Advances in optical gastrointestinal endoscopy: a technical review

Engineering of an EPHA2-Targeted Monobody for the Detection of Colorectal Cancer

BACKGROUND/AIM

Colorectal cancer (CRC) is the third most common cancer worldwide, and is second only to lung cancer with respect to cancer-related deaths. Noninvasive molecular imaging using established markers is a new emerging method to diagnose CRC. The human ephrin receptor family type-A 2 (hEPHA2) oncoprotein is overexpressed at the early, but not late, stages of CRC. Previously, we reported development of an E1 monobody that is specific for hEPHA2-expressing cancer cells both in vitro and in vivo. Herein, we investigated the ability of the E1 monobody to detect hEPHA2 expressing colorectal tumors in a mouse model, as well as in CRC tissue.

MATERIALS AND METHODS

The expression of hEPHA2 on the surface of CRC cells was analyzed by western blotting and flow cytometry. The targeting efficacy of the E1 monobody for CRC cells was examined by flow cytometry, and immunofluorescence staining. E1 conjugated to the Renilla luciferase variant 8 (Rluc8) reporter protein was used for in vivo imaging in mice. Additionally, an enhanced green fluorescence protein (EGFP) conjugated E1 monobody was used to check the ability of the E1 monobody to target CRC tissue.

RESULTS

The E1 monobody bound efficiently to hEPHA2-expressing CRC cell lines, and E1 conjugated to the Rluc8 reporter protein targeted tumor tissues in mice transplanted with HCT116 CRC tumor cells. Finally, E1-EGFP stained tumor tissues from human CRC patients, showing a pattern similar to that of an anti-hEPHA2 antibody.

CONCLUSION

The E1 monobody has utility as an EPHA2 targeting agent for the detection of CRC.

Investigation of factors that may potentially affect anxiety in patients undergoing esophagogastroduodenoscopy and evaluation of sedation effect

BACKGROUND

As with any other invasive procedure, esophagogastroduodenoscopy (EGD) may lead to considerable anxiety in patients. This study aimed to investigate and compare the effects of sedated and non-sedated procedures on anxiety in patients undergoing EGD and to better recognize patient groups at risk for anxiety.

METHODS

In this prospective and 2-armed designed study, demographic data, including age, gender, comorbidities, height, weight, body mass index (BMI), and educational background, were collected. In this study, the Beck Anxiety Inventory (BAI) was administered to each patient before they were brought to the endoscopy unit. Subsequently, each patient who underwent EGD was telephoned on the seventh day after the procedure and the BAI was administered a second time.

RESULTS

Women population had higher pre-EGD and post-EGD BAI scores compared to men. No significant correlation was observed between educational background and BAI scores. Possible correlations between age, BMI, Charlson comorbidity index (CCI), and BAI scores were examined. There was a weak correlation between BMI and pre-EGD and post-EGD BAI scores. A strong and positive correlation was observed between the pre-EGD BAI score and post-EGD BAI and difference in BAI scores between groups (ΔBAI).

CONCLUSION

Endoscopic procedures may cause anxiety in patients as with all other invasive procedures. Patients' compliance with the procedure and having a lower level of anxiety are very significant for diagnostic and, if necessary, therapeutic success. In this study, the patient gender was evaluated as a predictor of anxiety level, whereas educational background was not a predictor.

In Vivo Microwave-Induced Thermoacoustic Endoscopy for Colorectal Tumor Detection in Deep Tissue

Optical endoscopy, as one of the common clinical diagnostic modalities, provides irreplaceable advantages in the diagnosis and treatment of internal organs. However, the approach is limited to the characterization of superficial tissues due to the strong optical scattering properties of tissue. In this work, a microwave-induced thermoacoustic (TA) endoscope (MTAE) was developed and evaluated. The MTAE system integrated a homemade monopole sleeve antenna (diameter = 7 mm) for providing homogenized pulsed microwave irradiation to induce a TA signal in the colorectal cavity and a side-viewing focus ultrasonic transducer (diameter = 3 mm) for detecting the TA signal in the ultrasonic spectrum to construct the image. Our MTAE, system combined microwave excitation and acoustic detection; produced images with dielectric contrast and high spatial resolution at several centimeters deep in soft tissues, overcome the current limitations of the imaging depth of optical endoscopy and mechanical wave-based imaging contrast of ultrasound endoscopy, and had the ability to extract complete features for deep location tumors that could be infiltrating and invading adjacent structures. The practical feasibility of the MTAE system was evaluated i n vivo with rabbits having colorectal tumors. The results demonstrated that colorectal tumor progression could be visualized from the changes in electromagnetic parameters of the tissue via MTAE, showing its potential clinical application.

Deep-learning-based image super-resolution of an end-expandable optical fiber probe for application in esophageal cancer diagnostics

Significance

Endoscopic screening for esophageal cancer (EC) may enable early cancer diagnosis and treatment. While optical microendoscopic technology has shown promise in improving specificity, the limited field of view (< 1    mm ) significantly reduces the ability to survey large areas efficiently in EC screening.

Aim

To improve the efficiency of endoscopic screening, we propose a novel concept of end-expandable endoscopic optical fiber probe for larger field of visualization and for the first time evaluate a deep-learning-based image super-resolution (DL-SR) method to overcome the issue of limited sampling capability.

Approach

To demonstrate feasibility of the end-expandable optical fiber probe, DL-SR was applied on simulated low-resolution microendoscopic images to generate super-resolved (SR) ones. Varying the degradation model of image data acquisition, we identified the optimal parameters for optical fiber probe prototyping. The proposed screening method was validated with a human pathology reading study.

Results

For various degradation parameters considered, the DL-SR method demonstrated different levels of improvement of traditional measures of image quality. The endoscopists' interpretations of the SR images were comparable to those performed on the high-resolution ones.

Conclusions

This work suggests avenues for development of DL-SR-enabled sparse image reconstruction to improve high-yield EC screening and similar clinical applications.

What makes a medical intervention invasive?

The classification of medical interventions as either invasive or non-invasive is commonly regarded to be morally important. On the most commonly endorsed account of invasiveness, a medical intervention is invasive if and only if it involves either breaking the skin ('incision') or inserting an object into the body ('insertion'). Building on recent discussions of the concept of invasiveness, we show that this standard account fails to capture three aspects of existing usage of the concept of invasiveness in relation to medical interventions-namely, (1) usage implying that invasiveness comes in degrees, (2) that the invasiveness of an intervention can depend on the characteristics of the salient alternative interventions, and (3) that medical interventions can be invasive in non-physical ways. We then offer the beginnings of a revised account that, we argue, is able to capture a wider range of existing usage. Central to our account is a distinction between two properties: basic invasiveness and threshold invasiveness We end by assessing what the standard account gets right, and what more needs to be done to complete our schematic account.

Research progress of exosomes in the angiogenesis of digestive system tumour

Malignant tumours of the digestive system cover a wide range of diseases that affect the health of people to a large extent. Angiogenesis is indispensable in the development, and metastasis of tumours, mainly in two ways: occupation or formation. Vessels can provide nutrients, oxygen, and growth factors for tumours to encourage growth and metastasis, so cancer progression depends on simultaneous angiogenesis. Recently, exosomes have been proven to participate in the angiogenesis of tumours. They influence angiogenesis by binding to tyrosine kinase receptors (VEGFR)-1, VEGFR-2, and VEGFR-3 with different affinities, regulating Yap-VEGF pathway, Akt pathway or other signaling pathway. Additionally, exosomes are potential therapeutic vectors that can deliver many types of cargoes to different cells. In this review, we summarize the roles of exosomes in the angiogenesis of digestive system tumours and highlight the clinical application prospects, directly used as targers or delivery vehicles, in antiangiogenic therapy.

A Drosophila heart optical coherence microscopy dataset for automatic video segmentation

The heart of the fruit fly, Drosophila melanogaster, is a particularly suitable model for cardiac studies. Optical coherence microscopy (OCM) captures in vivo cross-sectional videos of the beating Drosophila heart for cardiac function quantification. To analyze those large-size multi-frame OCM recordings, human labelling has been employed, leading to low efficiency and poor reproducibility. Here, we introduce a robust and accurate automated Drosophila heart segmentation algorithm, called FlyNet 2.0+, which utilizes a long short-term memory (LSTM) convolutional neural network to leverage time series information in the videos, ensuring consistent, high-quality segmentation. We present a dataset of 213 Drosophila heart videos, equivalent to 604,000 cross-sectional images, containing all developmental stages and a wide range of beating patterns, including faster and slower than normal beating, arrhythmic beating, and periods of heart stop to capture these heart dynamics. Each video contains a corresponding ground truth mask. We expect this unique large dataset of the beating Drosophila heart in vivo will enable new deep learning approaches to efficiently characterize heart function to advance cardiac research.

Endoluminal Procedures and Devices for Esophageal Tract Investigation: A Critical Review

Diseases of the esophageal tract represent a heterogeneous class of pathological conditions for which diagnostic paradigms continue to emerge. In the last few decades, innovative diagnostic devices have been developed, and several attempts have been made to advance and standardize diagnostic algorithms to be compliant with medical procedures. To the best of our knowledge, a comprehensive review of the procedures and available technologies to investigate the esophageal tract was missing in the literature. Therefore, the proposed review aims to provide a comprehensive analysis of available endoluminal technologies and procedures to investigate esophagus health conditions. The proposed systematic review was performed using PubMed, Scopus, and Web of Science databases. Studies have been divided into categories based on the type of evaluation and measurement that the investigated technology provides. In detail, three main categories have been identified, i.e., endoluminal technologies for the (i) morphological, (ii) bio-mechanical, and (iii) electro-chemical evaluation of the esophagus.

A multifaceted comparative analysis of image and video technologies in gastrointestinal endoscope and their clinical applications

This paper presents a comprehensive exploration of endoscopic technologies in clinical applications across seven tables, each focusing on a unique facet of the medical field. The discourse begins with a detailed analysis of pediatric endoscopes, highlighting their diagnostic capabilities in various conditions. It then delves into the specifications and applications of globally recognized capsule endoscopy devices. Additionally, the paper incorporates an analysis of advanced imaging techniques, such as Narrow Band Imaging (NBI), Flexible Spectral Imaging Color Enhancement (FICE), and i-scan, which are increasingly being integrated into ultrathin gastrointestinal (GI) endoscopes. Factors like technological capabilities, light source, camera technology, and computational constraints are evaluated to understand their compatibility with these advanced imaging techniques, each offering unique advantages and challenges in clinical settings. NBI, for instance, is lauded for its user-friendly, real-time enhanced imaging capabilities, making it effective for early detection of conditions like colorectal cancer and Barrett's esophagus. Conversely, FICE and i-scan offer high customizability and are compatible with a broader range of endoscope models. The paper further delves into innovative advances in movement control for Nasojejunal (NJ) feeding tube endoscopy, elucidating the potential of AI and other novel strategies. A review of the technologies and methodologies enhancing endoscopic procedure control and diagnostic precision follows, emphasizing image and video technologies in pediatric endoscopy, capsule endoscopes, ultrathin endoscopes, and their clinical applications. Finally, a comparative analysis of leading real-time video monitoring endoscopes in clinical practices underscores the continuous advancements in the field of endoscopy, ensuring improved diagnostics and precision in surgical procedures. Collectively, the comparative analysis presented in this paper highlights the remarkable diversity and continuous evolution of endoscopic technologies, underlining their crucial role in diagnosing and treating an array of medical conditions, thereby fostering advancements in patient care and clinical outcomes.

Application of near-infrared fluorescence imaging in theranostics of gastrointestinal tumors

Gastrointestinal cancers have become an important cause of cancer-related death in humans. Improving the early diagnosis rate of gastrointestinal tumors and improving the effect of surgical treatment can significantly improve the survival rate of patients. The conventional diagnostic method is high-definition white-light endoscopy, which often leads to missed diagnosis. For surgical treatment, intraoperative tumor localization and post-operative anastomotic state evaluation play important roles in the effect of surgical treatment. As a new imaging method, near-infrared fluorescence imaging (NIRFI) has its unique advantages in the diagnosis and auxiliary surgical treatment of gastrointestinal tumors due to its high sensitivity and the ability to image deep tissues. In this review, we focus on the latest advances of NIRFI technology applied in early diagnosis of gastrointestinal tumors, identification of tumor margins, identification of lymph nodes, and assessment of anastomotic leakage. In addition, we summarize the advances of NIRFI systems such as macro imaging and micro imaging systems, and also clearly describe the application process of NIRFI from system to clinical application, and look into the prospect of NIRFI applied in the theranostics of gastrointestinal tumors.

Optical imaging for early detection of cervical cancer: state of the art and perspectives

Significance

Cervical cancer is one of the major causes of death in females worldwide. HPV infection is the key cause of uncontrolled cell growth leading to cervical cancer. About 90% of cervical cancer is preventable because of the slow progression of the disease, giving a window of about 10 years for the precancerous lesion to be recognized and treated.

Aim

The present challenges for cervical cancer diagnosis are interobserver variation in clinicians' interpretation of visual inspection with acetic acid/visual inspection with Lugol's iodine, cost of cytology-based screening, and lack of skilled clinicians. The optical modalities can assist in qualitatively and quantitatively analyzing the tissue to differentiate between cancerous and surrounding normal tissues.

Approach

This work is on the recent advances in optical techniques for cervical cancer diagnosis, which promise to overcome the above-listed challenges faced by present screening techniques.

Results

The optical modalities provide substantial measurable information in addition to the conventional colposcopy and Pap smear test to clinically aid the diagnosis.

Conclusions

Recent optical modalities on fluorescence, multispectral imaging, polarization-sensitive imaging, microendoscopy, Raman spectroscopy, especially with the portable design and assisted by artificial intelligence, have a significant scope in the diagnosis of premalignant cervical cancer in future.

Artificial Intelligence-Aided Optical Imaging for Cancer Theranostics

The use of artificial intelligence (AI) to assist biomedical imaging have demonstrated its high accuracy and high efficiency in medical decision-making for individualized cancer medicine. In particular, optical imaging methods are able to visualize both the structural and functional information of tumors tissues with high contrast, low cost, and noninvasive property. However, no systematic work has been performed to inspect the recent advances on AI-aided optical imaging for cancer theranostics. In this review, we demonstrated how AI can guide optical imaging methods to improve the accuracy on tumor detection, automated analysis and prediction of its histopathological section, its monitoring during treatment, and its prognosis by using computer vision, deep learning and natural language processing. By contrast, the optical imaging techniques involved mainly consisted of various tomography and microscopy imaging methods such as optical endoscopy imaging, optical coherence tomography, photoacoustic imaging, diffuse optical tomography, optical microscopy imaging, Raman imaging, and fluorescent imaging. Meanwhile, existing problems, possible challenges and future prospects for AI-aided optical imaging protocol for cancer theranostics were also discussed. It is expected that the present work can open a new avenue for precision oncology by using AI and optical imaging tools.

Role of Confocal Laser Endomicroscopy in Early Detection of Upper Gastrointestinal Malignancy in High Risk Patients

BACKGROUND

Upper gastrointestinal malignancies are a major global health burden. Early diagnosis of upper gastrointestinal premalignant and malignant lesions is crucial for improving prognosis and reducing morbidity and mortality. The purpose of this study was to investigate the diagnostic accuracy of confocal laser endomicroscopy (CLE) in detecting upper gastrointestinal premalignant and early malignant lesions in high-risk patients, as well as diagnosing patients with inconclusive white light endoscopy (WLE) and histopathology results.

METHODS

It was a cross-sectional study that included ninety (n = 90) high-risk patients with inconclusive diagnoses of upper gastrointestinal lesions on WLE and WLE-based biopsy histopathology. These patients underwent CLE, and the definitive diagnosis was confirmed using CLE and CLE-target biopsy histopathology. Diagnostic accuracy was determined by comparing the sensitivity, specificity, predictive values, and accuracy between the procedures.

RESULT

The mean patient age was 47.43 ± 11.18 years. CLE and target biopsy confirmed that 30 (33.3%) patients had normal histology, while 60 (66.7%) patients were diagnosed with gastritis, gastric intestinal metaplasia, high-grade dysplasia, adenocarcinoma, Barrett's esophagus, and squamous cell carcinoma of the esophagus. The results of CLE were superior to those of WLE in terms of diagnostic parameters. Additionally, CLE demonstrated nearly similar results in sensitivity (98.33%), specificity (100%), positive predictive value (100%), negative predictive value (96.77%), and accuracy (98.89%) when compared to CLE-target biopsy.

CONCLUSION

CLE showed higher diagnostic accuracy in differentiating normal, premalignant and malignant lesions. It effectively diagnosed patients who initially had inconclusive WLE and/or biopsy results. Furthermore, early detection of upper gastrointestinal premalignant or malignant lesions may improve prognosis and reduce morbidity and mortality.

Hybrid Models for Endoscopy Image Analysis for Early Detection of Gastrointestinal Diseases Based on Fused Features

The gastrointestinal system contains the upper and lower gastrointestinal tracts. The main tasks of the gastrointestinal system are to break down food and convert it into essential elements that the body can benefit from and expel waste in the form of feces. If any organ is affected, it does not work well, which affects the body. Many gastrointestinal diseases, such as infections, ulcers, and benign and malignant tumors, threaten human life. Endoscopy techniques are the gold standard for detecting infected parts within the organs of the gastrointestinal tract. Endoscopy techniques produce videos that are converted into thousands of frames that show the disease's characteristics in only some frames. Therefore, this represents a challenge for doctors because it is a tedious task that requires time, effort, and experience. Computer-assisted automated diagnostic techniques help achieve effective diagnosis to help doctors identify the disease and give the patient the appropriate treatment. In this study, many efficient methodologies for analyzing endoscopy images for diagnosing gastrointestinal diseases were developed for the Kvasir dataset. The Kvasir dataset was classified by three pre-trained models: GoogLeNet, MobileNet, and DenseNet121. The images were optimized, and the gradient vector flow (GVF) algorithm was applied to segment the regions of interest (ROIs), isolating them from healthy regions and saving the endoscopy images as Kvasir-ROI. The Kvasir-ROI dataset was classified by the three pre-trained GoogLeNet, MobileNet, and DenseNet121 models. Hybrid methodologies (CNN-FFNN and CNN-XGBoost) were developed based on the GVF algorithm and achieved promising results for diagnosing disease based on endoscopy images of gastroenterology. The last methodology is based on fused CNN models and their classification by FFNN and XGBoost networks. The hybrid methodology based on the fused CNN features, called GoogLeNet-MobileNet-DenseNet121-XGBoost, achieved an AUC of 97.54%, accuracy of 97.25%, sensitivity of 96.86%, precision of 97.25%, and specificity of 99.48%.

Research trends in endoscopic applications in early gastric cancer: A bibliometric analysis of studies published from 2012 to 2022

Background

Endoscopy is the optimal method of diagnosing and treating early gastric cancer (EGC), and it is therefore important to keep up with the rapid development of endoscopic applications in EGC. This study utilized bibliometric analysis to describe the development, current research progress, hotspots, and emerging trends in this field.

Methods

We retrieved publications about endoscopic applications in EGC from 2012 to 2022 from Web of Science™ (Clarivate™, Philadelphia, PA, USA) Core Collection (WoSCC). We mainly used CiteSpace (version 6.1.R3) and VOSviewer (version 1.6.18) to perform the collaboration network analysis, co-cited analysis, co-occurrence analysis, cluster analysis, and burst detection.

Results

A total of 1,333 publications were included. Overall, both the number of publications and the average number of citations per document per year increased annually. Among the 52 countries/regions that were included, Japan contributed the most in terms of publications, citations, and H-index, followed by the Republic of Korea and China. The National Cancer Center, based in both Japan and the Republic of Korea, ranked first among institutions in terms of number of publications, citation impact, and the average number of citations. Yong Chan Lee was the most productive author, and Ichiro Oda had the highest citation impact. In terms of cited authors, Gotoda Takuji had both the highest citation impact and the highest centrality. Among journals, Surgical Endoscopy and Other Interventional Techniques had the most publications, and Gastric Cancer had the highest citation impact and H-index. Among all publications and cited references, a paper by Smyth E C et al., followed by one by Gotoda T et al., had the highest citation impact. Using keywords co-occurrence and cluster analysis, 1,652 author keywords were categorized into 26 clusters, and we then divided the clusters into six groups. The largest and newest clusters were endoscopic submucosal dissection and artificial intelligence (AI), respectively.

Conclusions

Over the last decade, research into endoscopic applications in EGC has gradually increased. Japan and the Republic of Korea have contributed the most, but research in this field in China, from an initially low base, is developing at a striking speed. However, a lack of collaboration among countries, institutions, and authors, is common, and this should be addressed in future. The main focus of research in this field (i.e., the largest cluster) is endoscopic submucosal dissection, and the topic at the frontier (i.e., the newest cluster) is AI. Future research should focus on the application of AI in endoscopy, and its implications for the clinical diagnosis and treatment of EGC.

An explainable artificial intelligence system for diagnosing Helicobacter Pylori infection under endoscopy: a case-control study

Background

Changes in gastric mucosa caused by Helicobacter pylori (H. pylori) infection affect the observation of early gastric cancer under endoscopy. Although previous researches reported that computer-aided diagnosis (CAD) systems have great potential in the diagnosis of H. pylori infection, their explainability remains a challenge.

Objective

We aim to develop an explainable artificial intelligence system for diagnosing H. pylori infection (EADHI) and giving diagnostic basis under endoscopy.

Design

A case-control study.

Methods

We retrospectively obtained 47,239 images from 1826 patients between 1 June 2020 and 31 July 2021 at Renmin Hospital of Wuhan University for the development of EADHI. EADHI was developed based on feature extraction combining ResNet-50 and long short-term memory networks. Nine endoscopic features were used for H. pylori infection. EADHI's performance was evaluated and compared to that of endoscopists. An external test was conducted in Wenzhou Central Hospital to evaluate its robustness. A gradient-boosting decision tree model was used to examine the contributions of different mucosal features for diagnosing H. pylori infection.

Results

The system extracted mucosal features for diagnosing H. pylori infection with an overall accuracy of 78.3% [95% confidence interval (CI): 76.2-80.3]. The accuracy of EADHI for diagnosing H. pylori infection (91.1%, 95% CI: 85.7-94.6) was significantly higher than that of endoscopists (by 15.5%, 95% CI: 9.7-21.3) in internal test. And it showed a good accuracy of 91.9% (95% CI: 85.6-95.7) in external test. Mucosal edema was the most important diagnostic feature for H. pylori positive, while regular arrangement of collecting venules was the most important H. pylori negative feature.

Conclusion

The EADHI discerns H. pylori gastritis with high accuracy and good explainability, which may improve the trust and acceptability of endoscopists on CADs.

Plain language summary

An explainable AI system for Helicobacter pylori with good diagnostic performance Helicobacter pylori (H. pylori) is the main risk factor for gastric cancer (GC), and changes in gastric mucosa caused by H. pylori infection affect the observation of early GC under endoscopy. Therefore, it is necessary to identify H. pylori infection under endoscopy. Although previous research showed that computer-aided diagnosis (CAD) systems have great potential in H. pylori infection diagnosis, their generalization and explainability are still a challenge. Herein, we constructed an explainable artificial intelligence system for diagnosing H. pylori infection (EADHI) using images by case. In this study, we integrated ResNet-50 and long short-term memory (LSTM) networks into the system. Among them, ResNet50 is used for feature extraction, LSTM is used to classify H. pylori infection status based on these features. Furthermore, we added the information of mucosal features in each case when training the system so that EADHI could identify and output which mucosal features are contained in a case. In our study, EADHI achieved good diagnostic performance with an accuracy of 91.1% [95% confidence interval (CI): 85.7-94.6], which was significantly higher than that of endoscopists (by 15.5%, 95% CI: 9.7-21.3%) in internal test. In addition, it showed a good diagnostic accuracy of 91.9% (95% CI: 85.6-95.7) in external tests. The EADHI discerns H. pylori gastritis with high accuracy and good explainability, which may improve the trust and acceptability of endoscopists on CADs. However, we only used data from a single center to develop EADHI, and it was not effective in identifying past H. pylori infection. Future, multicenter, prospective studies are needed to demonstrate the clinical applicability of CADs.

Future of Endoscopy in Inflammatory Bowel Diseases (IBDs)

Gastrointestinal (GI) endoscopy has transformed over the years in scope, safety, accuracy, acceptability, and cost effectiveness of the clinical practice. There has been a reduction in the superiority of the endoscopic devices as innovations have taken place and increased the diagnostic values with certain limitations. There are particular difficulties in striking a balance between the development of new technology and the device's acceptance. The wide use of endoscopy for investigating GI lesions and diagnosis has led to an increase in more advanced methods and their broad application. It can simultaneously diagnose pre-malignant and malignant lesions, and newer interventions have made the biopsy specimen uptake possible. In this review article, we focus on the more recent roles, indications, applications, and usage of the innovative methods of endoscopy.

Non-optical polyp-based resect and discard strategy: A prospective clinical study

BACKGROUND

Post-polypectomy surveillance intervals are currently determined based on pathology results.

AIM

To evaluate a polyp-based resect and discard model that assigns surveillance intervals based solely on polyp number and size.

METHODS

Patients undergoing elective colonoscopies at the Montreal University Medical Center were enrolled prospectively. The polyp-based strategy was used to assign the next surveillance interval using polyp size and number. Surveillance intervals were also assigned using optical diagnosis for small polyps (< 10 mm). The primary outcome was surveillance interval agreement between the polyp-based model, optical diagnosis, and the pathology-based reference standard using the 2020 United States Multi-Society Task Force guidelines. Secondary outcomes included the proportion of reduction in required histopathology evaluations and proportion of immediate post-colonoscopy recommendations provided to patients.

RESULTS

Of 944 patients (mean age 62.6 years, 49.3% male, 933 polyps) were enrolled. The surveillance interval agreement for the polyp-based strategy was 98.0% [95% confidence interval (CI): 0.97-0.99] compared with pathology-based assignment. Optical diagnosis-based intervals achieved 95.8% (95%CI: 0.94-0.97) agreement with pathology. When using the polyp-based strategy and optical diagnosis, the need for pathology assessment was reduced by 87.8% and 70.6%, respectively. The polyp-based strategy provided 93.7% of patients with immediate surveillance interval recommendations vs 76.1% for optical diagnosis.

CONCLUSION

The polyp-based strategy achieved almost perfect surveillance interval agreement compared with pathology-based assignments, significantly reduced the number of required pathology evaluations, and provided most patients with immediate surveillance interval recommendations.

In vivo microscopy as an adjunctive tool to guide detection, diagnosis, and treatment

SIGNIFICANCE

There have been numerous academic and commercial efforts to develop high-resolution in vivo microscopes for a variety of clinical use cases, including early disease detection and surgical guidance. While many high-profile studies, commercialized products, and publications have resulted from these efforts, mainstream clinical adoption has been relatively slow other than for a few clinical applications (e.g., dermatology).

AIM

Here, our goals are threefold: (1) to introduce and motivate the need for in vivo microscopy (IVM) as an adjunctive tool for clinical detection, diagnosis, and treatment, (2) to discuss the key translational challenges facing the field, and (3) to propose best practices and recommendations to facilitate clinical adoption.

APPROACH

We will provide concrete examples from various clinical domains, such as dermatology, oral/gastrointestinal oncology, and neurosurgery, to reinforce our observations and recommendations.

RESULTS

While the incremental improvement and optimization of IVM technologies should and will continue to occur, future translational efforts would benefit from the following: (1) integrating clinical and industry partners upfront to define and maintain a compelling value proposition, (2) identifying multimodal/multiscale imaging workflows, which are necessary for success in most clinical scenarios, and (3) developing effective artificial intelligence tools for clinical decision support, tempered by a realization that complete adoption of such tools will be slow.

CONCLUSIONS

The convergence of imaging modalities, academic-industry-clinician partnerships, and new computational capabilities has the potential to catalyze rapid progress and adoption of IVM in the next few decades.

The development and clinical application of microscopic endoscopy for in vivo optical biopsies: Endocytoscopy and confocal laser endomicroscopy

Endoscopies are crucial for detecting and diagnosing diseases in gastroenterology, pulmonology, urology, and other fields. To accurately diagnose diseases, sample biopsies are indispensable and are currently considered the gold standard. However, random 4-quadrant biopsies have sampling errors and time delays. To provide intraoperative real-time microscopic images of suspicious lesions, microscopic endoscopy for in vivo optical biopsy has been developed, including endocytoscopy and confocal laser endomicroscopy. This article reviews recent advances in technology and clinical applications, as well as their shortcomings and future directions.

Innovative Diagnostic Endoscopy in Inflammatory Bowel Diseases: From High-Definition to Molecular Endoscopy

High-definition endoscopy is one essential step in the initial diagnosis of inflammatory bowel disease (IBD) characterizing the extent and severity of inflammation, as well as discriminating ulcerative colitis (UC) from Crohn's disease (CD). Following general recommendations and national guidelines, individual risk stratification should define the appropriate surveillance strategy, biopsy protocol and frequency of endoscopies. Beside high-definition videoendoscopy the application of dyes applied via a spraying catheter is of additional diagnostic value with a higher detection rate of intraepithelial neoplasia (IEN). Virtual chromoendoscopy techniques (NBI, FICE, I-scan, BLI) should not be recommended as a single surveillance strategy in IBD, although newer data suggest a higher comparability to dye-based chromoendoscopy than previously assumed. First results of oral methylene blue formulation are promising for improving the acceptance rate of classical chromoendoscopy. Confocal laser endomicroscopy (CLE) is still an experimental but highly innovative endoscopic procedure with the potential to contribute to the detection of dysplastic lesions. Molecular endoscopy in IBD has taken application of CLE to a higher level and allows topical application of labeled probes, mainly antibodies, against specific target structures expressed in the tissue to predict response or failure to biological therapies. First pre-clinical and in vivo data from label-free multiphoton microscopy (MPM) are now available to characterize mucosal and submucosal inflammation on endoscopy in more detail. These new techniques now have opened the door to individualized and highly specific molecular imaging in IBD in the future and pave the path to personalized medicine approaches. The quality of evidence was stated according to the Oxford Center of evidence-based medicine (March 2009). For this review a Medline search up to January 2021 was performed using the words “inflammatory bowel disease,” “ulcerative colitis,” “crohn's disease,” “chromoendoscopy,” “high-definition endoscopy,” “confocal laser endomicroscopy,” “confocal laser microscopy,” “molecular imaging,” “multiphoton microscopy.”

Lifestyles, genetics, and future perspectives on gastric cancer in east Asian populations

The prevalence of gastric cancer (GC) differs among regions worldwide, with the highest occurrence in east Asia. Thus, its etiology, with respect to ethnic background, environmental factors, and lifestyles, is also thought to differ essentially. In addition, etiology of GC is speculated to be changing due to the recent decrease in the Helicobacter pylori (H. pylori) infection in Japan. State-of-the-art somatic/germline cancer genomics has clarified the etiologies of gastric carcinogenesis. In this review article, we summarize past and present milestones in our understanding of GC achieved through genomic approaches, including a recent report that revealed higher-than-expected frequencies of GCs attributed to east Asian-specific germline variants in ALDH2 or CDH1 in combination with lifestyles. Based on this updated knowledge, we also discuss the possible impact of and high-risk approaches for GCs in the upcoming "H. pylori-negative era."

Plasmonic optical fiber for bacteria manipulation-characterization and visualization of accumulation behavior under plasmo-thermal trapping

In this article, we demonstrate a plasmo-thermal bacterial accumulation effect using a miniature plasmonic optical fiber. The combined action of far-field convection and a near-field trapping force (referred to as thermophoresis)-induced by highly localized plasmonic heating-enabled the large-area accumulation of Escherichia coli. The estimated thermophoretic trapping force agreed with previous reports, and we applied speckle imaging analysis to map the in-plane bacterial velocities over large areas. This is the first time that spatial mapping of bacterial velocities has been achieved in this setting. Thus, this analysis technique provides opportunities to better understand this phenomenon and to drive it towards in vivo applications.