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Background: Gastric cancer (GC) is associated with a significant global health burden and high mortality rates when diagnosed at later stages. The diagnosis often occurs at advanced stages when treatment options are limited and less effective. Early detection strategies are crucial to improving survival rates and outcomes for patients. Blue laser imaging (BLI) is an image-enhanced endoscopy technique that utilizes white light and narrow-band light to detect pathological changes in the mucosal architecture. This study aims at investigating the diagnostic performance of BLI for the detection of GC. Methods: A comprehensive search was conducted across multiple databases from inception until March 2023. Studies assessing the diagnostic efficacy of BLI for GC detection were included. The sensitivity, specificity and accuracy of BLI were calculated using pooled proportions and 95% confidence intervals (CI) with a random-effects model. Heterogeneity among the included studies was assessed using the I2 statistic. Results: Six studies were included in the pooled analysis. There were 708 patients with 380 GC lesions. Most of the lesions involved the lower two-thirds of the stomach. The pooled performance metrics of BLI for GC detection were as follows: sensitivity of 91.9% (95% CI 83.3–96.3%; I2 = 82.3%), specificity of 93.4% (95% CI 82.0–97.8%; I2 = 87.9%) and accuracy of 95.4% (95% CI 72.6–99.8%; I2 = 73.6%). Conclusion: BLI demonstrates high diagnostic efficacy for the detection of GC. BLI can be a valuable tool in clinical practice. However, large-scale, randomized controlled studies are needed to further establish the role of BLI in routine clinical practice for GC detection. [ABSTRACT FROM AUTHOR]

Objective: To assess whether narrow band imaging (NBI) detects fields of cancerisation around suspicious lesions in the upper aerodigestive tract, which were undetected by white light imaging (WLI). Methods: In 96 patients with laryngeal and pharyngeal lesions suspicious for malignancy, 206 biopsies were taken during laryngoscopy: 96 biopsies of suspicious lesions detected by both WLI and NBI (WLI+/NBI+), 60 biopsies adjacent mucosa only suspicious with NBI (WLI‐/NBI+), and 46 biopsies of NBI and WLI unsuspicious mucosa (WLI‐/NBI‐) as negative controls. Optical diagnosis according to the Ni‐classification was compared with histopathology. Results: Signs of (pre)malignancy were found in 88% of WLI+/NBI+ biopsies, 32% of WLI‐/NBI+ biopsies and 0% in WLI‐/NBI‐ (p <.001). In 58% of the WLI‐/NBI+ mucosa any form of dysplasia or carcinoma was detected. Conclusion: The use of additional NBI led to the detection of (pre)malignancy in 32% of the cases, that would have otherwise remained undetected with WLI alone. This highlights the potential of NBI as a valuable adjunct to WLI in the identification of suspicious lesions in the upper aerodigestive tract. [ABSTRACT FROM AUTHOR]

Background: Our previous studies have demonstrated that Raman spectroscopy could be used for skin cancer detection with good sensitivity and specificity. The objective of this study is to determine if skin cancer detection can be further improved by combining deep neural networks and Raman spectroscopy. Patients and methods: Raman spectra of 731 skin lesions were included in this study, containing 340 cancerous and precancerous lesions (melanoma, basal cell carcinoma, squamous cell carcinoma and actinic keratosis) and 391 benign lesions (melanocytic nevus and seborrheic keratosis). One-dimensional convolutional neural networks (1D-CNN) were developed for Raman spectral classification. The stratified samples were divided randomly into training (70%), validation (10%) and test set (20%), and were repeated 56 times using parallel computing. Different data augmentation strategies were implemented for the training dataset, including added random noise, spectral shift, spectral combination and artificially synthesized Raman spectra using one-dimensional generative adversarial networks (1D-GAN). The area under the receiver operating characteristic curve (ROC AUC) was used as a measure of the diagnostic performance. Conventional machine learning approaches, including partial least squares for discriminant analysis (PLS-DA), principal component and linear discriminant analysis (PC-LDA), support vector machine (SVM), and logistic regression (LR) were evaluated for comparison with the same data splitting scheme as the 1D-CNN. Results: The ROC AUC of the test dataset based on the original training spectra were 0.886±0.022 (1D-CNN), 0.870±0.028 (PLS-DA), 0.875±0.033 (PC-LDA), 0.864±0.027 (SVM), and 0.525±0.045 (LR), which were improved to 0.909 ±0.021 (1D-CNN), 0.899±0.022 (PLS-DA), 0.895±0.022 (PC-LDA), 0.901 ±0.020 (SVM), and 0.897±0.021 (LR) respectively after augmentation of the training dataset (p<0.0001, Wilcoxon test). Paired analyses of 1D-CNN with conventional machine learning approaches showed that 1D-CNN had a 1-3% improvement (p<0.001, Wilcoxon test). Conclusions: Data augmentation not only improved the performance of both deep neural networks and conventional machine learning techniques by 2-4%, but also improved the performance of the models on spectra with higher noise or spectral shifting. Convolutional neural networks slightly outperformed conventional machine learning approaches for skin cancer detection by Raman spectroscopy. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of blending dimethyl ether (DME) and ethanol on the soot transition periods in ethylene counterflow diffusion flames by using a novel optical diagnostic method. The soot critical transition point in different conditions is identified experimentally and numerically. Two kinds of flames are carried out to gain the soot critical transition point in counterflow diffusion flames by changing oxygen fraction (Xo) and changing volume flow rates of fuel and oxidizer (Qv). The red-green-blue (RGB) ratio method is used to precisely identify the soot critical transition point, and chemical kinetic simulations are performed to analyze the detailed reaction paths. The results show that compared to the ethylene flame, the soot critical transition point occurs at a higher Xo and a lower Qv when DME or ethanol is blended. The addition of DME and ethanol can inhibit soot formation, due to the degree of soot formation reaction being lower than the degree of the oxidation reaction in the blending flames. [ABSTRACT FROM AUTHOR]

ndoscopic mucosal resection (EMR) is a therapeutic technique developed for the resectioning of sessile and flat lesions localized in the mucosa of any part of the gastrointestinal tract. It is easy to learn and allows the resection of large polyps that would otherwise require radical surgery. For early detection of neoplasia of the gastrointestinal tract, the screening program for colorectal cancer proved to be the most important, and its wide acceptance led to a decrease in the incidence and mortality rate. This article reviews EMR techniques and focuses on large colorectal polyps, representing the most common indication for EMR. Before starting resection, the endoscopist should carefully and thoroughly examine the lesion and differentiate between resectable lesions and those potentially affected by the submucosal invasion. There are different methods of evaluating polyps; more recently advanced techniques are also used. The characteristics of colorectal lesions, including location, size, morphology, and histology, influence the choice of the optimal method of removal. The EMR removes part of the wall of the colorectum that contains the mucosa, the muscularis mucosa and partially or completely, the submucosal layer. In addition to removing benign adenomas of varying degrees of atypia, mucosectomy enables the treatment of early colorectal cancer where the risk of metastasis to the lymph glands is minimal. The primary goal of EMR is the complete and safe removal of colorectal lesions and the complete prevention of CRC. Techniques for performing EMR include conventional EMR with submucosal solution injection, hot loop, and electrocautery removal of colorectal lesions, as well as alternative EMR techniques such as cold loop EMR and "underwater" EMR. Major adverse events associated with EMR include bleeding and perforation after mucosectomy. Because of the risk of polyp recurrence regardless of the EMR technique, as well as the risk of metachronous polyps, control colonoscopies are necessary, especially in patients with the highest risk of recurrence.

This review article provides a comprehensive overview of the evolving techniques in image-enhanced endoscopy (IEE) for the characterization of colorectal polyps, and the potential of artificial intelligence (AI) in revolutionizing the diagnostic accuracy of endoscopy. We discuss the historical use of dye-spray and virtual chromoendoscopy for the characterization of colorectal polyps, which are now being replaced with more advanced technologies. Specifically, we focus on the application of AI to create a "virtual biopsy" for the detection and characterization of colorectal polyps, with potential for replacing histopathological diagnosis. The incorporation of AI has the potential to provide an evolutionary learning system that aids in the diagnosis and management of patients with the best possible outcomes. A detailed analysis of the literature supporting AI-assisted diagnostic techniques for the detection and characterization of colorectal polyps, with a particular emphasis on AI's characterization mechanism, is provided. The benefits of AI over traditional IEE techniques, including the reduction in human error in diagnosis, and its potential to provide an accurate diagnosis with similar accuracy to the gold standard are presented. However, the need for large-scale testing of AI in clinical practice and the importance of integrating patient data into the diagnostic process are acknowledged. In conclusion, the constant evolution of IEE technology and the potential for AI to revolutionize the field of endoscopy in the future are presented. [ABSTRACT FROM AUTHOR]

Abstract Background Accurate diagnosis of breast cancer (BC) plays a crucial role in clinical pathology analysis and ensuring precise surgical margins to prevent recurrence. Methods Laser-induced fluorescence (LIF) technology offers high sensitivity to tissue biochemistry, making it a potential tool for noninvasive BC identification. In this study, we utilized hyperspectral (HS) imaging data of stimulated BC specimens to detect malignancies based on altered fluorescence characteristics compared to normal tissue. Initially, we employed a HS camera and broadband spectrum light to assess the absorbance of BC samples. Notably, significant absorbance differences were observed in the 440–460 nm wavelength range. Subsequently, we developed a specialized LIF system for BC detection, utilizing a low-power blue laser source at 450 nm wavelength for ten BC samples. Results Our findings revealed that the fluorescence distribution of breast specimens, which carries molecular-scale structural information, serves as an effective marker for identifying breast tumors. Specifically, the emission at 561 nm exhibited the greatest variation in fluorescence signal intensity for both tumor and normal tissue, serving as an optical predictive biomarker. To enhance BC identification, we propose an advanced image classification technique that combines image segmentation using contour mapping and K-means clustering (K-mc, K = 8) for HS emission image data analysis. Conclusions This exploratory work presents a potential avenue for improving "in-vivo" disease characterization using optical technology, specifically our LIF technique combined with the advanced K-mc approach, facilitating early tumor diagnosis in BC.

In this paper, the spray and combustion characteristics of diesel/butanol-blended fuels were studied within a high-temperature and high-pressure constant volume chamber equipped with a single-hole injector. Two blends with 80% diesel/20% butanol and 60% diesel/40% butanol mixed by volume were tested in this study. The pure diesel B0 was also tested here as a reference. The spray penetration, flame lift-off length, and soot optical thickness were obtained through high-speed schlieren imaging, OH* chemiluminescence, and diffused back-illumination extinction imaging technique, respectively. The thermogravimetric curves of different fuels were obtained through a thermogravimetric analyzer. The results showed that butanol/diesel blends presented a longer ignition delay (ID) and flame lift-off length compared with pure diesel, and such finding was mainly caused by the lower cetane number and higher latent heat of vaporization of n-butanol. With the increase in the n-butanol ratio, soot production in the combustion process decreased significantly. Given the shorter ID period, the soot distribution of pure diesel reached a steady state earlier than the blends. [ABSTRACT FROM AUTHOR]

Study on the ignition characteristics of coal is the theoretical basis for realizing the high-efficient and clean utilization of coal. The alkali metals such as K and Na in coal are released into the gas phase during combustion and enter the system, which can easily cause high temperature corrosion of the reactor, fouling of the heating surface and slagging in the furnace. Based on the single-particle coal ignition detection platform, the ignition and alkali metal Na* and K* radiation characteristics of single-particle Yangchangwan (YCW) bituminous coal and Naomaohu (NMH) lignite during combustion were investigated under different oxygen volume flow rates. High-speed camera technology was used to capture the flame evolution process during single-particle coal ignition, and hyperspectral imaging technology was used to measure the spontaneous emission spectra of alkali metals Na* and K* in the flame to obtain the spatial release behavior of alkali metals. The results show that the ignition process of different types of coal is different. The enveloping flame is formed in the combustion process of volatile matter in the YCW coal particles, while the ignition reaction of the NMH coal is more intense without enveloping phenomenon due to its high volatile matter content, and the flame brightness in the whole ignition process is stronger than that of the YCW coal. The increase of oxygen can promote the ignition of coal particles, with the increase of oxygen volume flow, the ignition delay time of the YCW coal and the NMH coal decreases, and the ignition delay time of the NMH coal is smaller than that of the YCW coal. When the fire occurs, the flame brightness is the brightest, and the flame shape is relatively smooth and stable. The radiation characteristics of alkali metals Na* and K* in single-particle YCW coal and NMH coal during ignition and combustion are different from that in coke combustion process, in which the radiation intensity of Na* and K* is the strongest. Na* has a release peak both in the volatile reaction process and coke reaction process, but K* radiation intensity does not have an obvious release peak in the volatile reaction process and coke combustion process. When oxygen content increases, the release time of alkali metals from the YCW coal and the NMH coal is gradually advanced, and the beginning time of alkali metal radiation from the NMH coal is less than that from the YCW coal. In addition, the analysis of the ignition process of single-particle coal shows that the release intensity of alkali metals Na* and K* in the peripheral position of the combustion flame is stronger than that in the central position.

Background/Aims Although the 3-second rule has been shown in our previous study to improve high-confidence (HC) assessment in optical diagnosis, the process remains not well-established. Additionally, the impact of recent advances in artificial intelligence and its interaction with endoscopists remains uncertain. This study aimed to evaluate the effectiveness of a new computer-aided diagnosis (CADx) system, combined with the 3-second rule, in the optical diagnosis of colorectal polyps among endoscopists with varying levels of experience. Methods This multicenter ex vivo study involved 35 endoscopists, each of whom evaluated 100 polyps (51 adenomas, 39 hyperplastic polyps, 10 sessile serrated lesions) using narrow-band imaging (NBI) video clips via an online test platform. The evaluations were conducted in two stages: independent diagnosis and diagnosis with CADx assistance. HC was defined by the 3-second rule established in a previous study. Performance metrics included HC accuracy, HC rate, and adherence to the Preservation and Incorporation of Valuable Endoscopic Innovations (PIVI) and Simple Optical Diagnosis Accuracy (SODA) thresholds. Results The stand-alone performance of CADx demonstrated accuracy, sensitivity, specificity, and positive and negative predictive values of 90.0%, 95.1%, 82.1%, 89.2%, and 91.4%, respectively. The CADx-assisted phase, using the 3-second rule, significantly improved both HC accuracy (78.3% vs. 89.8%; p<0.001) and HC rates (64.2% vs. 75.4%; p<0.001) across all groups. Notably, novice endoscopists exhibited a substantial increase in accuracy with CADx assistance (74.1% vs. 88.8%; p<0.0001) (Table). The CADx-assisted performance for HC diagnoses nearly achieved the SODA standards and PIVI thresholds when combined with the use of the 3-second rule (Figure). Conclusion The new CADx system, when used in conjunction with the 3-second rule, significantly enhances the optical diagnosis of colorectal polyps, particularly among less experienced endoscopists. This combined approach could be valuable for cost-effective management strategies for colorectal polyps. [ABSTRACT FROM AUTHOR]

Background: Accurate diagnosis of breast cancer (BC) plays a crucial role in clinical pathology analysis and ensuring precise surgical margins to prevent recurrence. Methods: Laser-induced fluorescence (LIF) technology offers high sensitivity to tissue biochemistry, making it a potential tool for noninvasive BC identification. In this study, we utilized hyperspectral (HS) imaging data of stimulated BC specimens to detect malignancies based on altered fluorescence characteristics compared to normal tissue. Initially, we employed a HS camera and broadband spectrum light to assess the absorbance of BC samples. Notably, significant absorbance differences were observed in the 440–460 nm wavelength range. Subsequently, we developed a specialized LIF system for BC detection, utilizing a low-power blue laser source at 450 nm wavelength for ten BC samples. Results: Our findings revealed that the fluorescence distribution of breast specimens, which carries molecular-scale structural information, serves as an effective marker for identifying breast tumors. Specifically, the emission at 561 nm exhibited the greatest variation in fluorescence signal intensity for both tumor and normal tissue, serving as an optical predictive biomarker. To enhance BC identification, we propose an advanced image classification technique that combines image segmentation using contour mapping and K-means clustering (K-mc, K = 8) for HS emission image data analysis. Conclusions: This exploratory work presents a potential avenue for improving "in-vivo" disease characterization using optical technology, specifically our LIF technique combined with the advanced K-mc approach, facilitating early tumor diagnosis in BC. [ABSTRACT FROM AUTHOR]

The sudden outbreak of the COVID-19 pandemic led to a huge concern globally because of the astounding increase in mortality rates worldwide. The medical imaging computed tomography technique, whole-genome sequencing, and electron microscopy are the methods generally used for the screening and identification of the SARS-CoV-2 virus. The main aim of this review is to emphasize the capabilities of various optical techniques to facilitate not only the timely and effective diagnosis of the virus but also to apply its potential toward therapy in the field of virology. This review paper categorizes the potential optical biosensors into the three main categories, spectroscopic-, nanomaterial-, and interferometry-based approaches, used for detecting various types of viruses, including SARS-CoV-2. Various classifications of spectroscopic techniques such as Raman spectroscopy, near-infrared spectroscopy, and fluorescence spectroscopy are discussed in the first part. The second aspect highlights advances related to nanomaterial-based optical biosensors, while the third part describes various optical interferometric biosensors used for the detection of viruses. The tremendous progress made by lab-on-a-chip technology in conjunction with smartphones for improving the point-of-care and portability features of the optical biosensors is also discussed. Finally, the review discusses the emergence of artificial intelligence and its applications in the field of bio-photonics and medical imaging for the diagnosis of COVID-19. The review concludes by providing insights into the future perspectives of optical techniques in the effective diagnosis of viruses. [ABSTRACT FROM AUTHOR]

Refractive index and density matching are essential for optical measurements of neutrally buoyant liquid–liquid flows. In this study, we proposed a design of experiments (DoE) to develop refractive index and density matching systems, including objective setting, candidates screening, sampling and fitting, and a detailed matching process. Candidates screening criteria based on the density and refractive index ranges of the aqueous and organic phases were used. Using the DoE, we proposed a system with a ternary aqueous phase potassium thiocyanate (KSCN)/ammonium thiocyanate (NH4SCN) solution and m-dichlorobenzene/tripropionin solution as the organic phase to achieve the tuning of the RI and density simultaneously. Empirical correlations of the refractive index and density with respect to the concentration and temperature for the three mixtures were obtained by combining Latin hypercube sampling with binary polynomial fitting. Correlations were validated with existing data in the literature and were found to align with deviations as low as 4 × 10 − 4 for the refractive index and 2 × 10 − 3   g ⋅ cm − 3 for the density. Using the correlations, the refractive indices for the ternary aqueous phase, the binary organic phase, and the device materials were matched to be equal. Density matching was performed for the liquid–liquid phases as well. Refractive index- and density-matched recipes could be obtained for a wide range of temperatures (15–65 °C) and device materials (PMMA, borosilicate glass, quartz, and silica gel). These recipes provide options for the optical measurement of a liquid–liquid system required to neutralize buoyancy. [ABSTRACT FROM AUTHOR]

Assessment of the anatomical colorectal segment of polyps during colonoscopy is important for treatment and follow-up strategies, but is largely operator dependent. This feasibility study aimed to assess whether, using images of a magnetic endoscope imaging (MEI) positioning device, a deep learning approach can be useful to objectively divide the colorectum into anatomical segments. Models based on the VGG-16 based convolutional neural network architecture were developed to classify the colorectum into anatomical segments. These models were pre-trained on ImageNet data and further trained using prospectively collected data of the POLAR study in which endoscopists were using MEI (3930 still images and 90,151 video frames). Five-fold cross validation with multiple runs was used to evaluate the overall diagnostic accuracies of the models for colorectal segment classification (divided into a 5-class and 2-class colorectal segment division). The colorectal segment assignment by endoscopists was used as the reference standard. For the 5-class colorectal segment division, the best performing model correctly classified the colorectal segment in 753 of the 1196 polyps, corresponding to an overall accuracy of 63%, sensitivity of 63%, specificity of 89% and kappa of 0.47. For the 2-class colorectal segment division, 1112 of the 1196 polyps were correctly classified, corresponding to an accuracy of 93%, sensitivity of 93%, specificity of 90% and kappa of 0.82. The diagnostic performance of a deep learning approach for colorectal segment classification based on images of a MEI device is yet suboptimal (clinicaltrials.gov: NCT03822390). [ABSTRACT FROM AUTHOR]

Research on combustion characteristics can provide basic information and theoretical support for the design of insensitive propellant. This work aims to investigate the combustion characteristics of insensitive triple-base propellant. All propellants were prepared based on same triple-base propellant, but they were desensitized with the same desensitizer in different ways. The high-speed camera, spontaneous luminescence, NO, NH chemiluminescence, and OH-planar laser induction fluorescence (PLIF) methods were employed to capture the combustion flame and derive the distributions of important intermediates. Results show that ignition delay times of insensitive propellants are obviously longer. This indicated that the application of the desensitizer has a partly hindering effect on the early ignition stage. The combustion time of insensitive propellants is mostly similar, which means that the desensitizer has little influence on the intensity of actual combustion. The change in flame height and area of insensitive propellants over time indicated that the combustion progressivity of some insensitive propellants was more prominent, which means that the desensitizer concentration and desensitizing methods all affect the performance of insensitive propellant. The signal intensities of NO and NH show a negative correlation, indicating that a competitive relationship probably exists between the formation of NO and NH radicals during the reaction process. The high concentration of OH mainly locates outside NO, suggesting that there may be a transformation between NO and OH. The maximum signal intensity of NO and NH of different insensitive propellants confirmed that both the concentration of desensitizers and the desensitizing methods exhibit important effect on the reaction process. [ABSTRACT FROM AUTHOR]

Gas targets hold distinctive significance and advantages in the field of laser-matter interaction. As a major type of gas targets, supersonic gas target is one of the most commonly used targets for laser wakefield acceleration (LWFA). The temporal-spatial resolution study of it could provide valuable data references for the LWFA experiment. In this work, a Nomarski interference system with high spatial-temporal resolution was set up to diagnose the jet process of supersonic gas jet target. The formation process of supersonic gas jet under different jet durations, different injection positions and different gas back pressures was studied. It is beneficial to determine the more optimized time and position of laser injection into target when conducting LWFA experiments. Therefore, the quality of the obtained electron beam and radiation source can be effectively improved.

This review article provides a comprehensive overview of the evolving techniques in image-enhanced endoscopy (IEE) for the characterization of colorectal polyps, and the potential of artificial intelligence (AI) in revolutionizing the diagnostic accuracy of endoscopy. We discuss the historical use of dye-spray and virtual chromoendoscopy for the characterization of colorectal polyps, which are now being replaced with more advanced technologies. Specifically, we focus on the application of AI to create a “virtual biopsy” for the detection and characterization of colorectal polyps, with potential for replacing histopathological diagnosis. The incorporation of AI has the potential to provide an evolutionary learning system that aids in the diagnosis and management of patients with the best possible outcomes. A detailed analysis of the literature supporting AI-assisted diagnostic techniques for the detection and characterization of colorectal polyps, with a particular emphasis on AI’s characterization mechanism, is provided. The benefits of AI over traditional IEE techniques, including the reduction in human error in diagnosis, and its potential to provide an accurate diagnosis with similar accuracy to the gold standard are presented. However, the need for large-scale testing of AI in clinical practice and the importance of integrating patient data into the diagnostic process are acknowledged. In conclusion, the constant evolution of IEE technology and the potential for AI to revolutionize the field of endoscopy in the future are presented.

Blue light imagining (BLI) is an image-enhanced endoscopy system from Fujifilm and was demonstrated useful in improving real-time characterization and diagnosis of colorectal polyps. The aim of this study was to evaluate the performance characteristics of a single private practice gastroenterology center in differentiating between adenomatous and non-adenomatous polyps, using the BLI-based classification system (BLI Adenoma Serrated International Classification, BASIC). A total of 163 consecutive patients that underwent opportunistic screening colonoscopy were included. 3 entry-level gastroenterologists participated in the study, all having previously completed the BASIC elearning training. All detected diminutive rectosigmoid polyps were in real-time evaluated with BLI and assessed as adenomas or non-adenomas. Polyp features were characterized and a level of confidence (high or low) of the predicted diagnosis was specified for each polyp. All polyps were removed and sent for histopathology examination. 91 polyps for which an optical diagnosis was recorded were included. Polyp characterization was performed with high confidence in 70,32% cases. Overall accuracy for differentiation of adenomas was 89,01%. For high-confidence predicted adenomas accuracy was 90,62%. In our study we have demonstrated that entry-level gastroenterologists, after training in BASIC classification, can achieve good optical diagnosis parameters. [ABSTRACT FROM AUTHOR]

Gastrointestinal tumors, as one of the most common cancers worldwide, pose a significant threat to human health. In this context, the advent of fluorescence probe technology has offered new perspectives and methods for the diagnosis and surgical treatment of gastrointestinal tumors. However, there is currently a lack of systematic bibliometric analysis on the research concerning gastrointestinal cancer and fluorescence probes. This study retrieved and comprehensively analyzed 1816 documents from the Web of Science database using the Cite Space tool, exploring the spatiotemporal distribution, author and subject category distribution, research themes, and keywords in this field. As of February 3, 2024, a total of 1816 records were retrieved, encompassing nine document types. Original research papers dominated the dataset, accounting for 89.922 %, followed by review articles at 6.773 %. We conducted a comprehensive analysis from various perspectives including countries, authors, institutions, keywords, journals, and references. Our findings reveal a strengthening trend in research on gastrointestinal cancer and fluorescent probes since 2010, with primary focus on drug delivery, endoscopy techniques, and genomic hybridization. In recent years, there has been a growing interest in the design, application, and quantitative analysis techniques of fluorescent probes, marking a notable frontier in this field. Our research findings offer fundamental insights and aid in identifying potential collaborators for future endeavors in this area. [ABSTRACT FROM AUTHOR]

The sudden outbreak of the COVID-19 pandemic led to a huge concern globally because of the astounding increase in mortality rates worldwide. The medical imaging computed tomography technique, whole-genome sequencing, and electron microscopy are the methods generally used for the screening and identification of the SARS-CoV-2 virus. The main aim of this review is to emphasize the capabilities of various optical techniques to facilitate not only the timely and effective diagnosis of the virus but also to apply its potential toward therapy in the field of virology. This review paper categorizes the potential optical biosensors into the three main categories, spectroscopic-, nanomaterial-, and interferometry-based approaches, used for detecting various types of viruses, including SARS-CoV-2. Various classifications of spectroscopic techniques such as Raman spectroscopy, near-infrared spectroscopy, and fluorescence spectroscopy are discussed in the first part. The second aspect highlights advances related to nanomaterial-based optical biosensors, while the third part describes various optical interferometric biosensors used for the detection of viruses. The tremendous progress made by lab-on-a-chip technology in conjunction with smartphones for improving the point-of-care and portability features of the optical biosensors is also discussed. Finally, the review discusses the emergence of artificial intelligence and its applications in the field of bio-photonics and medical imaging for the diagnosis of COVID-19. The review concludes by providing insights into the future perspectives of optical techniques in the effective diagnosis of viruses.

Zebrafish is a well‐established animal model for developmental and disease studies. Its optical transparency at early developmental stages allows in vivo tissues visualization. Interaction of polarized light with these tissues provides information on their structure and properties. This approach is effective for muscle tissue analysis due to its birefringence. To enable real‐time Mueller‐matrix characterization of unanesthetized fish, we assembled a microscope for single‐shot Mueller‐matrix imaging. First, we performed a continuous observation of 48 species within the period of 2 to 96 hpf and measured temporal dependencies of the polarization features in different tissues. These measurements show that hatching was accompanied by a sharp change in the angle and degree of linearly polarized light after interaction with muscles. Second, we analyzed nine species with skeletal disorders and demonstrated that the spatial distribution of light depolarization features clearly indicated them. Obtained results demonstrated that real‐time Mueller‐matrix imaging is a powerful tool for label‐free monitoring zebrafish embryos. [ABSTRACT FROM AUTHOR]

Abstract Background Narrow-band imaging (NBI) highlights the surface structures and vessels of colorectal polyps and is useful for determining the polyp histology. The narrow-band imaging international colorectal endoscopic (NICE) classification is a diagnostic tool for determining colorectal polyp histology based on NBI without optical magnification. In this study, we aimed to investigate the value of each type of the NICE classification for determining colorectal polyp histology using endoscopy data accumulated in a clinical setting. Methods Endoscopy data for 534 colorectal polyps (316 patients) treated at our facility were retrospectively analyzed. First, we investigated the diagnostic performance of each type of the NICE classification for the optical diagnosis of colorectal polyp histology. The procedures were performed by experienced endoscopists using high-definition colonoscopy without optical magnification. Second, inter-observer and intra-observer agreements were assessed after providing experts and non-experts with a short lecture on the NICE classification. Using 50 fine NBI images of colorectal polyps without optical magnification, the inter-observer and intra-observer agreements between five experts and five non-experts were assessed. Results The sensitivity, specificity, and accuracy values were 86.0%, 99.6%, and 98.5% for NICE type 1 lesions; 99.2%, 85.2%, and 97.8% for NICE type 2 lesions; and 81.8%, 99.6%, and 99.3% for NICE type 3 lesions, respectively. The inter-observer and intra-observer agreements ranged from substantial to excellent for both experts and non-experts. Conclusions The NICE classification had good diagnostic ability in terms of determining the polyp histology and demonstrated a high level of reproducibility among experts and non-experts. Thus, the NICE classification is a useful clinical tool that can be used without optical magnification.

Background. Contemporary dental diagnosis should supplement clinical examination with instrumental diagnostic techniques. Raman spectroscopy has become widely adopted due to high spatial resolution, non-invasiveness, the lack of strict requirements and ease of sample preparation.Objectives. A qualitative assessment of enamel mineral and organic composition dynamics using Raman spectroscopy.Methods. Raman spectroscopy was used as primary research method. The trial bench consisted of a Shamrocksr-303i high-resolution digital spectrometer with built-in DV420A-OE cooled optical detector (spectral range 200–1200 nm), RPB-785 optic fibre scattering probe integrated with LuxxMaster LML-785.0RB-04 laser source with wavelength 785 nm.Software spectrum processing was performed with Wolfram Mathematica 9. Spectra were denoised with a median filter (5 points), the approximating line (fifth order polynomial) of autofluorescent component was determined in 700–2200 cm-1 range using an iterative algorithm and then subtracted to receive isolated Raman spectra.Linear discriminant analysis (LDA) of data was performed with the IBM SPSS Statistics package. Results. The assay included 28 teeth, with 14 extracted for orthodontic indications and 14 — for chronic periodontitis. Spectral dental enamel dynamics has been established in periodontal disease and after the in-office bleaching procedure. The evidence obtained can be applicable in dental practice to verify patients at risk of periodontal disease by interpreting the tooth enamel spectral properties, as well as prior to in-office bleaching.Conclusion. We demonstrate high efficiency of Raman spectroscopy for qualitative assessment of the mineral and organic enamel composition dynamics in various settings. Raman spectroscopy is confirmed effective and versatile in various aetiologies. It was successfully applied to diagnose periodontitis by changes in the organic and mineral enamel composition and evaluate enamel after in-office bleaching.

Artificial intelligence (AI)–based optical diagnosis systems (CADx) have been developed to allow pathology prediction of colorectal polyps during colonoscopies. However, CADx systems have not yet been validated for autonomous performance. Therefore, we conducted a trial comparing autonomous AI to AI-assisted human (AI-H) optical diagnosis. We performed a randomized noninferiority trial of patients undergoing elective colonoscopies at 1 academic institution. Patients were randomized into (1) autonomous AI-based CADx optical diagnosis of diminutive polyps without human input or (2) diagnosis by endoscopists who performed optical diagnosis of diminutive polyps after seeing the real-time CADx diagnosis. The primary outcome was accuracy in optical diagnosis in both arms using pathology as the gold standard. Secondary outcomes included agreement with pathology for surveillance intervals. A total of 467 patients were randomized (238 patients/158 polyps in the autonomous AI group and 229 patients/179 polyps in the AI-H group). Accuracy for optical diagnosis was 77.2% (95% confidence interval [CI], 69.7–84.7) in the autonomous AI group and 72.1% (95% CI, 65.5–78.6) in the AI-H group (P =.86). For high-confidence diagnoses, accuracy for optical diagnosis was 77.2% (95% CI, 69.7–84.7) in the autonomous AI group and 75.5% (95% CI, 67.9–82.0) in the AI-H group. Autonomous AI had statistically significantly higher agreement with pathology-based surveillance intervals compared to AI-H (91.5% [95% CI, 86.9–96.1] vs 82.1% [95% CI, 76.5–87.7]; P =.016). Autonomous AI-based optical diagnosis exhibits noninferior accuracy to endoscopist-based diagnosis. Both autonomous AI and AI-H exhibited relatively low accuracy for optical diagnosis; however, autonomous AI achieved higher agreement with pathology-based surveillance intervals. (ClinicalTrials.gov , Number NCT05236790) [Display omitted] In this study, autonomous artificial intelligence performed with high accuracy in diagnosing small (1–5-mm) colorectal polyps during colonoscopies and allowed follow-ups to be scheduled more correctly than when humans decided the final diagnosis. [ABSTRACT FROM AUTHOR]

Research on combustion characteristics can provide basic information and theoretical support for the design of insensitive propellant. This work aims to investigate the combustion characteristics of insensitive triple-base propellant. All propellants were prepared based on same triple-base propellant, but they were desensitized with the same desensitizer in different ways. The high-speed camera, spontaneous luminescence, NO, NH chemiluminescence, and OH-planar laser induction fluorescence (PLIF) methods were employed to capture the combustion flame and derive the distributions of important intermediates. Results show that ignition delay times of insensitive propellants are obviously longer. This indicated that the application of the desensitizer has a partly hindering effect on the early ignition stage. The combustion time of insensitive propellants is mostly similar, which means that the desensitizer has little influence on the intensity of actual combustion. The change in flame height and area of insensitive propellants over time indicated that the combustion progressivity of some insensitive propellants was more prominent, which means that the desensitizer concentration and desensitizing methods all affect the performance of insensitive propellant. The signal intensities of NO and NH show a negative correlation, indicating that a competitive relationship probably exists between the formation of NO and NH radicals during the reaction process. The high concentration of OH mainly locates outside NO, suggesting that there may be a transformation between NO and OH. The maximum signal intensity of NO and NH of different insensitive propellants confirmed that both the concentration of desensitizers and the desensitizing methods exhibit important effect on the reaction process.

Megavolt-class pulsed gas switches play an important role in large pulsers as transfer switches. This article analyzes the breakdown process and characteristics of a megavolt self-triggered preionized switch under 100-ns pulses based on the optical diagnosis. It is discovered that the triggering spark illumination targeting the main cathode or anode can separately preionize the main gap. The discharge channel is likely to first form between trigger electrodes and the main anode. Based on the above deduction, the streamer velocity is calculated to be $0.54 \times 10^{6}$ – $2.34 \times 10^{6}$ m/s, proportional to the electric field. Also, parameters of the empirical formula for calculating the gas heating time are amended. Influence mechanisms of the switch jitter are also studied. Under pulsed preionization mode, the trigger gap breaks down when the main gap electric field is high enough, and the switch jitter is mainly determined by the self-triggering jitter. Nonetheless, the self-triggering jitter can be partly offset during the breakdown process if the changing rate of mean reduced electric field $d(E/p)$ / dt at the self-triggering time is higher than 1.0 $1.0\left(\mathrm{kV} \cdot \mathrm{ns}^{-1} \cdot \mathrm{cm}^{-1} \cdot \mathrm{MPa}^{-1}\right)$. Under sustaining preionization mode, the trigger gap breaks down prematurely, and the continuous arcing driven by switch leak current preionizes the main gap. Therefore, the influence of the self-triggering jitter on the switch jitter can be eliminated. [ABSTRACT FROM AUTHOR]

The design of a supersonic-supersonic mixing layer facility was motivated by the need for a benchmark experimental platform to study the physical phenomena underlying supersonic mixing layers. The facility is an intermittent blowdown wind tunnel characterized by a two-stream design separated by a splitter plate in the middle of the nozzle. The splitter plate ends exactly at the start of the mixing layer test section. The Mach number of the primary stream is M1 = 3 for all nozzles and the secondary streams are M2 = 2, 2.5, and 2.9 to generate different convective Mach numbers of Mc = 0.25, 0.10, and 0.01, respectively. The facility was calibrated by pressure measurements to verify the Mach number and the pressure distribution in the streamwise direction. Large-eddy simulation (LES) was performed to illustrate a full view of the turbulent compressible mixing layer flow field and to compare this against the experimental data. Optical diagnosis measurements, i.e., femtosecond laser-induced electronic excitation tagging velocimetry (FLEET) for velocity measurement and focused laser differential interferometer (FLDI) for the density fluctuation, were also performed on the facility. [ABSTRACT FROM AUTHOR]

The purpose of this work is to investigate the effect of different initial temperatures on the combustion characteristics of RDX materials. In the experiments, the electric heating plate below the RDX samples was controlled so that the initial temperatures were set to be 298, 323, 373, 423, and 473 K (below the material melting point), respectively. Three optical diagnostic methods were employed to capture the ignition process, flame thermal radiation, and NO distribution in the flame at different conditions. The results show that the increase in initial temperature can improve the reaction rate, shorten the ignition delay time, and increase the flame combustion intensity and speed, because of the earlier evaporation and pyrolysis process in the RDX samples. Increasing the initial temperature also enhances the thermal effect of the flame, which is related to the generation and consumption of NO to a certain extent. [ABSTRACT FROM AUTHOR]

Breast tumors are among the most common types of tumors that can affect both genders. It may spread to the whole breast without any symptoms. Therefore, the early detection and accurate diagnosis of breast tumors are significantly important. Current approaches for breast cancer screening such as positron emission tomography (PET) and magnetic resonance imaging (MRI) have some limitations of being time and money-consuming. In addition, mammography screening is not recommended for women under forty. Consequently, optical techniques have been introduced as safe and functional alternatives. Diffuse optical imaging is a non-invasive imaging technique that utilizes near-infrared light to examine biological tissues based on measuring the optical transmission and/or reflection at various locations on the tissue surface. In this paper, we propose a modified arrangement between the laser source and the detectors for distinguishing tumors from normal breast tissue. A three-dimensional model of the normal human breast with three types of tumors is developed using a COMSOL simulation software based on the finite element solution of Helmholtz equation to estimate optical fluence distribution. The breast model consists of four layers: skin, fat, glandular, and muscle, where the tumor is included in the glandular layer. Different wavelengths were used to determine the most proper wavelength for the discrimination between the normal tissue and tumor. The obtained results were verified using the receiver operating characteristic (ROC) method. The resultant fluence images show different features between normal breast and breast with tumor especially using 600-nm incident laser as demonstrated by the obtained ROC curves. [ABSTRACT FROM AUTHOR]

In this study, the effect and mechanism of a dynamic axial magnetic field on a preconditioned single-wire Z-pinch were investigated experimentally and theoretically. Optical diagnostic methods, including shadowgraphy, interferometry, Faraday rotation, and Thomson scattering, have been used to measure the parameters of magnetized plasmas. Compression of the azimuthal and axial magnetic fields was observed, and the suppression of the plasma instability was recorded and analyzed. The results showed that an external axial magnetic field could reduce the plasma instability and non-uniformity, but prolong the implosion time and weaken the compression ratio. In the implosion process with an axial magnetic field, the plasma rotated at a speed similar to that of imploding, which could be regarded as a stabilization method. A simplified model of the diffusion and compression processes of a dynamic axial magnetic field was developed to investigate the conditions for maximizing the amplitude of the axial magnetic field. Subsequently, the snowplow model was used to calculate the effect of axial magnetic fields on the implosion process and energy conversion.

Background & Aims: Computer-aided diagnosis (CADx) assists endoscopists in differentiating between neoplastic and non-neoplastic polyps during colonoscopy. This study aimed to evaluate the impact of polyp location (proximal vs. distal colon) on the diagnostic performance of CADx for ≤5 mm polyps., Methods: We searched for studies evaluating the performance of real-time CADx alone (ie, independently of endoscopist judgement) for predicting the histology of colorectal polyps ≤5 mm. The primary endpoints were CADx sensitivity and specificity in the proximal and distal colon. Secondary outcomes were the negative predictive value (NPV), positive predictive value (PPV), and the accuracy of the CADx alone. Distal colon was limited to the rectum and sigmoid., Results: We included 11 studies for analysis with a total of 7782 polyps ≤5 mm. CADx specificity was significantly lower in the proximal colon compared with the distal colon (62% vs 85%; risk ratio (RR), 0.74; 95% confidence interval [CI], 0.72-0.84). Conversely, sensitivity was similar (89% vs 87%); RR, 1.00; 95% CI, 0.97-1.03). The NPV (64% vs 93%; RR, 0.71; 95% CI, 0.64-0.79) and accuracy (81% vs 86%; RR, 0.95; 95% CI, 0.91-0.99) were significantly lower in the proximal than distal colon, whereas PPV was higher in the proximal colon (87% vs 76%; RR, 1.11; 95% CI, 1.06-1.17)., Conclusion: The diagnostic performance of CADx for polyps in the proximal colon is inadequate, exhibiting significantly lower specificity compared with its performance for distal polyps. Although current CADx systems are suitable for use in the distal colon, they should not be employed for proximal polyps until more performant systems are developed specifically for these lesions., (Copyright © 2024 AGA Institute. Published by Elsevier Inc. All rights reserved.)

Sinus blockages are a common reason for physician visits, affecting one out of seven people in the United States, and often require medical treatment. Diagnosis in the primary care setting is challenging because symptom criteria (via detailed clinical history) plus objective imaging [computed tomography (CT) or endoscopy] are recommended. Unfortunately, neither option is routinely available in primary care. We previously demonstrated that low-cost near-infrared (NIR) transillumination correlates with the bulk findings of sinus opacity measured by CT. We have upgraded the technology, but questions of source optimization, anatomical influence, and detection limits remain. In order to begin addressing these questions, we have modeled NIR light propagation inside a three-dimensional adult human head constructed via CT images using a mesh-based Monte Carlo algorithm (MMCLAB). In this application, the sinus itself, which when healthy is a void region (e.g., nonscattering), is the region of interest. We characterize the changes in detected intensity due to clear (i.e., healthy) versus blocked sinuses and the effect of illumination patterns. We ran simulations for two clinical cases and compared simulations with measurements. The simulations presented herein serve as a proof of concept that this approach could be used to understand contrast mechanisms and limitations of NIR sinus imaging.

Diseases affecting myocardial tissues are currently a leading cause of death in developed nations. Fast and reliable techniques for analysing and understanding how tissues are affected by disease and respond to treatment are fundamental to combating the effects of heart disease. A 3D Mueller matrix method that reconstructs the linear and circular birefringence and dichroism parameters has been developed to image the biological structures in myocardial tissues. The required optical data is gathered using a Stokes polarimeter and then processed mathematically to recover the individual optical anisotropy parameters, expanding on existing 2D Mueller matrix implementations by combining with a digital holography approach. Changes in the different optical anisotropy parameters are rationalised with reference to the general tissue structure, such that the structures can be identified from the anisotropy distributions. The first to fourth order statistical moments characterising the distribution of the parameters of the optical anisotropy of the polycrystalline structure of the partially depolarising layer of tissues in different phase sections of their volumes are investigated and analysed. The third and fourth order statistical moments are found to be the most sensitive to changes in the phase and amplitude anisotropy. The possibility of forensic medical differentiation of death in cases of acute coronary insufficiency (ACI) and coronary heart disease (CHD) is considered as a diagnostic application. The optimal phase plane (θ∗=0.7rad) has been found, in which excellent differentiation accuracy is achieved ACI and CHD -Ac(ΔZ4(θ∗,ΦL,ΔL))=93.05%÷95.8%. A comparative analysis of the accuracy of the Mueller-matrix reconstruction of the parameters of the optical anisotropy of the myocardium in different phase planes (θ=0.9rad and θ=1.2rad), as well as the 2D Mueller-matrix reconstruction method was carried out. This work demonstrates that a 3D Mueller matrix method can be used to effectively analyse the optical anisotropy parameters of myocardial tissues with potential for definitive diagnostics in forensic medicine.

Background: Narrow-band imaging (NBI) highlights the surface structures and vessels of colorectal polyps and is useful for determining the polyp histology. The narrow-band imaging international colorectal endoscopic (NICE) classification is a diagnostic tool for determining colorectal polyp histology based on NBI without optical magnification. In this study, we aimed to investigate the value of each type of the NICE classification for determining colorectal polyp histology using endoscopy data accumulated in a clinical setting.Methods: Endoscopy data for 534 colorectal polyps (316 patients) treated at our facility were retrospectively analyzed. First, we investigated the diagnostic performance of each type of the NICE classification for the optical diagnosis of colorectal polyp histology. The procedures were performed by experienced endoscopists using high-definition colonoscopy without optical magnification. Second, inter-observer and intra-observer agreements were assessed after providing experts and non-experts with a short lecture on the NICE classification. Using 50 fine NBI images of colorectal polyps without optical magnification, the inter-observer and intra-observer agreements between five experts and five non-experts were assessed.Results: The sensitivity, specificity, and accuracy values were 86.0%, 99.6%, and 98.5% for NICE type 1 lesions; 99.2%, 85.2%, and 97.8% for NICE type 2 lesions; and 81.8%, 99.6%, and 99.3% for NICE type 3 lesions, respectively. The inter-observer and intra-observer agreements ranged from substantial to excellent for both experts and non-experts.Conclusions: The NICE classification had good diagnostic ability in terms of determining the polyp histology and demonstrated a high level of reproducibility among experts and non-experts. Thus, the NICE classification is a useful clinical tool that can be used without optical magnification. [ABSTRACT FROM AUTHOR]

Biomass is the only carbon-neutral fuel, the development and utilization of biomass are crucial for achieving carbon neutrality. However, the combustion of biomass in boilers is often unstable due to the heterogeneity of biomass raw materials, leading to a decrease in combustion efficiency and an increase in pollutant emissions. Continuous online monitoring is essential for the safe, stable and efficient operation of boilers. Traditional measurement methods typically rely off-line analysis to study the kinetics of biomass oxidation and pyrolysis. These methods struggle to accurately capture transient parameters during combustion due to changes in reaction pathways and oxidant products. Optical diagnosis is a non-contact, instantaneous and efficient method that can achieve in-situ, online and rapid measurement of multiple parameters. This technology has been extensively applied by researchers in the field of biomass combustion diagnosis. The current status and applications of online measurement methods for biomass ignition/combustion behavior and soot generation are reviewed. The problems and development trends of existing optical diagnostic technologies for biomass combustion are also been proposed. The review suggests that the future development of more diverse and effective optical diagnostic techniques, as well as the combination of various diagnostic technologies, is beneficial for comprehensively analyzing the key issues in biomass combustion, so as to realize the efficient utilization of biomass. [Display omitted] • The application of optical diagnosis in biomass combustion has been emphasized. • Highlights challenges in combustion, underscoring the need for advanced diagnostics. • The integrated optical technology for efficient analysis is advocated. [ABSTRACT FROM AUTHOR]

Background: Narrow-band imaging (NBI) allows “in vivo” classification of colorectal polyps. Objectives: We evaluated the optical diagnosis by nonexpert community-based endoscopists in routine clinical practice, the impact of training, and whether the endoscopists could achieve the threshold for the “do not resect” policy. Methods: This was an observational study performed in two periods (P1 and P2). Endoscopists had no prior experience in NBI in P1 and applied the technique on a daily basis for 1 year before participation in P2. Lesions were classified by applying the NBI International Colorectal Endoscopic (NICE) and Workgroup serrAted polypS and Polyposis (WASP) classifications, simultaneously. Results: A total of 290 polyps were analyzed. The overall accuracy of optical diagnosis was 0.75 (95% CI 0.68–0.81) in P1, with an increase to 0.82 (95% CI 0.73–0.89) in P2 (p = 0.260). The accuracy of the NICE/WASP classifications to differentiate adenomatous from nonadenomatous histology was 0.78 (95% CI 0.72–0.84) in P1 and 0.86 (95% CI 0.77–0.92) in P2 (p = 0.164); assignments made with a high confidence level achieved statistical significance (13% improvement, 95% CI 3–22%; p = 0.022). The negative predictive value for adenomatous histology of diminutive rectosigmoid polyps was 81% (95% CI 64–93%) and 80% (95% CI 59–93%) in P1 and P2, respectively. Conclusions: Nonexpert endoscopists achieved moderate accuracy for real-time optical diagnosis of colorectal lesions with the NICE/WASP classifications. The overall performance of the endoscopists improved after sustained use of optical diagnosis, but did not achieve the standards for the implementation of the “do not resect” strategy.

The design of a supersonic-supersonic mixing layer facility was motivated by the need for a benchmark experimental platform to study the physical phenomena underlying supersonic mixing layers. The facility is an intermittent blowdown wind tunnel characterized by a two-stream design separated by a splitter plate in the middle of the nozzle. The splitter plate ends exactly at the start of the mixing layer test section. The Mach number of the primary stream is M1 = 3 for all nozzles and the secondary streams are M2 = 2, 2.5, and 2.9 to generate different convective Mach numbers of Mc = 0.25, 0.10, and 0.01, respectively. The facility was calibrated by pressure measurements to verify the Mach number and the pressure distribution in the streamwise direction. Large-eddy simulation (LES) was performed to illustrate a full view of the turbulent compressible mixing layer flow field and to compare this against the experimental data. Optical diagnosis measurements, i.e., femtosecond laser-induced electronic excitation tagging velocimetry (FLEET) for velocity measurement and focused laser differential interferometer (FLDI) for the density fluctuation, were also performed on the facility.

Background: Our previous studies have demonstrated that Raman spectroscopy could be used for skin cancer detection with good sensitivity and specificity. The objective of this study is to determine if skin cancer detection can be further improved by combining deep neural networks and Raman spectroscopy., Patients and Methods: Raman spectra of 731 skin lesions were included in this study, containing 340 cancerous and precancerous lesions (melanoma, basal cell carcinoma, squamous cell carcinoma and actinic keratosis) and 391 benign lesions (melanocytic nevus and seborrheic keratosis). One-dimensional convolutional neural networks (1D-CNN) were developed for Raman spectral classification. The stratified samples were divided randomly into training (70%), validation (10%) and test set (20%), and were repeated 56 times using parallel computing. Different data augmentation strategies were implemented for the training dataset, including added random noise, spectral shift, spectral combination and artificially synthesized Raman spectra using one-dimensional generative adversarial networks (1D-GAN). The area under the receiver operating characteristic curve (ROC AUC) was used as a measure of the diagnostic performance. Conventional machine learning approaches, including partial least squares for discriminant analysis (PLS-DA), principal component and linear discriminant analysis (PC-LDA), support vector machine (SVM), and logistic regression (LR) were evaluated for comparison with the same data splitting scheme as the 1D-CNN., Results: The ROC AUC of the test dataset based on the original training spectra were 0.886±0.022 (1D-CNN), 0.870±0.028 (PLS-DA), 0.875±0.033 (PC-LDA), 0.864±0.027 (SVM), and 0.525±0.045 (LR), which were improved to 0.909±0.021 (1D-CNN), 0.899±0.022 (PLS-DA), 0.895±0.022 (PC-LDA), 0.901±0.020 (SVM), and 0.897±0.021 (LR) respectively after augmentation of the training dataset (p<0.0001, Wilcoxon test). Paired analyses of 1D-CNN with conventional machine learning approaches showed that 1D-CNN had a 1-3% improvement (p<0.001, Wilcoxon test)., Conclusions: Data augmentation not only improved the performance of both deep neural networks and conventional machine learning techniques by 2-4%, but also improved the performance of the models on spectra with higher noise or spectral shifting. Convolutional neural networks slightly outperformed conventional machine learning approaches for skin cancer detection by Raman spectroscopy., Competing Interests: The authors and the BC Cancer Agency hold several patents for Raman spectroscopy that have been licensed to Vita Imaging Inc San Jose, California., (Copyright © 2024 Zhao, Lui, Kalia, Lee and Zeng.)

Optical diagnosis during colorectal cancer screening is instrumental in deciding whether or not to resect colorectal lesions, choose the appropriate technique and to properly communicate with the pathologist. The latter is even more important when it comes to serrated lesions with the latest WHO classification justifying a pathology diagnosis of a serrated lesion with a minimum criterion of characteristic findings in just one crypt, which may only be detectable when adequate sectioning and scrutinization is performed. Here, we present a unique case of comparatively small rectal lesions with typical endoscopic findings warranting a diagnosis of a serrated lesion (open pit pattern) and adenoma (valley sign).

The purpose of this work is to investigate the effect of different initial temperatures on the combustion characteristics of RDX materials. In the experiments, the electric heating plate below the RDX samples was controlled so that the initial temperatures were set to be 298, 323, 373, 423, and 473 K (below the material melting point), respectively. Three optical diagnostic methods were employed to capture the ignition process, flame thermal radiation, and NO distribution in the flame at different conditions. The results show that the increase in initial temperature can improve the reaction rate, shorten the ignition delay time, and increase the flame combustion intensity and speed, because of the earlier evaporation and pyrolysis process in the RDX samples. Increasing the initial temperature also enhances the thermal effect of the flame, which is related to the generation and consumption of NO to a certain extent.