A Comprehensive Study on the digestive Endoscopic Technique and Narrow-Band Imaging for Early Gastric Cancer Screening

Objective:To explore the implementation of gastrointestinal endoscopy technology and endoscopic narrow-band imaging(NBI)in the early screening of gastric cancer and to observe and study their application effects.Methods:During the period from March 2023 to August 2023,312 patients who received gastroscopy in the Kunming Guandu District People’s Hospital were selected,and they underwent both conventional gastroscopy and endoscopic NBI,with clinicopathological tissue biopsy serving as the gold standard.The application value for early screening of gastric cancer was observed and analyzed.Results:The scoring data showed that the clarity of gastric mucosal glandular tube structure,microvascular structure clarity,and lesion contour scoring data of conventional gastroscopy were lower than those of the NBI technology(P<0.05).The screening rate of pathological biopsy in 312 patients was 18.59%(58 cases).Conventional gastroscopy showed a screening rate of 11.53%(36 cases),while NBI technology examined a screening rate of 17.63%(55 cases),and the two-by-two comparison of the screening rate data of the three groups was not statistically significant(P>0.05).The sensitivity,specificity,accuracy,positive predictive value,and negative predictive value of conventional gastroscopy appeared to be lower than those of NBI technology(P<0.05).Conclusion:In the early screening of gastric cancer,endoscopic NBI technology can be applied to patients.Compared with conventional gastroscopy,it provides a clearer visualization of the structure of the gastric mucosal glandular structure and microvascular structure,with a certain screening rate.Additionally,its sensitivity,specificity,accuracy,positive predictive value,and negative predictive value are higher,demonstrating outstanding effectiveness.

Magnetic imaging-assisted colonoscopy vs conventional colonoscopy: A randomized controlled trial

AIM: To compare magnetic imaging-assisted colonoscopy (MIC) with conventional colonoscopy (CC).

Advancements in Barrett's esophagus detection:The role of artificial intelligence and its implications

Artificial intelligence(AI)is making significant strides in revolutionizing the detection of Barrett's esophagus(BE),a precursor to esophageal adenocarcinoma.In the research article by Tsai et al,researchers utilized endoscopic images to train an AI model,challenging the traditional distinction between endoscopic and histological BE.This approach yielded remarkable results,with the AI system achieving an accuracy of 94.37%,sensitivity of 94.29%,and specificity of 94.44%.The study's extensive dataset enhances the AI model's practicality,offering valuable support to endoscopists by minimizing unnecessary biopsies.However,questions about the applicability to different endoscopic systems remain.The study underscores the potential of AI in BE detection while highlighting the need for further research to assess its adaptability to diverse clinical settings.

Endoscopic imaging of Barrett's esophagus

The incidence of esophageal adenocarcinoma (EAC) has dramatically increased in the United States as well as Western European countries. The majority of esophageal adenocarcinomas arise from a backdrop of Barrett&rsquo;s esophagus (BE), a premalignant lesion that can lead to dysplasia and cancer. Because of the increased risk of EAC, GI society guidelines recommend endoscopic surveillance of patients with BE. The emphasis on early detection of dysplasia in BE through surveillance endoscopy has led to the development of advanced endoscopic imaging technologies. These techniques have the potential to both improve mucosal visualization and characterization and to detect small mucosal abnormalities which are difficult to identify with standard endoscopy. This review summarizes the advanced imaging technologies used in evaluation of BE.

Diagnostic performance of narrow-band imaging international colorectal endoscopic and Japanese narrow-band imaging expert team classification systems for colorectal cancer and precancerous lesions

BACKGROUND In recent years,two new narrow-band imaging(NBI)classifications have been proposed:The NBI international colorectal endoscopic(NICE)classification and Japanese NBI expert team(JNET)classification.Most validation studies of the two new NBI classifications were conducted in classification setting units by experienced endoscopists,and the application of use in different centers among endoscopists with different endoscopy skills remains unknown.AIM To evaluate clinical application and possible problems of NICE and JNET classification for the differential diagnosis of colorectal cancer and precancerous lesions.METHODS Six endoscopists with varying levels of experience participated in this study.Eighty-seven consecutive patients with a total of 125 lesions were photographed during non-magnifying conventional white-light colonoscopy,non-magnifying NBI,and magnifying NBI.The three groups of endoscopic pictures of each lesion were evaluated by the six endoscopists in randomized order using the NICE and JENT classifications separately.Then we calculated the six endoscopists’sensitivity,specificity,accuracy,positive predictive value,and negative predictive value for each category of the two classifications.RESULTS The sensitivity,specificity,and accuracy of JNET classification type 1 and 3 were similar to NICE classification type 1 and 3 in both the highly experienced endoscopist(HEE)and less-experienced endoscopist(LEE)groups.The specificity of JNET classification type 1 and 3 and NICE classification type 3 in both the HEE and LEE groups was>95%,and the overall interobserver agreement was good in both groups.The sensitivity of NICE classification type 3 lesions for diagnosis of SM-d carcinoma in the HEE group was significantly superior to that in the LEE group(91.7%vs 83.3%;P=0.042).The sensitivity of JNET classification type 2B lesions for the diagnosis of high-grade dysplasia or superficial submucosal invasive carcinoma in the HEE and LEE groups was 53.8%and 51.3%,respectively.Compared with other types of JNET classification,the diagnostic ability of type 2B was the weakest.CONCLUSION The treatment strategy of the two classification type 1 and 3 lesions can be based on the results of endoscopic examination.JNET type 2B lesions need further examination.

Unsupervised Oral Endoscope Image Stitching Algorithm

Oral endoscope image stitching algorithm is studied to obtain wide-field oral images through regis-tration and stitching,which is of great significance for auxiliary diagnosis.Compared with natural images,oral images have lower textures and fewer features.However,traditional feature-based image stitching methods rely heavily on feature extraction quality,often showing an unsatisfactory performance when stitching images with few features.Moreover,due to the hand-held shooting,there are large depth and perspective disparities between the captured images,which also pose a challenge to image stitching.To overcome the above problems,we propose an unsupervised oral endoscope image stitching algorithm based on the extraction of overlapping regions and the loss of deep features.In the registration stage,we extract the overlapping region of the input images by sketching polygon intersection for feature points screening and estimate homography from coarse to fine on a three-layer feature pyramid structure.Moreover,we calculate loss using deep features instead of pixel values to emphasize the importance of depth disparities in homography estimation.Finally,we reconstruct the stitched images from feature to pixel,which can eliminate artifacts caused by large parallax.Our method is compared with both feature-based and previous deep-based methods on the UDIS-D dataset and our oral endoscopy image dataset.The experimental results show that our algorithm can achieve higher homography estimation accuracy,and better visual quality,and can be effectively applied to oral endoscope image stitching.

Endoscopic diagnosis and treatment of gastric dysplasia and early cancer:Current evidence and what the future may hold

Gastric cancer accounts for a significant proportion of worldwide cancer-related morbidity and mortality.The well documented precancerous cascade provides an opportunity for clinicians to detect and treat gastric cancers at an endoscopically curable stage.In high prevalence regions such as Japan and Korea,this has led to the implementation of population screening programs.However,guidelines remain ambiguous in lower prevalence regions.In recent years,there have been many advances in the endoscopic diagnosis and treatment of early gastric cancer and precancerous lesions.More advanced endoscopic imaging has led to improved detection and characterization of gastric lesions as well as superior accuracy for delineation of margins prior to resection.In addition,promising early data on artificial intelligence in gastroscopy suggests a future role for this technology in maximizing the yield of advanced endoscopic imaging.Data on endoscopic resection(ER)are particularly robust in Japan and Korea,with high rates of curative ER and markedly reduced procedural morbidity.However,there is a shortage of data in other regions to support the applicability of protocols from these high prevalence countries.Future advances in endoscopic therapeutics will likely lead to further expansion of the current indications for ER,as both technology and proceduralist expertise continue to grow.

Pencil-beam scanning catheter for intracoronary optical coherence tomography

Current gradient-index(GRIN)lens based proximal-driven intracoronary optical coherence tomography(ICOCT)probes consist of a spacer and a GRIN lens with large gradient constant.This design provides great flexibility to control beam profiles,but the spacer length should be well controlled to obtain desired beam profiles and thus it sets an obstacle in mass catheter fabrication.Besides,although GRIN lens with large gradient constant can provide tight focus spot,it has short depth of focus and fast-expanded beam which leads to poor lateral resolution for deep tissue.In this paper,a type of spacer-removed probe is demonstrated with a small gradient constant GRIN lens.This design simplifies the fabrica-tion process and is suitable for mass production.The output beam of the catheter is a narrow nearly collimated light beam,referred to as pencil beam here.The full width at half maximum beam size varies from 35.1μm to 75.3μm in air over 3-mm range.Probe design principles are elaborated with probe/catheter fabrication and performance test.The in vivo imaging of the catheter was verified by a clinical ICOCT system.Those results prove that this novel pencil-beam scanning catheter is potentially a good choice for ICOCT systems.

Ultrasonic signal detection based on Fabry–Perot cavity sensor

Acoustic/ultrasonic sensors are devices that can convert mechanical energy into electrical signals.The Fabry–Perot cavity is processed on the end face of the double-clad fiber by a two-photon three-dimensional lithography machine.In this study,the outer diameter of the core cladding was 250μm,the diameter of the core was 9μm,and the microcavity sensing unit was only 30μm.It could measure ultrasonic signals with high precision.The characteristics of the proposed ultrasonic sensor were investigated,and its feasibility was proven through experiments.Its design has a small size and can replace a larger ultrasonic detector device for photoacoustic signal detection.The sensor is applicable to the field of biomedical information technology,including medical diagnosis,photoacoustic endoscopy,and photoacoustic imaging.

Semi-supervised Long-tail Endoscopic Image Classification

Objective To explore the semi-supervised learning(SSL) algorithm for long-tail endoscopic image classification with limited annotations.Method We explored semi-supervised long-tail endoscopic image classification in HyperKvasir,the largest gastrointestinal public dataset with 23 diverse classes.Semi-supervised learning algorithm FixMatch was applied based on consistency regularization and pseudo-labeling.After splitting the training dataset and the test dataset at a ratio of 4:1,we sampled 20%,50%,and 100% labeled training data to test the classification with limited annotations.Results The classification performance was evaluated by micro-average and macro-average evaluation metrics,with the Mathews correlation coefficient(MCC) as the overall evaluation.SSL algorithm improved the classification performance,with MCC increasing from 0.8761 to 0.8850,from 0.8983 to 0.8994,and from 0.9075 to 0.9095 with 20%,50%,and 100% ratio of labeled training data,respectively.With a 20% ratio of labeled training data,SSL improved both the micro-average and macro-average classification performance;while for the ratio of 50% and 100%,SSL improved the micro-average performance but hurt macro-average performance.Through analyzing the confusion matrix and labeling bias in each class,we found that the pseudo-based SSL algorithm exacerbated the classifier’ s preference for the head class,resulting in improved performance in the head class and degenerated performance in the tail class.Conclusion SSL can improve the classification performance for semi-supervised long-tail endoscopic image classification,especially when the labeled data is extremely limited,which may benefit the building of assisted diagnosis systems for low-volume hospitals.However,the pseudo-labeling strategy may amplify the effect of class imbalance,which hurts the classification performance for the tail class.

Asymptomatic pancreatic lesions: New insights and clinical implications

Despite great efforts in experimental and clinical research, the prognosis of pancreatic cancer (PC) has not changed significantly for decades. Detection of pre-invasive lesions or early-stage PC with small resectable cancers in asymptomatic individuals remains one of the most promising approaches to substantially improve the overall outcome of PC. Therefore, screening programs have been proposed to identify curable lesions especially in individuals with a familial or genetic predisposition for PC. In this regard, Canto et al recently contributed an important article comparing computed tomography, magnetic resonance imaging, and endoscopic ultrasound for the screening of 216 asymptomatic high-risk individuals (HRI). Pancreatic lesions were detected in 92 of 216 asymptomatic HRI (42.6%). The high diagnostic yield in this study raises several questions that need to be answered of which two will be discussed in detail in this commentary: First: which imaging test should be performed? Second and most importantly: what are we doing with incidentally detected pancreatic lesions? Which ones can be observed and which ones need to be resected?

Artificial intelligence assisted endocytoscopy: A novel eye in endoscopy

Over the past few years,emerging new approaches in endoscopic imaging technologies facilitate a high-quality assessment of lesions found in the gastrointestinal(GI)tract.Endocytoscopy(EC),as a novel tool in endoscopy,aids the more accurate evaluation of superficial mucosal surface.This review article aims to represent the most relevant information related to the latest EC technology and its clinical application in the lower GI tract diagnostic.We discuss EC-computer-aided diagnosis capability to differentiate between non-neoplastic and neoplastic lesion that offers a closer look to in-vivo assessment and diagnosis of cancerous tissue.Nevertheless,artificial-assisted EC diagnostics could also be employed with benefits in patients with inflammatory bowel disease(IBD)by accurately highlighting the presence of mucosal injury.In our review we included those studies comprising data about colonoscopy with narrow banding imaging and computer-aided diagnosis,as well as EC.Last but not least,artificial-assisted EC facilitates in-vivo diagnosis of the lower GI tract and may,in the future,remodel the field of in-vivo endoscopic diagnosis of colorectal lesions,representing another step towards the so-called optical biopsy.

Experimental assessment of a 3-D plenoptic endoscopic imaging system

All endoscopic imaging system using a plenoptic technique to reconstruct 3-D information is demonstrated and analyzed in this Letter. The proposed setup integrates a clinical surgical endoscope with a plenoptic camera to achieve a depth accuracy error of about 1 mm and a precision error of about 2 mm, within a 25 mm×25 mm field of view, operating at 11 frames per second.

Multispectral light scattering endoscopic imaging of esophageal precancer

Esophageal adenocarcinoma is the most rapidly growing cancer in America.Although the prognosis after diagnosis is unfavorable,the chance of a successful outcome increases tremendously if detected early while the lesion is still dysplastic.Unfortunately,the present standard-of-care,endoscopic surveillance,has major limitations,since dysplasia is invisible,often focal,and systematic biopsies typically sample less than one percent of the esophageal lining and therefore easily miss malignancies.To solve this problem we developed a multispectral light scattering endoscopic imaging system.It surveys the entire esophageal lining and accurately detects subcellular dysplastic changes.The system combines light scattering spectroscopy,which detects and identifies invisible dysplastic sites by analyzing light scattered from epithelial cells,with rapid scanning of the entire esophageal lining using a collimated broadband light beam delivered by an endoscopically compatible fiber optic probe.Here we report the results of the first comprehensive multispectral imaging study,conducted as part of routine endoscopic procedures performed on patients with suspected dysplasia.In a double-blind study that characterized the system’s ability to serve as a screening tool,55 out of 57 patients were diagnosed correctly.In addition,a smaller double-blind comparison of the multispectral data in 24 patients with subsequent pathology at locations where 411 biopsies were collected yielded an accuracy of 90%in detecting individual locations of dysplasia,demonstrating the capability of this method to serve as a guide for biopsy.