Improving the endoscopic detection of early oesophageal neoplasia

The endoscopic detection of oesophageal cancer is complex; largely owing to the subtle appearances of early oesophageal lesions on endoscopy, as well as clinician experience. Early detection is vital, since lesions confined to the mucosal or superficial layers of the submucosa can be treated with endoscopic eradication therapies to good effect. Conversely, patients presenting with late stage oesophageal cancer have very poor outcomes. Improving the detection of oesophageal cancer requires a multifaceted approach. Since the symptoms patients present with are often vague until the disease has progressed beyond the point that it is curable, developing a way to risk stratify or rationalise patient access to endoscopy, based on objective markers of the presence of serious underlying pathology, is vital to allow adequate resource provision in the modern UK endoscopy unit. In patients who do undergo endoscopy there remains a significant mis-rate of cancers in those with de-novo oesophageal cancer as well as those enrolled in Barrett’s oesophagus surveillance programs. We postulate that advanced imaging technologies, in combination with artificial intelligence systems, may improve the diagnostic performance of endoscopists assessing for oesophageal cancers. This body of work presents a comprehensive review of the literature surrounding the epidemiology, detection, classification and endoscopic treatment modalities for both squamous cell and adenocarcinomas of the oesophagus. It also presents four studies undertaken with the overarching aim of improving the endoscopic detection of oesophageal cancer. The first study presents a methodology for the quantification of a biomarker from gastric aspirate samples and an assessment of whether differences in expression levels can be used to predict the presence of neoplasia in patients with or without Barrett’s oesophagus. The second study investigates the role of a novel, advanced endoscopic imaging technology and whether it improves the diagnostic performance of expert and trainee endoscopists assessing Barrett’s oesophagus for the presence of dysplasia or adenocarcinoma. The final two studies present a significant body of work assessing the feasibility and diagnostic performance of a novel artificial intelligence system designed as part of this thesis, for the detection and characterisation of squamous cell cancer of the oesophagus based on microvascular patterns

Endoscopic Optical Coherence Tomography for Clinical Gastroenterology

Optical coherence tomography (OCT) is a real-time optical imaging technique that is similar in principle to ultrasonography, but employs light instead of sound waves and allows depth-resolved images with near-microscopic resolution. Endoscopic OCT allows the evaluation of broad-field and subsurface areas and can be used ancillary to standard endoscopy, narrow band imaging, chromoendoscopy, magnification endoscopy, and confocal endomicroscopy. This review article will provide an overview of the clinical utility of endoscopic OCT in the gastrointestinal tract and of recent achievements using state-of-the-art endoscopic 3D-OCT imaging systems. Keywords: optical coherence tomography; optical biopsy; endoscopic imaging; Barrett’s esophagus; inflammatory bowel diseaseNational Institutes of Health (U.S.) (Grant R01-CA75289-17)National Institutes of Health (U.S.) (Grant R44-CA101067-06)National Institutes of Health (U.S.) (Grant R01-CA178636-01)National Institutes of Health (U.S.) (Grant R44EY022864-01)National Institutes of Health (U.S.) (Grant R01-EY011289-27)National Institutes of Health (U.S.) (Grant R01-NS057476-05)United States. Air Force Office of Scientific Research (Grant FA9550-12-1-0499)United States. Air Force Office of Scientific Research (Grant FA9550-10-1-0551

Artificial intelligence and automation in endoscopy and surgery

Modern endoscopy relies on digital technology, from high-resolution imaging sensors and displays to electronics connecting configurable illumination and actuation systems for robotic articulation. In addition to enabling more effective diagnostic and therapeutic interventions, the digitization of the procedural toolset enables video data capture of the internal human anatomy at unprecedented levels. Interventional video data encapsulate functional and structural information about a patient’s anatomy as well as events, activity and action logs about the surgical process. This detailed but difficult-to-interpret record from endoscopic procedures can be linked to preoperative and postoperative records or patient imaging information. Rapid advances in artificial intelligence, especially in supervised deep learning, can utilize data from endoscopic procedures to develop systems for assisting procedures leading to computer-assisted interventions that can enable better navigation during procedures, automation of image interpretation and robotically assisted tool manipulation. In this Perspective, we summarize state-of-the-art artificial intelligence for computer-assisted interventions in gastroenterology and surgery

Endoscopic Assessment and Treatment of Barrett’s Oesophagus

Oesophageal cancer worldwide is the eighth commonest cancer and carries a poor prognosis. Barrett’s oesophagus is the only known risk factor for oesophageal adenocarcinoma. Cancer progresses along a metaplasia-dysplasia pathway. Dysplastic changes may be seen on endoscopic assessment. This thesis presents evidence that i-Scan virtual chromoendoscopy together with acetic acid chromoendoscopy can improve dysplasia detection using a simple classification system. Superficial lesions, without deeper invasion (low and high grade dysplasia, early cancers) have a low risk of distant metastasis. Endoscopic resection and ablation techniques have been demonstrated to have an excellent efficacy and safety profile. The current standard of care for early Barrett’s neoplasia is endoscopic management rather than surgical intervention. Surgery for oesophageal cancer is centred in specialist units due to improved outcomes in high volume centres. The UK radiofrequency ablation registry collects outcomes for patients undergoing endoscopic therapy for Barrett’s neoplasia. This thesis demonstrates that there is no difference in dysplasia or intestinal metaplasia resolution rates or dysplasia recurrence between low and high volume centres. Learning curve analysis suggests that there is a change point at 18 cases, when the observed successful treatment rate of the centre becomes better than the expected rate. Centres should complete 20 cases before competency can be achieved. Treatment of Barrett’s neoplasia involves endoscopic resection of visible lesions. Due to the high risk of metachronous lesions, the remaining Barrett’s epithelium undergoes field ablation, commonly with radiofrequency ablation. Following successful treatment the risk of dysplasia recurrence is 6%. The risk increases with increasing length of the initial Barrett segment and with increasing age. The risk of untreated islands of Barrett’s IM is unknown but this thesis demonstrates that it does not seem to confer an increased risk of recurrence and may not require further ablation if unresponsive to treatment

Artificial intelligence in gastroenterology: a state-of-the-art review

The development of artificial intelligence (AI) has increased dramatically in the last 20 years, with clinical applications progressively being explored for most of the medical specialties. The field of gastroenterology and hepatology, substantially reliant on vast amounts of imaging studies, is not an exception. The clinical applications of AI systems in this field include the identification of premalignant or malignant lesions (e.g., identification of dysplasia or esophageal adenocarcinoma in Barrett's esophagus, pancreatic malignancies), detection of lesions (e.g., polyp identification and classification, small-bowel bleeding lesion on capsule endoscopy, pancreatic cystic lesions), development of objective scoring systems for risk stratification, predicting disease prognosis or treatment response [e.g., determining survival in patients post-resection of hepatocellular carcinoma), determining which patients with inflammatory bowel disease (IBD) will benefit from biologic therapy], or evaluation of metrics such as bowel preparation score or quality of endoscopic examination. The objective of this comprehensive review is to analyze the available AI-related studies pertaining to the entirety of the gastrointestinal tract, including the upper, middle and lower tracts; IBD; the hepatobiliary system; and the pancreas, discussing the findings and clinical applications, as well as outlining the current limitations and future directions in this field.Cellular mechanisms in basic and clinical gastroenterology and hepatolog

New Techniques in Gastrointestinal Endoscopy

As result of progress, endoscopy has became more complex, using more sophisticated devices and has claimed a special form. In this moment, the gastroenterologist performing endoscopy has to be an expert in macroscopic view of the lesions in the gut, with good skills for using standard endoscopes, with good experience in ultrasound (for performing endoscopic ultrasound), with pathology experience for confocal examination. It is compulsory to get experience and to have patience and attention for the follow-up of thousands of images transmitted during capsule endoscopy or to have knowledge in physics necessary for autofluorescence imaging endoscopy. Therefore, the idea of an endoscopist has changed. Examinations mentioned need a special formation, a superior level of instruction, accessible to those who have already gained enough experience in basic diagnostic endoscopy. This is the reason for what these new issues of endoscopy are presented in this book of New techniques in Gastrointestinal Endoscopy

Morphological Features of Dysplastic Progression in Epithelium: Quantification of Cytological, Microendoscopic, and Second Harmonic Generation Images

Advances in imaging technology have led to a variety of available clinical and investigational systems. In this collection of studies, we tested the relevance of morphological image feature quantification on several imaging systems and epithelial tissues. Quantification carries the benefit of creating numerical baselines and thresholds of healthy and abnormal tissues, to potentially aid clinicians in determining a diagnosis, as well as providing researchers with standardized, unbiased results for future dissemination and comparison. Morphological image features in proflavine stained oral cells were compared qualitatively to traditional Giemsa stained cells, and then we quantified the nuclear to cytoplasm ratio. We determined that quantification of proflavine stained cells matched our hypothesis, as the nuclei in oral carcinoma cells were significantly larger than healthy oral cells. Proflavine has been used in conjunction with translational fluorescence microendoscopy of the gastrointestinal tract, and we demonstrated the ability of our custom algorithm to accurately (up to 85% sensitivity) extract colorectal crypt area and circularity data, which could minimize the burden of training on clinicians. In addition, we proposed fluorescein as an alternative fluorescent dye, providing comparable crypt area and circularity information. In order to investigate the morphological changes of crypts via the supporting collagen structures, we adapted our quantification algorithm to analyze crypt area, circularity, and an additional shape parameter in second harmonic generation images of label-free freshly resected murine epithelium. Murine models of colorectal cancer (CRC) were imaged at early and late stages of tumor progression, and we noted significant differences between the Control groups and the late cancer stages, with some differences between early and late stages of CRC progression

Examining lipid metabolism of colorectal adenomas and carcinomas using Rapid Evaporative Ionisation Mass Spectrometry (REIMS)

Background There is an unmet need for real-time intraoperative colorectal tissue recognition, which would promote personalised oncologic decision making. Rapid Evaporative Ionization Mass Spectrometry (REIMS) analyses the composition of cellular lipids through the aerosol generated from electrosurgical instruments, providing a novel diagnostic platform and surgeon feedback. Thesis Hypothesis Colorectal lipid metabolism and cellular lipid composition are associated with the phenotype of colorectal adenomas and carcinomas, which can be leveraged for tissue recognition in vivo. Methods This thesis contains three work packages. First, a method for REIMS spectral quality control was developed based on a human dataset and analysis of a porcine model assessed the spectral impact of technical and environmental factors. Second, an ex vivo spectral reference database was constructed from analysis of human colorectal tissues, assessing the ability of REIMS for tissue recognition. Finally, REIMS was translated into the operating theatre, for proof-of-principle application of during transanal minimally invasive surgery (TAMIS). Results Sensitivity analyses revealed seven minimum quality criteria for REIMS spectra to be included in all future statistical analyses, with quality also impacted by low diathermy power, coagulation mode and tissue contamination. Based on tissue of 161 patients, REIMS could differentiate colorectal normal, adenoma and cancer tissue with 91.1% accuracy, and disease from normal with 93.5% accuracy. REIMS could risk-stratify adenomas by predicting grade of dysplasia, however not histological features of poor prognosis in cancers. 61 pertinent lipid metabolites were structurally identified. REIMS was coupled to TAMIS in seven patients. Optimisation of the workflow successfully increased signal intensity, with tissue recognition showing high accuracy in vivo and identification of a cancer-involved margin. Discussion This thesis demonstrates that REIMS can be optimised and applied for accurate real-time colorectal tissue recognition based on cellular lipid composition. This can be translated in vivo, with promising results during first-in-man mass spectrometry-coupled TAMIS.Open Acces