Multifunctional Ablative Gastrointestinal Imaging Capsule (MAGIC) for Esophagus Surveillance and Interventions.

Objective and Impact Statement: A clinically viable technology for comprehensive esophagus surveillance and potential treatment is lacking. Here, we report a novel multifunctional ablative gastrointestinal imaging capsule (MAGIC) technology platform to address this clinical need. The MAGIC technology could also facilitate the clinical translation and adoption of the tethered capsule endomicroscopy (TCE) technology. Introduction: Recently developed optical coherence tomography (OCT) TCE technologies have shown a promising potential for surveillance of Barrett's esophagus and esophageal cancer in awake patients without the need for sedation. However, it remains challenging with the current TCE technology for detecting early lesions and clinical adoption due to its suboptimal resolution, imaging contrast, and lack of visual guidance during imaging. Methods: Our technology reported here integrates dual-wavelength OCT imaging (operating at 800 and 1300 nm), an ultracompact endoscope camera, and an ablation laser, aiming to enable comprehensive surveillance, guidance, and potential ablative treatment of the esophagus. Results: The MAGIC has been successfully developed with its multimodality imaging and ablation capabilities demonstrated by imaging swine esophagus ex vivo and in vivo. The 800-nm OCT imaging offers exceptional resolution and contrast for the superficial layers, well suited for detecting subtle changes associated with early neoplasia. The 1300-nm OCT imaging provides deeper penetration, essential for assessing lesion invasion. The built-in miniature camera affords a conventional endoscopic view for assisting capsule deployment and laser ablation. Conclusion: By offering complementary and clinically viable functions in a single device, the reported technology represents an effective solution for endoscopic screening, diagnosis, and potential ablation treatment of the esophagus of a patient in an office setting.

SHG fiberscopy assessment of collagen morphology and its potential for breast cancer optical histology.

OBJECTIVE: this study is to investigate the feasibility of our recently developed nonlinear fiberscope for label-free in situ breast tumor detection and lymph node status assessment based on second harmonic generation (SHG) imaging of fibrillar collagen matrix with histological details. The long-term goal is to improve the current biopsy-based cancer paradigm with reduced sampling errors. METHODS: in this pilot study we undertook retrospective SHG imaging study of ex vivo invasive ductal carcinoma human biopsy tissue samples, and carried out quantitative image analysis to search for collagen structural signatures that are associated with the malignance of breast cancer. RESULTS: SHG fiberscopy image-based quantitative assessment of collagen fiber morphology reveals that: 1) cancerous tissues contain generally less extracellular collagen fibers compared with tumor-adjacent normal tissues, and 2) collagen fibers in lymph node positive biopsies are more aligned than lymph node negative counterparts. CONCLUSION/SIGNIFICANCE: the results demonstrate the promising potential of our SHG fiberscope for in situ breast tumor detection and lymph node involvement assessment and for offering real-time guidance during ongoing tissue biopsy.

The effect of miR-155-5p on M1 polarization of Kupffer cells and immune response during liver transplantation through regulating the expression of KDM5D.

BACKGROUND: To explore the effect and its specific mechanism of miR-155-5p on M1 polarization of Kupffer cells (KCs) and immune response in liver transplantation (LT) through KDM5D. METHODS: Primary KCs were isolated from Wistar rats and identified by cell culture, ink-swallowing test and flow cytometry. The cells identified as KCs were induced into LT acute rejection (AR) model cells by LPS/IFN-γ, flow cytometry was used for cell sorting and apoptosis detection. Enzyme-linked immunosorbent assay (ELISA) kit was used to detect the levels of inflammatory factors, macrophages and liver function markers. RT-qPCR detected the expression of miR-155-5p and KDM5D mRNA. The protein expression of KDM5D was detected by Western blot. Dual luciferase reporter gene experiment verified the targeting relationship between miR-155-5p and KDM5D. RESULTS: The separated KCs adhered after being cultured for 24 h, had pseudopodia and phagocytosis, and the proportion of F4/80 positive cells was more than 90%. The expression of miR-155-5p was increased in LPS/IFN-γ-induced KCs. And knockdown of miR-155-5p inhibited H3K4me3 and H3K27me3 of TNF-α promoter, M1 polarization of KCs and the immune response of AR model cells by upregulating KDM5D. In animal experiments, knockdown of miR-155-5p was found to inhibit liver damage and immune response in rats with allogeneic orthotopic LT. CONCLUSION: These results confirmed that miR-155-5p inhibited M1 polarization of KCs induced by LPS/IFN-γ, thereby alleviating AR and liver function impairment after LT by upregulating KDM5D.

Deep learning-based optical coherence tomography image analysis of human brain cancer.

Real-time intraoperative delineation of cancer and non-cancer brain tissues, especially in the eloquent cortex, is critical for thorough cancer resection, lengthening survival, and improving quality of life. Prior studies have established that thresholding optical attenuation values reveals cancer regions with high sensitivity and specificity. However, threshold of a single value disregards local information important to making more robust predictions. Hence, we propose deep convolutional neural networks (CNNs) trained on labeled OCT images and co-occurrence matrix features extracted from these images to synergize attenuation characteristics and texture features. Specifically, we adapt a deep ensemble model trained on 5,831 examples in a training dataset of 7 patients. We obtain 93.31% sensitivity and 97.04% specificity on a holdout set of 4 patients without the need for beam profile normalization using a reference phantom. The segmentation maps produced by parsing the OCT volume and tiling the outputs of our model are in excellent agreement with attenuation mapping-based methods. Our new approach for this important application has considerable implications for clinical translation.

Technologies for depth scanning in miniature optical imaging systems [Invited].

Biomedical optical imaging has found numerous clinical and research applications. For achieving 3D imaging, depth scanning presents the most significant challenge, particularly in miniature imaging devices. This paper reviews the state-of-art technologies for depth scanning in miniature optical imaging systems, which include two general approaches: 1) physically shifting part of or the entire imaging device to allow imaging at different depths and 2) optically changing the focus of the imaging optics. We mainly focus on the second group of methods, introducing a wide variety of tunable microlenses, covering the underlying physics, actuation mechanisms, and imaging performance. Representative applications in clinical and neuroscience research are briefly presented. Major challenges and future perspectives of depth/focus scanning technologies for biomedical optical imaging are also discussed.

Impact of MDR1 and UGT Gene Polymorphisms on Sodium Valproate Plasma Concentration in Patients with Epilepsy.

BACKGROUND: This study aimed to identify the effects of multidrug resistance gene 1 (MDR1) and UGT gene polymorphisms on the plasma concentration of VPA in subjects with epilepsy and provide a reference for individualized medicine of patients with epilepsy. METHODS: One hundred subjects with epilepsy who were treated with sustained release VPA monotherapy were enrolled. Sanger sequencing was used to detect the genotypes of MDR1_G1199A, MDR1_G2677T/A, UGT1A6_A 552C, T19G and UGT2B7_C161T. By adjusting the plasma concentrations of VPA with body weight and a total daily dose of VPA, the concentration-to-dose ratio of VPA (CDRV) was obtained. Data were analyzed using SPSS17.0. RESULTS: No mutation of MDR1_G1199A gene was detected. MDR1_G2677T/A site T allele frequency is 43.5%, A is 14%. The genetic frequencies of UGT1A6_A552C, T19G, and UGT2B7_C161T were 29.5%, 25.5%, and 36%, respectively. Significant differences in CDRV were observed between carriers of TT, TG, and GG genotypes in the UGT1A6_T19G polymorphism (p = 0.021, p < 0.05). The CDRV was significantly lower in patients carry UGT1A6_T19G GG genotype compared to TG ((3.40 ± 1.61) µg.kg/mL.mg) and TT ((4.33 ± 1.97) µg.kg/mL.mg) genotype. While the MDR1_G2677T/A, UGT1A6_A552C and UGT2B7_C161T gene polymorphisms had no effect on the plasma concentration of VPA (p > 0.05). CONCLUSIONS: The genetic polymorphisms of UGT1A6_T19G significantly affect the plasma concentration of VPA in patients with epilepsy and the mutation of this locus can decrease the blood concentration of VPA. The MDR1_G2677T/A, UGT1A6_A552C and UGT2B7_C161T gene polymorphisms did not affect the plasma VPA concentration in Han patients with epilepsy.

Direct Visualization and Quantitative Imaging of Small Airway Anatomy In Vivo Using Deep Learning Assisted Diffractive OCT.

OBJECTIVE/BACKGROUND: In vivo imaging and quantification of the microstructures of small airways in three dimensions (3D) allows a better understanding and management of airway diseases, such as asthma and chronic obstructive pulmonary disease (COPD). At present, the resolution and contrast of the currently available conventional optical coherence tomography (OCT) imaging technologies operating at 1300 nm remain challenging to directly visualize the fine microstructures of small airways in vivo. METHODS: We developed an ultrahigh-resolution diffractive endoscopic OCT at 800 nm to afford a resolving power of 1.7 µm (in tissue) with an improved contrast and a custom deep residual learning based image segmentation framework to perform accurate and automated 3D quantification of airway anatomy. RESULTS: The 800-nm diffractive OCT enabled the direct delineation of the structural components in the small airway wall in vivo. We further first demonstrated the 3D anatomic quantification of critical tissue compartments of small airways in sheep using the automated segmentation method. CONCLUSION: The deep learning assisted diffractive OCT provides a unique ability to access the small airways, directly visualize and quantify the important tissue compartments, such as airway smooth muscle, in the airway wall in vivo in 3D. SIGNIFICANCE: These pilot results suggest a potential technology for calculating volumetric measurements of small airways in patients in vivo.

In vivo assessment of inflammatory bowel disease in rats with ultrahigh-resolution colonoscopic OCT.

A technology capable of high-resolution, label-free imaging of subtle pathology in vivo during colonoscopy is imperative for the early detection of disease and the performance of accurate biopsies. While colonoscopic OCT has been developed to visualize colonic microstructures beyond the mucosal surface, its clinical potential remains limited by sub-optimal resolution (∼6.5 µm in tissue), inadequate imaging contrast, and a lack of high-resolution OCT criteria for lesion detection. In this study, we developed an ultrahigh-resolution (UHR) colonoscopic OCT and evaluated its ability to volumetrically visualize and identify the pathological features of inflammatory bowel disease (IBD) in a rat model. Owing to its improved resolution (∼1.7 µm in tissue) and enhanced contrast, UHR colonoscopic OCT can accurately delineate fine colonic microstructures and identify the pathophysiological characteristics of IBD in vivo. By using a quantitative optical attenuation map, UHR colonoscopic OCT is able to differentiate diseased tissue (such as crypt distortion and microabscess) from normal colonic mucosa over a large field of view in vivo. Our results suggest the clinical potential of UHR colonoscopic OCT for in vivo assessment of IBD pathology.

Diagnostic Value of MRI Combined with CXCR4 Expression Level in Lymph Node Metastasis Head and Neck Squamous Cell Carcinoma.

Objective: To explore the diagnostic value of magnetic resonance imaging (MRI) combined with CXCR4 expression levels in lymph node metastasis of the head and neck squamous cell carcinoma (HNSCC). Methods: 289 patients with HNSCC were divided into lymph node metastasis group (LNM group, n = 171) and non-LNM group (n = 118) according to the pathological examination results. MRI was used to scan the patient's lesions and cervical lymph nodes, and ADC was measured by MRI diffusion weighting imaging. The expression of CXCR4 in tumor tissues was detected by qRT-PCR. Logistic regression was used to analyze the risk factors of HNSCC lymph node metastasis. ROC curve was used to analyze the diagnostic effects of MRI, CXCR4, and MRI combined with CXCR4 on HNSCC lymph node metastasis. Results: Compared with the non-LNM group, patients in the LNM group had a lower degree of pathological differentiation, and the positive rate of TNM staging and vascular invasion was higher. The signal intensity of T1WI and T2WI were low intensity and high intensity, respectively, and the ADC value was significantly reduced. At the same time, the expression level of CXCR4 in the tumor tissues of the LNM group was also significantly increased. In addition, compared with MRI and CXCR4 used alone, MRI combined with CXCR4 has a higher predictive value. Conclusion: MRI has a good effect in demonstrating lymph node metastasis. CXCR4 is significantly upregulated in lymph node metastasis tumor tissue. The combination of the two can be used for clinical diagnosis of HNSCC lymph node metastasis.

Visualization and Validation of The Microstructures in The Airway Wall in vivo Using Diffractive Optical Coherence Tomography.

RATIONALE AND OBJECTIVES: At present, there is no available method to study the in vivo microstructures of the airway wall (epithelium, smooth muscle, adventitia, basement membrane, glands, cartilage). Currently, we rely on ex vivo histologic evaluation of airway biopsies. To overcome this obstacle, we have developed an endoscopic ultrahigh-resolution diffractive optical coherence tomography (OCT) system, operating at a wavelength of 800 nm, to non-invasively study the in vivo microstructures of the airway wall. Prior to human study, validation of diffractive OCT's ability to quantitate airway microstructural components is required. MATERIALS AND METHODS: To validate and demonstrate the accuracy of this OCT system, we used an ovine model to image small airways (∼ 2 mm in diameter). Histologic samples and correlated OCT images were matched. The cross-sectional area of the airway wall, lumen, and other microstructures were measured and compared. RESULTS: A total of 27 sheep were studied from which we identified 39 paired OCT-histology airway images. We found strong correlations between the OCT and the histology measurements of the airway wall area and the microstructural area measurements of the epithelium, basement membrane, airway smooth muscle, glands, cartilage, and adventitia. The correlations ranged from r=0.61 (p<0.001) for the epithelium to r=0.86 (p<0.001) for the adventitia with the correlation between the OCT and the histology measurements for the entire airway wall of r=0.76 (p<0.001). CONCLUSION: Given the high degree of correlation, these data validate the ability to acquire and quantify in vivo microscopic level imaging with this newly developed 800nm ultra-high resolution diffractive OCT system.

Deep-learning two-photon fiberscopy for video-rate brain imaging in freely-behaving mice.

Scanning two-photon (2P) fiberscopes (also termed endomicroscopes) have the potential to transform our understanding of how discrete neural activity patterns result in distinct behaviors, as they are capable of high resolution, sub cellular imaging yet small and light enough to allow free movement of mice. However, their acquisition speed is currently suboptimal, due to opto-mechanical size and weight constraints. Here we demonstrate significant advances in 2P fiberscopy that allow high resolution imaging at high speeds (26 fps) in freely-behaving mice. A high-speed scanner and a down-sampling scheme are developed to boost imaging speed, and a deep learning (DL) algorithm is introduced to recover image quality. For the DL algorithm, a two-stage learning transfer strategy is established to generate proper training datasets for enhancing the quality of in vivo images. Implementation enables video-rate imaging at ~26 fps, representing 10-fold improvement in imaging speed over the previous 2P fiberscopy technology while maintaining a high signal-to-noise ratio and imaging resolution. This DL-assisted 2P fiberscope is capable of imaging the arousal-induced activity changes in populations of layer2/3 pyramidal neurons in the primary motor cortex of freely-behaving mice, providing opportunities to define the neural basis of behavior.

Impact of CYP2C19 and CYP2C9 gene polymorphisms on sodium valproate plasma concentration in patients with epilepsy.

BACKGROUND: Valproic acid (VPA) is a broad spectrum anticonvulsant drug, which could be partially metabolised by cytochrome P450 (CYP) 2C9 and 2C19 enzymes. This study was designed to investigate the relationship between CYP2C19 and CYP2C9 gene polymorphisms and the plasma concentrations of VPA in subjects with epilepsy. METHODS: Eighty-three subjects with epilepsy aged 18-92 years were enrolled in this study. All were treated with sustained-release VPA monotherapy. Based on the genotypes of CYP2C19 and the ability to metabolise substrates, the subjects were divided into poor metabolisers, intermediate metabolisers and extensive metabolisers. Sanger sequencing was used to detect the genotypic and allelic frequencies of CYP2C19 (*1, *2 and *3) and CYP2C9 (*13) of the patients. Automatic immunity analysis was used to find steady-state trough plasma concentrations of VPA. By adjusting the plasma concentrations of VPA with body weight and total daily dose of VPA, the concentration-to-dose ratio of VPA (CDRV) was obtained. Data were analysed using SPSS software. RESULTS: The genetic frequencies of CYP2C19*2, CYP2C19*3 and CYP2C9*13 were 33.1%, 3.0% and 5.4%, respectively, among patients with epilepsy from Yunnan province, China who used VPA therapy. The CDRV was significantly lower in the CYP2C19 extensive metabolisers (3.33±1.78) than it was in the CYP2C19 intermediate metabolisers (4.45±1.42) and the CYP2C19 poor metabolizers (6.64±1.06). The CYP2C19*2 and CYP2C19*3 alleles were correlated with the plasma VPA concentration, while the CYP2C9*13 allele had no effect on the plasma VPA concentration (p=0.809). CONCLUSIONS: The genetic polymorphisms of CYP2C19 significantly affect the VPA plasma concentration, and the dosage of VPA for intermediate and poor metabolisers could be lower than for extensive metabolisers. CYP2C9*13 carrier was not closely related to plasma concentrations of VPA in patients with epilepsy.

Minimizing OCT quantification error via a surface-tracking imaging probe.

OCT-based quantitative tissue optical properties imaging is a promising technique for intraoperative brain cancer assessment. The attenuation coefficient analysis relies on the depth-dependent OCT intensity profile, thus sensitive to tissue surface positions relative to the imaging beam focus. However, it is almost impossible to maintain a steady tissue surface during intraoperative imaging due to the patient's arterial pulsation and breathing, the operator's motion, and the complex tissue surface geometry of the surgical cavity. In this work, we developed an intraoperative OCT imaging probe with a surface-tracking function to minimize the quantification errors in optical attenuation due to the tissue surface position variations. A compact OCT imaging probe was designed and engineered to have a long working distance of ∼ 41 mm and a large field of view of 4 × 4 mm2 while keeping the probe diameter small (9 mm) to maximize clinical versatility. A piezo-based linear motor was integrated with the imaging probe and controlled based upon real-time feedback of tissue surface position inferred from OCT images. A GPU-assisted parallel processing algorithm was implemented, enabling detection and tracking of tissue surface in real-time and successfully suppressing more than 90% of the typical physiologically induced motion range. The surface-tracking intraoperative OCT imaging probe could maintain a steady beam focus inside the target tissue regardless of the surface geometry or physiological motions and enabled to obtain tissue optical attenuation reliably for assessing brain cancer margins in challenging intraoperative settings.

Label-free imaging of human brain tissue at subcellular resolution for potential rapid intra-operative assessment of glioma surgery.

Background: Frozen section and smear preparation are the current standard for intraoperative histopathology during cancer surgery. However, these methods are time-consuming and subject to limited sampling. Multiphoton microscopy (MPM) is a high-resolution non-destructive imaging technique capable of optical sectioning in real time with subcellular resolution. In this report, we systematically investigated the feasibility and translation potential of MPM for rapid histopathological assessment of label- and processing-free surgical specimens. Methods: We employed a customized MPM platform to capture architectural and cytological features of biological tissues based on two-photon excited NADH and FAD autofluorescence and second harmonic generation from collagen. Infiltrating glioma, an aggressive disease that requires subcellular resolution for definitive characterization during surgery, was chosen as an example for this validation study. MPM images were collected from resected brain specimens of 19 patients and correlated with histopathology. Deep learning was introduced to assist with image feature recognition. Results: MPM robustly captures diagnostic features of glioma including increased cellularity, cellular and nuclear pleomorphism, microvascular proliferation, necrosis, and collagen deposition. Preliminary application of deep learning to MPM images achieves high accuracy in distinguishing gray from white matter and cancer from non-cancer. We also demonstrate the ability to obtain such images from intact brain tissue with a multiphoton endomicroscope for intraoperative application. Conclusion: Multiphoton imaging correlates well with histopathology and is a promising tool for characterization of cancer and delineation of infiltration within seconds during brain surgery.

Circular RNA ABCB10 contributes to laryngeal squamous cell carcinoma (LSCC) progression by modulating the miR-588/CXCR4 axis.

Laryngeal squamous cell carcinoma (LSCC) is a common head and neck cancer with a high metastasis and poor prognosis. Circular RNAs (circRNAs) are a type of non-coding RNAs (ncRNAs) with regulatory function and broadly participate in cancer development. However, the correlation of circular RNA ABCB10 (circABCB10) with LSCC remains unclear. Here, we were interested in the role of circABCB10 in the modulation of LSCC progression. Our data demonstrated that the depletion of circABCB10 significantly inhibited the proliferation and induced the apoptosis of LSCC cells. Meanwhile, circABCB10 knockdown was able to remarkably reduce the invasion and migration of LSCC cells. Mechanically, circABCB10 served as a sponge for microRNAs-588 (miR-588) and miR-588 could target and down-regulated chemokine receptor 4 (CXCR4) expression in LSCC cells. The overexpression of CXCR4 or miR-588 inhibitor could reverse circABCB10 depletion-attenuated malignant phenotypes of LSCC cells. Functionally, the depletion of circABCB10 alleviated the tumor growth of LSCC cells in the tumorigenicity analysis of nude mice. The CXCR4 expression was decreased while the miR-588 expression was enhanced by circABCB10 depletion in vivo. Thus, we concluded that circABCB10 was involved in the malignant progression of LSCC by regulating miR-588/CXCR4 axis. Our finding provides new insights into the mechanism of circRHOT1 contributing to the development of LSCC. CircABCB10 and miR-588 may be used as potential targets for the treatment of LSCC.

Multicolor fiber-optic two-photon endomicroscopy for brain imaging.

Visualizing activity patterns of distinct cell types during complex behaviors is essential to understand complex neural networks. It remains challenging to excite multiple fluorophores simultaneously so that different types of neurons can be imaged. In this Letter, we report a multicolor fiber-optic two-photon endomicroscopy platform in which two pulses from a Ti:sapphire laser and an optical parametric oscillator were synchronized and delivered through a single customized double-clad fiber to excite multiple chromophores. A third virtual wavelength could also be generated by spatial-temporal overlapping of the two pulses. The performance of the fiber-optic multicolor two-photon endomicroscope was demonstrated by in vivo imaging of a mouse cerebral cortex with "Brainbow" labeling.

Deep OCT image compression with convolutional neural networks.

We report an end-to-end image compression framework for retina optical coherence tomography (OCT) images based on convolutional neural networks (CNNs), which achieved an image size compression ratio as high as 80. Our compression scheme consists of three parts: data preprocessing, compression CNNs, and reconstruction CNNs. The preprocessing module was designed to reduce OCT speckle noise and segment out the region of interest. Skip connections with quantization were developed and added between the compression CNNs and the reconstruction CNNs to reserve the fine-structure information. Two networks were trained together by taking the semantic segmented images from the preprocessing module as input. To train the two networks sensitive to both low and high frequency information, we leveraged an objective function with two components: an adversarial discriminator to judge the high frequency information and a differentiable multi-scale structural similarity (MS-SSIM) penalty to evaluate the low frequency information. The proposed framework was trained and evaluated on ophthalmic OCT images with pathological information. The evaluation showed reconstructed images can still achieve above 99% similarity in terms of MS-SSIM when the compression ratio reached 40. Furthermore, the reconstructed images after 80-fold compression with the proposed framework even presented comparable quality with those of a compression ratio 20 from state-of-the-art methods. The test results showed that the proposed framework outperformed other methods in terms of both MS-SSIM and visualization, which was more obvious at higher compression ratios. Compression and reconstruction were fast and took only about 0.015 seconds per image. The results suggested a promising potential of deep neural networks on customized medical image compression, particularly valuable for effective image storage and tele-transfer.

In vivo assessment of vascular-targeted photodynamic therapy effects on tumor microvasculature using ultrahigh-resolution functional optical coherence tomography.

Vascular-targeted photodynamic therapy (VTP) is an emerging treatment for tumors. The change of tumor vasculatures, including a newly-formed microvascular, in response to VTP, is a key assessment parameter for optimizing the treatment effect. However, an accurate assessment of vasculature, particularly the microvasculature's changes in vivo, remains challenging due to the limited resolution afforded by existing imaging modalities. In this study, we demonstrated the in vivo imaging of VTP effects on an A431 tumor-bearing window chamber model of a mouse with an 800-nm ultrahigh-resolution functional optical coherence tomography (UHR-FOCT). We further quantitatively demonstrated the effects of VTP on the size and density of tumor microvasculature before, during, and after the treatment. Our results suggest the promising potential of UHR-FOCT for assessing the tumor treatment with VTP in vivo and in real time to achieve an optimal outcome.