmic diseases. [ABSTRACT FROM AUTHOR]

Myopia is a significant cause of visual impairment which may lead to many complications. However, the understanding of the mechanisms of myopia is still limited. In this paper, in order to investigate the development and the treatment of myopia, we analyzed the biological structure parameters of mice eyes, obtained from optical coherence tomography (OCT), and the optical performance of mice eyes calculated using ZEMAX software (ZEMAX Development Corporation, Kirkland, WA, USA) in which the optical model was built on the segment-by-segment optically corrected OCT 3D-images. Time-serial evaluation of three groups of mice eyes (form-deprivation myopia mice eyes, normal mice eyes, and atropine-treated myopia mice eyes) was performed. In addition to the biological structure parameters, imaging performance with the development of root-mean-square wavefront aberration at six filed angles was compared and analyzed. Results show that the biological structure parameters of the eye are closely related to the development of myopia. The peripheral defocus of the retina has a significant impact on inducing myopia, which verifies the new theory of myopia development. The delaying effect of atropine solution on myopia development is shown to verify the therapeutic effect of the medicine. This study provides technical support for the investigation of the myopia mechanism. [ABSTRACT FROM AUTHOR]

Retinal disorders are a major cause of irreversible vision loss, which can be mitigated through accurate and early diagnosis. Conventionally, fundus images are used as the gold diagnosis standard in detecting retinal diseases. In recent years, more and more researchers have employed deep learning methods for diagnosing ophthalmic diseases using fundus photography datasets. Among the studies, most of them focus on diagnosing a single disease in fundus images, making it still challenging for the diagnosis of multiple diseases. In this paper, we propose a framework that combines ResNet and Transformer for multi-label classification of retinal disease. This model employs ResNet to extract image features, utilizes Transformer to capture global information, and enhances the relationships between categories through learnable label embedding. On the publicly available Ocular Disease Intelligent Recognition (ODIR-5 k) dataset, the proposed method achieves a mean average precision of 92.86%, an area under the curve (AUC) of 97.27%, and a recall of 90.62%, which outperforms other state-of-the-art approaches for the multi-label classification. The proposed method represents a significant advancement in the field of retinal disease diagnosis, offering a more accurate, efficient, and comprehensive model for the detection of multiple retinal conditions.Graphical Abstract: Retinal disorders are a major cause of irreversible vision loss, which can be mitigated through accurate and early diagnosis. Conventionally, fundus images are used as the gold diagnosis standard in detecting retinal diseases. In recent years, more and more researchers have employed deep learning methods for diagnosing ophthalmic diseases using fundus photography datasets. Among the studies, most of them focus on diagnosing a single disease in fundus images, making it still challenging for the diagnosis of multiple diseases. In this paper, we propose a framework that combines ResNet and Transformer for multi-label classification of retinal disease. This model employs ResNet to extract image features, utilizes Transformer to capture global information, and enhances the relationships between categories through learnable label embedding. On the publicly available Ocular Disease Intelligent Recognition (ODIR-5 k) dataset, the proposed method achieves a mean average precision of 92.86%, an area under the curve (AUC) of 97.27%, and a recall of 90.62%, which outperforms other state-of-the-art approaches for the multi-label classification. The proposed method represents a significant advancement in the field of retinal disease diagnosis, offering a more accurate, efficient, and comprehensive model for the detection of multiple retinal conditions. [ABSTRACT FROM AUTHOR]

The shape and structure of retinal layers are basic characteristics for the diagnosis of many ophthalmological diseases. Based on B-Scans of optical coherence tomography, most of retinal layer segmentation methods are composed of two-steps: classifying pixels and extracting retinal layers, in which the optimization of two independent steps decreases the accuracy. Although the methods based on deep learning are highly accurate, they require a large amount of labeled data. This paper proposes a single-step method based on transformer for retinal layer segmentation, which is trained by axial data (A-Scans), to obtain the boundary of each layer. The proposed method was evaluated on two public data sets. The first one contains eight retinal layer boundaries for diabetic macular edema, and the second one contains nine retinal layer boundaries for healthy controls and subjects with multiple sclerosis. Its absolute average distance errors are 0.99 pixels and 3.67 pixels, respectively, for the two sets, and its root mean square error is 1.29 pixels for the latter set. In addition, its accuracy is acceptable even if the training data is reduced to 0.3. The proposed method achieves state-of-the-art performance while maintaining the correct topology and requires less labeled data. [ABSTRACT FROM AUTHOR]

Age-related Macular Degeneration (AMD) and Diabetic Macular Edema (DME) are two common retinal diseases for elder people that may ultimately cause irreversible blindness. Timely and accurate diagnosis is essential for the treatment of these diseases. In recent years, computer-aided diagnosis (CAD) has been deeply investigated and effectively used for rapid and early diagnosis. In this paper, we proposed a method of CAD using vision transformer to analyze optical coherence tomography (OCT) images and to automatically discriminate AMD, DME, and normal eyes. A classification accuracy of 99.69% was achieved. After the model pruning, the recognition time reached 0.010 s and the classification accuracy did not drop. Compared with the Convolutional Neural Network (CNN) image classification models (VGG16, Resnet50, Densenet121, and EfficientNet), vision transformer after pruning exhibited better recognition ability. Results show that vision transformer is an improved alternative to diagnose retinal diseases more accurately. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the effect of powerless contact lens on improving the quality of optical coherence tomography imaging of rodent retina. Methods: A spectral-domain optical coherence tomography (SD-OCT) system was built for in vivo imaging of rodent retina. The calibrated depth resolution of the system was 3 |im in tissue. A commercial powerless contact lens for rat eye was tested in the experiments. For each rat eye, the retina was imaged in vivo sequentially first without wearing contact lens and then with wearing contact lens. The lateral resolution and signal-to-noise ratio of the OCT images with and without contact lens were compared to evaluate the improvement of image quality. Results: The fundus images generated from the measured 3D OCT datasets with contact lens showed sharper retinal blood vessels than those without contact lens. The contrast of the retinal blood vessels was also significantly enhanced in the OCT fundus images with contact lens. As high as 10 dB improvements in SNR was observed for OCT images with contact lens compared to the images of the same retinal area without contact lens. Conclusions: We have demonstrated that the use of powerless contact lens on rat eye can significantly improve OCT image quality of rodent retina, which is a benefit in addition to preventing cataract formation. We believe the improvement in image quality is the result of partial compensation of the optical aberrations of the rodent eye by the contact lens. [ABSTRACT FROM AUTHOR]

Abstract: A novel holographic display system is proposed in this paper. The system takes LC-R2500, a kind of reflective liquid crystal spatial light modulator, (LC-SLM) as the core display unit, which can meet the requirement of real-time reconstruction of three-dimensional (3D) objects from holograms in free space. The relationship between hologram recording and image reconstruction is discussed, and the parameters associated with the magnification of reconstructed image over original object are determined. Experimental results of holographic display using the system are also given in the end. [Copyright &y& Elsevier]

Tumor angiogenesis is a complex process that is unamenable to intravital whole‐process monitoring, especially on microscopic assessment of tumor microvessel and quantifying microvascular hemodynamics before and after the nanotherapeutics, which hinder the understanding of nanotheranostics outcomes in tumor treatment. Herein, a new photoacoustic (PA) imaging‐optical coherence tomography angiography (OCTA)‐laser speckle (LS) multimodal imaging strategy is first proposed, which is not only able to precisely macro guide the thermo‐chemotherapy of tumor by monitoring blood oxygen saturation (SaO2) and hemoglobin content (HbT), but also capable of long‐term microscopic investigating the microvessel morphology (microvascular density) and hemodynamics changes (relative blood flow) before and after the nanotherapeutics in vivo. Moreover, to realize the tumor thermo‐chemotherapy treatment based on this novel multimodal imaging strategy, a 2D 5‐fluorouracil silicon nanosheets (5‐Fu‐Si NSs) therapeutic agent is designed. Furthermore, 2D high‐resolution tumor microvascular images in different stage display that tendency of the thermo‐chemotherapy effect is closely associated with tumor angiogenesis. Taken together, the investigations establish the fundamental base in theory and technology for further tailoring the novel specific diagnosis and treatment strategy in tumor. More importantly, this technique will be beneficial to evaluate the tumor microvascular response to nanotherapeutics at microscale. [ABSTRACT FROM AUTHOR]

Tumor angiogenesis is a complex process that is unamenable to intravital whole‐process monitoring, especially on microscopic assessment of tumor microvessel and quantifying microvascular hemodynamics before and after the nanotherapeutics, which hinder the understanding of nanotheranostics outcomes in tumor treatment. Herein, a new photoacoustic (PA) imaging‐optical coherence tomography angiography (OCTA)‐laser speckle (LS) multimodal imaging strategy is first proposed, which is not only able to precisely macro guide the thermo‐chemotherapy of tumor by monitoring blood oxygen saturation (SaO2) and hemoglobin content (HbT), but also capable of long‐term microscopic investigating the microvessel morphology (microvascular density) and hemodynamics changes (relative blood flow) before and after the nanotherapeutics in vivo. Moreover, to realize the tumor thermo‐chemotherapy treatment based on this novel multimodal imaging strategy, a 2D 5‐fluorouracil silicon nanosheets (5‐Fu‐Si NSs) therapeutic agent is designed. Furthermore, 2D high‐resolution tumor microvascular images in different stage display that tendency of the thermo‐chemotherapy effect is closely associated with tumor angiogenesis. Taken together, the investigations establish the fundamental base in theory and technology for further tailoring the novel specific diagnosis and treatment strategy in tumor. More importantly, this technique will be beneficial to evaluate the tumor microvascular response to nanotherapeutics at microscale. [ABSTRACT FROM AUTHOR]

Determination of the precise location and the degree of the Choroidal neovascularization (CNV) lesion is essential for diagnosation Neovascular age-related macular degeneration (AMD) and evaluation the efficacy of treatment. Noninvasive imaging techniques with specific contrast for CNV evaluation are demanded. In this paper, two noninvasive imaging techniques, namely Optical coherence tomography (OCT) and Photoacoustic microscopy (PAM), are combined to provide specific detection of CNV for their complimentary contrast mechanisms. In vivo time-serial evaluation of Laser-induced CNV in rats is present at days 1, 3, 5, 7, 14, 21 after laser photocoagulation is applied to the rat fundus. Both OCT and PAM show that the CNV increases to its maximum at day 7 and decreases at day 14. Quantification of CNV area and CNV thickness is given. The dual-modal information of CNV is consistent with the histologic evaluation by hematoxylin and eosin (H&E) staining. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the feasibility and practicality of real-time noninvasive imaging and measurement of ocular accommodation (0-5D with one diopter step) using dual-channel, dual-focus spectral domain optical coherence tomography (SD-OCT). Materials and Methods: A custom-built, dual-channel, dual-focus SD-OCT was used to image the anterior segment, including the cornea, iris, and anterior and posterior lens surfaces. Three consecutive measurements were taken in each accommodative session for each subject. Changes in ocular dimensions during accommodation were calculated based on the acquired SD-OCT images. A Friedman test was used to test sensitivity of ocular dimension changes per diopter of accommodation. Results: With accommodation, anterior chamber depth (ACD), curvature radius of both anterior (RAL) and posterior (RPL) lens surfaces, and pupil diameter (PD) decreased significantly, whereas lens thickness (LT) increased significantly ( p < 0.05, Friedman test). Ocular dimensions tended to change according to the increasing of accommodative stimulus, as did a backward movement of the posterior lens surface. Conclusions: SD-OCT, via extended imaging depth through a dual-channel, dual-focus approach, is a feasible and practical modality for noninvasive imaging and measurement of ocular accommodation. [ABSTRACT FROM AUTHOR]

B Thermo-Chemotherapy b A promising biocompatible nanotheranostics agent based on chemotherapeutic drug 5-fluorouracil and 2D silicon nanosheets is developed for synergistic thermo-chemotherapy strategy. The tumor tissue functional parameters, including SaO SB 2 sb , HbT, micro microvascular morphology, and hemodynamics, are dynamically monitored by multimodal PA/OCTA/LS imaging strategy to accurately evaluate overall therapeutic effects. Intravital Whole-Process Monitoring Thermo-Chemotherapy Via 2D Silicon Nanoplatform: A Macro Guidance and Long-Term Microscopic Precise Imaging Strategy (Adv. Sci. 16/2021). [Extracted from the article]

Intravital Whole-Process Monitoring Thermo-Chemotherapy Via 2D Silicon Nanoplatform: A Macro Guidance and Long-Term Microscopic Precise Imaging Strategy (Adv. Sci. 16/2021) B Thermo-Chemotherapy b A promising biocompatible nanotheranostics agent based on chemotherapeutic drug 5-fluorouracil and 2D silicon nanosheets is developed for synergistic thermo-chemotherapy strategy. The tumor tissue functional parameters, including SaO SB 2 sb , HbT, micro microvascular morphology, and hemodynamics, are dynamically monitored by multimodal PA/OCTA/LS imaging strategy to accurately evaluate overall therapeutic effects. [Extracted from the article]

Summary: Grating spacing dependence of nonvolatile holographic recording in doubly doped lithium niobate crystals is theoretically investigated allowing arbitrary charge transport lengths. It is shown that the nonvolatile refractive index modulation initially increases with increasing grating spacing, then a saturation behavior arises because of the dominant bulk photovoltaic effect. Although different charge transport length results in different nonvolatile refractive index modulation, the grating spacing dependence of nonvolatile holographic recording obeys almost the same rules for arbitrary charge transport lengths. The experimental results obtained by recording nonvolatile holograms in LiNbO3:Cu:Ce crystals with different grating spacing are consistent with the theoretical analyses. [Copyright &y& Elsevier]