Establishment of Standards for the Referral of Large Non-Pedunculated Colorectal Polyps: An International Expert Consensus Using a Modified Delphi Process.

BACKGROUND AND AIMS: Resection of colorectal polyps has been shown to decrease the incidence and mortality of colorectal cancer. Large non-pedunculated colorectal polyps are often referred to expert centres for endoscopic resection, which requires relevant information to be conveyed to the therapeutic endoscopist to allow for triage and planning of resection technique. The primary objective of our study was to establish minimum expected standards for the referral of LNPCP for potential ER. METHODS: A Delphi methodology was employed to establish consensus on minimum expected standards for the referral of large colorectal polyps among a panel of international endoscopy experts. The expert panel was recruited through purposive sampling, and three rounds of surveys were conducted to achieve consensus, with quantitative and qualitative data analysed for each round. RESULTS: A total of 24 international experts from diverse continents participated in the Delphi study, resulting in consensus on 19 statements related to the referral of large colorectal polyps. The identified factors, including patient demographics, relevant medications, lesion factors, photodocumentation and the presence of a tattoo, were deemed important for conveying the necessary information to therapeutic endoscopists. The mean scores for the statements ranged from 7.04 to 9.29 out of 10, with high percentages of experts considering most statements as a very high priority. Subgroup analysis by continent revealed some variations in consensus rates among experts from different regions. CONCLUSION: The identified consensus statements can aid in improving the triage and planning of resection techniques for large colorectal polyps, ultimately contributing to the reduction of colorectal cancer incidence and mortality.

Texture and Color Enhancement Imaging Improves Colonic Adenoma Detection: A Multicenter Randomized Controlled Trial.

The global burden of colorectal cancer is expected to increase more than 60% by 2030; however, compelling evidence now shows that the implementation of population screening programs in developed countries has led to a substantial reduction in incidence and mortality.1,2 Despite this, patients continue to develop preventable colorectal cancers, in part because of high rates of interval colon cancer diagnosed after screening or surveillance colonoscopies.3.

Prevalence and factors associated with probable obstructive sleep apnea among patients with hypertension in two primary care clinics in Miri, Sarawak, Malaysia.

PURPOSE: Obstructive sleep apnea (OSA) has been increasingly recognized as an important factor contributing to medical morbidity and mortality. It was reported that more than half of the population with hypertension had OSA. Limited studies have been done on assessing OSA in hypertensive patients. This study aimed to determine the prevalence, socio-demographic characteristics, and factors associated with probable OSA in hypertensive patients in primary care clinics in Sarawak. METHODS: A cross-sectional study was carried out using a systematic random sampling method in hypertensive patients who attended two government primary care clinics in Sarawak. The STOP-Bang questionnaire was used to screen for OSA, and social-demographic data was captured with a questionnaire. Multiple logistic regressions were used to examine the determinants of the OSA. RESULTS: A total of 410 patients were enrolled in this study. The mean age of study population patients was 56.4 years, with more than half being female. The mean blood pressure was 136/82. The prevalence of probable OSA among patients with hypertension was 54.4%. According to multiple logistic regression analyses, smoking (odds ratio [OR] 14.37, 95% confidence interval [CI] 3.335-61.947), retirees (OR 3.20, 95% CI 1.675-6.113), and being Chinese (OR 2.21, 95% CI 1.262-3.863) had a significant positive association with probable OSA. CONCLUSIONS: Because of the high prevalence of probable OSA among patients with hypertension, primary care physicians should be more vigilant in identifying hypertensive patients with OSA risk. Early detection and intervention would reduce disease complications and healthcare costs.

Precision endoscopy in the era of climate change and sustainability.

Global warming caused by increased greenhouse gas (GHG) emissions has a direct impact on human health. Gastrointestinal (GI) endoscopy contributes significantly to GHG emissions due to energy consumption, reprocessing of endoscopes and accessories, production of equipment, safe disposal of biohazardous waste, and travel by patients. Moreover, GHGs are also generated in histopathology through tissue processing and the production of biopsy specimen bottles. The reduction in unnecessary surveillance endoscopies and biopsies is a practical approach to decrease GHG emissions without affecting disease outcomes. This narrative review explores the role of precision medicine in GI endoscopy, such as image-enhanced endoscopy and artificial intelligence, with a focus on decreasing unnecessary endoscopic procedures and biopsies in the surveillance and diagnosis of premalignant lesions in the esophagus, stomach, and colon. This review offers strategies to minimize unnecessary endoscopic procedures and biopsies, decrease GHG emissions, and maintain high-quality patient care, thereby contributing to sustainable healthcare practices.

The Role of Artificial Intelligence in Colorectal Cancer Screening: Lesion Detection and Lesion Characterization.

Colorectal cancer remains a leading cause of cancer-related morbidity and mortality worldwide, despite the widespread uptake of population surveillance strategies. This is in part due to the persistent development of 'interval colorectal cancers', where patients develop colorectal cancer despite appropriate surveillance intervals, implying pre-malignant polyps were not resected at a prior colonoscopy. Multiple techniques have been developed to improve the sensitivity and accuracy of lesion detection and characterisation in an effort to improve the efficacy of colorectal cancer screening, thereby reducing the incidence of interval colorectal cancers. This article presents a comprehensive review of the transformative role of artificial intelligence (AI), which has recently emerged as one such solution for improving the quality of screening and surveillance colonoscopy. Firstly, AI-driven algorithms demonstrate remarkable potential in addressing the challenge of overlooked polyps, particularly polyp subtypes infamous for escaping human detection because of their inconspicuous appearance. Secondly, AI empowers gastroenterologists without exhaustive training in advanced mucosal imaging to characterise polyps with accuracy similar to that of expert interventionalists, reducing the dependence on pathologic evaluation and guiding appropriate resection techniques or referrals for more complex resections. AI in colonoscopy holds the potential to advance the detection and characterisation of polyps, addressing current limitations and improving patient outcomes. The integration of AI technologies into routine colonoscopy represents a promising step towards more effective colorectal cancer screening and prevention.

Self-supervised pseudo multi-class pre-training for unsupervised anomaly detection and segmentation in medical images.

Unsupervised anomaly detection (UAD) methods are trained with normal (or healthy) images only, but during testing, they are able to classify normal and abnormal (or disease) images. UAD is an important medical image analysis (MIA) method to be applied in disease screening problems because the training sets available for those problems usually contain only normal images. However, the exclusive reliance on normal images may result in the learning of ineffective low-dimensional image representations that are not sensitive enough to detect and segment unseen abnormal lesions of varying size, appearance, and shape. Pre-training UAD methods with self-supervised learning, based on computer vision techniques, can mitigate this challenge, but they are sub-optimal because they do not explore domain knowledge for designing the pretext tasks, and their contrastive learning losses do not try to cluster the normal training images, which may result in a sparse distribution of normal images that is ineffective for anomaly detection. In this paper, we propose a new self-supervised pre-training method for MIA UAD applications, named Pseudo Multi-class Strong Augmentation via Contrastive Learning (PMSACL). PMSACL consists of a novel optimisation method that contrasts a normal image class from multiple pseudo classes of synthesised abnormal images, with each class enforced to form a dense cluster in the feature space. In the experiments, we show that our PMSACL pre-training improves the accuracy of SOTA UAD methods on many MIA benchmarks using colonoscopy, fundus screening and Covid-19 Chest X-ray datasets.

The Surface Morphology of Large Nonpedunculated Colonic Polyps Predicts Synchronous Large Lesions.

BACKGROUND & AIMS: Large (≥20 mm) nonpedunculated colorectal polyps (LNPCPs) may have synchronous LNPCPs in up to 18% of cases. The nature of this relationship has not been investigated. We aimed to examine the relationship between individual LNPCP characteristics and synchronous colonic LNPCPs. METHODS: Consecutive patients referred for resection of LNPCPs over 130 months until March 2022 were enrolled. Serrated lesions and mixed granularity LNPCPs were excluded from analysis. Patients with multiple LNPCPs resected were identified, and the largest was labelled as dominant. The primary outcome was the identification of individual lesion characteristics associated with the presence of synchronous LNPCPs. RESULTS: There were 3149 of 3381 patients (93.1%) who had a single LNPCP. In 232 (6.9%) a synchronous lesion was detected. Solitary lesions had a median size of 35 mm with a predominant Paris 0-IIa morphology (42.9%) and right colon location (59.5%). In patients with ≥2 LNPCPs, the dominant lesion had a median size of 40 mm, Paris 0-IIa (47.6%) morphology, and right colon location (65.9%). In this group, 35.8% of dominant LNPCPs were non-granular compared with 18.7% in the solitary LNPCP cohort. Non-granular (NG)-LNPCPs were more likely to demonstrate synchronous disease, with left colon NG-LNPCPs demonstrating greater risk (odds ratio, 4.78; 95% confidence interval, 2.95-7.73) than right colon NG-LNPCPs (odds ratio, 1.99; 95% confidence interval, 1.39-2.86). CONCLUSIONS: We found that 6.9% of LNPCPs have synchronous disease, with NG-LNPCPs demonstrating a greater than 4-fold increased risk. With post-colonoscopy interval cancers exceeding 5%, endoscopists must be cognizant of an individual's LNPCP phenotype when examining the colon at both index procedure and surveillance. CLINICALTRIALS: gov, NCT01368289; NCT02000141; NCT02198729.

A Review on Spike and Recovery Method in Analytical Method Development and Validation.

In multidisciplinary science, Analytical approaches based on spike and recovery (SAR) play a substantial role in analytical testing. The spike and recovery method is an important technique for analyzing and accessing the accuracy of analytical methods. The goal of this review seeks to provide clarity on the role of SAR methods in the forensic science discipline. Recent literature has been searched from numerous databases like Google, Web of Sciences, Scopus, PubMed, Google Scholar, and SciFinder. Websites like Science Direct are critically explored to gather scientific reports related to SAR utility. This review discusses the applications and current role of the SAR methods in Forensic Toxicology. It is suggested as one of the major parameters in the validation of the analytical method. SAR methodology is extremely important for the identification and quantitation of analytes in the sample matrix. Moreover, the extension of SAR methods to any scientific discipline is equally important for quality assurance. All relevant processes like method development and its optimization, quality control, and assurance rely on SAR-based studies. However, the method requires better apprehension and needs to be utilized using standard guidelines.

Diagnostic Accuracy of Artificial Intelligence (AI) to Detect Early Neoplasia in Barrett's Esophagus: A Non-comparative Systematic Review and Meta-Analysis.

Background and Aims: Artificial Intelligence (AI) is rapidly evolving in gastrointestinal (GI) endoscopy. We undertook a systematic review and meta-analysis to assess the performance of AI at detecting early Barrett's neoplasia. Methods: We searched Medline, EMBASE and Cochrane Central Register of controlled trials database from inception to the 28th Jan 2022 to identify studies on the detection of early Barrett's neoplasia using AI. Study quality was assessed using Quality Assessment of Diagnostic Accuracy Studies - 2 (QUADAS-2). A random-effects model was used to calculate pooled sensitivity, specificity, and diagnostics odds ratio (DOR). Forest plots and a summary of the receiving operating characteristics (SROC) curves displayed the outcomes. Heterogeneity was determined by I 2, Tau2 statistics and p-value. The funnel plots and Deek's test were used to assess publication bias. Results: Twelve studies comprising of 1,361 patients (utilizing 532,328 images on which the various AI models were trained) were used. The SROC was 0.94 (95% CI: 0.92-0.96). Pooled sensitivity, specificity and diagnostic odds ratio were 90.3% (95% CI: 87.1-92.7%), 84.4% (95% CI: 80.2-87.9%) and 48.1 (95% CI: 28.4-81.5), respectively. Subgroup analysis of AI models trained only on white light endoscopy was similar with pooled sensitivity and specificity of 91.2% (95% CI: 85.7-94.7%) and 85.1% (95% CI: 81.6%-88.1%), respectively. Conclusions: AI is highly accurate at detecting early Barrett's neoplasia and validated for patients with at least high-grade dysplasia and above. Further well-designed prospective randomized controlled studies of all histopathological subtypes of early Barrett's neoplasia are needed to confirm these findings further.

Comparative Snake Venom Analysis for Facilitating Wildlife Forensics: A Pilot Study.

Confirm and authentic identification of species is required for the implementation of wildlife laws in cases of illegal trafficking of snake venoms. Illegally trafficked snake venom might be misidentified with other drugs of abuse, and sometimes, the species of venom-yielding snake cannot be verified. Snake venoms from medically important snake species, Naja naja and Daboia russelii, were procured from Irula Snake Catcher's Society, Tamil Nadu, India. Comparative analyses of both venoms were carried out using SDS-PAGE, LC-MS/MS, ICP-MS, and mtDNA analysis. The protein concentration of Naja naja and Daboia russelii venoms was 76.1% and 83.9%, respectively. SDS analysis showed a distinct banding pattern of both venoms. LC-MS/MS results showed proteins and toxins from 12 to 14 protein families in Naja naja and Daboia russelii venoms. Elemental analysis using ICP-MS showed a different profile of some elements in both venoms. mtDNA analysis of venoms using universal primers against Cyt b gene showed homology with sequence of Naja naja and Daboia russelii genes. The study proposed a template of various conventional and advanced molecular and instrumental techniques with their pros and cons. The template can be used by forensic science laboratories for detection, screening, and confirmatory analysis of suspected venoms of snakes. Clubbing of various techniques can be used to confirm the identification of species of snake from which the alleged venom was milked. The results can be helpful in framing charge-sheets against accused of illegal venom trafficking and can also be used to verify the purity and quality of commercially available snake venoms.

Modified Zenker's peroral endoscopic myotomy: a novel technique to improve access and depth of muscular dissection.

Video 1The modified Zenker's peroral endoscopic myotomy technique to treat a large Zenker's diverticulum.

Global variations in diagnostic guidelines for Barrett's esophagus.

Endoscopic diagnosis of gastroesophageal junction and Barrett's esophagus is essential for surveillance and early detection of esophageal adenocarcinoma and esophagogastric junction cancer. Despite its small size, the gastroesophageal junction has many inherent problems, including marked differences in diagnostic methods for Barrett's esophagus in international guidelines. To define Barrett's esophagus, gastroesophageal junction location should be clarified. Although gastric folds and palisade vessels are landmarks for identifying this junction, they are sometimes difficult to observe due to air entry or reflux esophagitis. The possibility of diagnosing a malignancy associated with Barrett's esophagus <1 cm, identified using palisade vessels, should be re-examined. Nontargeted biopsies of Barrett's esophagus are commonly used to detect intestinal metaplasia, dysplasia, and cancer as described in the Seattle protocol. Barrett's esophagus with intestinal metaplasia has a high risk of becoming cancerous. Furthermore, the frequency of cancer in patients with Barrett's esophagus without intestinal metaplasia is high, and the guidelines differ on whether to include the presence of intestinal metaplasia in the diagnosis of Barrett's esophagus. Use of advanced imaging technologies, including narrow-band imaging with magnifying endoscopy and linked color imaging, is reportedly valid for diagnosing Barrett's esophagus. Furthermore, artificial intelligence has facilitated the diagnosis of Barrett's esophagus through its deep learning and image recognition capabilities. However, it is necessary to first use the endoscopic definition of the gastroesophageal junction, which is common in all countries, and then elucidate the characteristics of Barrett's esophagus in each region, for example, length differences in the risk of carcinogenesis with and without intestinal metaplasia.

Rio de Janeiro Global Consensus on Landmarks, Definitions, and Classifications in Barrett's Esophagus: World Endoscopy Organization Delphi Study.

BACKGROUND & AIMS: Despite the significant advances made in the diagnosis and treatment of Barrett's esophagus (BE), there is still a need for standardized definitions, appropriate recognition of endoscopic landmarks, and consistent use of classification systems. Current controversies in basic definitions of BE and the relative lack of anatomic knowledge are significant barriers to uniform documentation. We aimed to provide consensus-driven recommendations for uniform reporting and global application. METHODS: The World Endoscopy Organization Barrett's Esophagus Committee appointed leaders to develop an evidence-based Delphi study. A working group of 6 members identified and formulated 23 statements, and 30 internationally recognized experts from 18 countries participated in 3 rounds of voting. We defined consensus as agreement by ≥80% of experts for each statement and used the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) tool to assess the quality of evidence and the strength of recommendations. RESULTS: After 3 rounds of voting, experts achieved consensus on 6 endoscopic landmarks (palisade vessels, gastroesophageal junction, squamocolumnar junction, lesion location, extraluminal compressions, and quadrant orientation), 13 definitions (BE, hiatus hernia, squamous islands, columnar islands, Barrett's endoscopic therapy, endoscopic resection, endoscopic ablation, systematic inspection, complete eradication of intestinal metaplasia, complete eradication of dysplasia, residual disease, recurrent disease, and failure of endoscopic therapy), and 4 classification systems (Prague, Los Angeles, Paris, and Barrett's International NBI Group). In round 1, 18 statements (78%) reached consensus, with 12 (67%) receiving strong agreement from more than half of the experts. In round 2, 4 of the remaining statements (80%) reached consensus, with 1 statement receiving strong agreement from 50% of the experts. In the third round, a consensus was reached on the remaining statement. CONCLUSIONS: We developed evidence-based, consensus-driven statements on endoscopic landmarks, definitions, and classifications of BE. These recommendations may facilitate global uniform reporting in BE.

Oncological outcomes after piecemeal endoscopic mucosal resection of large non-pedunculated colorectal polyps with covert submucosal invasive cancer.

OBJECTIVE: Management of covert submucosal invasive cancer (SMIC) discovered after piecemeal endoscopic mucosal resection (pEMR) of large (>20 mm) non-pedunculated colorectal polyps is challenging. The residual cancer risk is largely unknown. We sought to evaluate this in a large tertiary referral cohort. DESIGN: Cases of covert SMIC following pEMR were identified and followed. Oncological outcomes after surgery were divided based on residual intramural cancer, lymph node metastases (LNM) or both. Risk factors for residual intramural cancer and LNM were analysed based on the original pEMR histological variables. Risk parameters were analysed with respect to low and high-risk variables for residual intramural cancer and LNM. RESULTS: Among 3372 cases of large non-pedunculated colorectal polyps, 143 cases of covert SMIC (4.2%) were identified. 109 underwent surgical resection. Histological analysis of pEMR histology was available in 98 of 109 (90%) cases. 62 cases (63%) had no residual malignancy. 36 cases had residual malignancy (residual intramural cancer n=24; LNM n=5; both n=7). All cases of residual intramural cancer could be identified by a R1 histological deep margin. Cases with poor differentiation (PD) and/or lymphovascular invasion (LVI) had a high risk of LNM (12/33), with a very low risk without these criteria (<1%; 0/65). Cases at low risk for LNM with R0 deep margin have a low risk of residual intramural cancer (<1%; 0/35). CONCLUSION: The majority of cases of large non-pedunculated colorectal polyps with covert SMIC following pEMR will have no residual malignancy. The risk of residual malignancy can be ascertained from three key variables: PD, LVI and R1 deep margin.

Narration and Legacy of Important Chemical Spot Tests in Forensic Investigation.

Chemical spot tests are one of the oldest and simplest presumptive methods of analytical chemistry. They are an integral part of the schematic analysis of different types of substances in various pure and applied scientific disciplines including forensic science. The role of spot tests has remained eternal utility in different branches of forensic science to analyze various types of physical or trace evidences. Forensic experts need to have an absolute understanding of the foundation and technicality behind complex reactions of customary spot tests. Forensic science literature dwells in the diversity of spot tests but an informative and comprehensive compendium of such prose remains occasional and limited in general. Keeping in view the ample history and legacy of spot test, the current review was constructed from a core of historical literature to recapitulate trending applications, chemistry, and limitations of notable "Griess test", "Luminol test", "Kastle-Meyer test", "Phenolphthalein test", "Ninhydrin test", and "Spy dust" in forensic science. The aim of this review article was to describe the outlook and likely impact of these tests on the expansion of scientific investigation. The anticipated output of this review is supposed to impart compatible knowledge in the attentive readers interested in understanding legacy and technical details of selected spot tests used in solving crime.