Training in Capsule Endoscopy: Are We Lagging behind?

Capsule endoscopy (CE) is a new modality to investigate the small bowel. Since it was invented in 1999, CE has been adopted in the algorithm of small bowel investigations worldwide. Reporting a CE video requires identification of landmarks and interpretation of pathology to formulate a management plan. There is established training infrastructure in place for most endoscopic procedures in Europe; however despite its wide use, there is a lack of structured training for CE. This paper focuses on the current available evidence and makes recommendations to standardise training in CE

International core curriculum for capsule endoscopy training courses

Capsule endoscopy (CE) has become a first-line noninvasive tool for visualisation of the small bowel (SB) and is being increasingly used for investigation of the colon. The European Society of Gastrointestinal Endoscopy (ESGE) guidelines have specified requirements for the clinical applications of CE. However, there are no standardized recommendations yet for CE training courses in Europe. The following suggestions in this curriculum are based on the experience of European CE training courses directors. It is suggested that 12 hours be dedicated for either a small bowel capsule endoscopy (SBCE) or a colon capsule endoscopy (CCE) course with 4 hours for an introductory CCE course delivered in conjunction with SBCE courses. SBCE courses should include state-of-the-art lectures on indications, contraindications, complications, patient management and hardware and software use. Procedural issues require approximately 2 hours. For CCE courses 2.5 hours for theoretical lessons and 3.5 hours for procedural issued are considered appropriate. Hands-on training on reading and interpretation of CE cases using a personal computer (PC) for 1 or 2 delegates is recommended for both SBCE and CCE courses. A total of 6 hours hands-on session- time should be allocated. Cases in a SBCE course should cover SB bleeding, inflammatory bowel diseases (IBD), tumors and variants of normal and cases with various types of polyps covered in CCE courses. Standardization of the description of findings and generation of high-quality reports should be essential parts of the training. Courses should be followed by an assessment of trainees' skills in order to certify readers' competency.info:eu-repo/semantics/publishedVersio

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

Novel developments in endoscopic mucosal imaging

Endoscopic techniques such as High-definition and optical-chromoendoscopy have had enormous impact on endoscopy practice. Since these techniques allow assessment of most subtle morphological mucosal abnormalities, further improvements in endoscopic practice lay in increasing the detection efficacy of endoscopists. Several new developments could assist in this. First, web based training tools could improve the skills of the endoscopist for enhancing the detection and classification of lesions. Secondly, incorporation of computer aided detection will be the next step to raise endoscopic quality of the captured data. These systems will aid the endoscopist in interpreting the increasing amount of visual information in endoscopic images providing real-time objective second reading. In addition, developments in the field of molecular imaging open opportunities to add functional imaging data, visualizing biological parameters, of the gastrointestinal tract to white-light morphology imaging. For the successful implementation of abovementioned techniques, a true multi-disciplinary approach is of vital importance

Quality assurance of training in diagnostic and therapeutic gastrointestinal endoscopy

Previous evidence has shown that standards of performance in gastrointestinal endoscopy are variable and that there are disparities in training outcomes. Many changes have been made recently to both training and assessment of endoscopy in the UK. However, no prospective methods of evaluating their outcome have been put in place. The aims of this research were to evaluate current and new training processes and assessments in order to quality assure the outcomes and improve the training process. Two audits were undertaken demonstrating improvements in colonoscopy training over 5 years within a single region and in trainee perceptions of their training nationally. Two studies were done investigating a novel computer colonoscopy simulator for assessment of colonoscopic skills, demonstrating excellent construct validity. A multi-centre randomised controlled trial evaluated the use of this simulator in novice training, which was shown to be equivalent to standard bed-side training with a high degree of skills transfer to real-life colonoscopy. Assessment tools for therapeutic endoscopic procedures were developed, validated and used to quality assure a course in therapeutic endoscopy. This course resulted in significant improvements in practical skills for three of the four therapeutic procedures following training. Web-based training and assessment modules for lesion recognition at capsule endoscopy were developed, validated and piloted. This demonstrated the effectiveness of using new training methodologies for skills improvement in this area. A training course for radiographers in virtual colonoscopy was developed and the training evaluated. This demonstrated competence in practical performance and improvements in knowledge and interpretative skill. Finally, two qualitative studies on non-technical skills in endoscopy were undertaken in order to widen the assessment domains from purely knowledge and skill. An interview study provided the basis for development of a nontechnical skills taxonomy and a video-analysis study resulted in production of a marker system for professional behaviour within gastrointestinal endoscopy

Explainable Information Retrieval using Deep Learning for Medical images

Image segmentation is useful to extract valuable information for an efficient analysis on the region of interest. Mostly, the number of images generated from a real life situation such as streaming video, is large and not ideal for traditional segmentation with machine learning algorithms. This is due to the following factors (a) numerous image features (b) complex distribution of shapes, colors and textures (c) imbalance data ratio of underlying classes (d) movements of the camera, objects and (e) variations in luminance for site capture. So, we have proposed an efficient deep learning model for image classification and the proof-of-concept has been the case studied on gastrointestinal images for bleeding detection. The Explainable Artificial Intelligence (XAI) module has been utilised to reverse engineer the test results for the impact of features on a given test dataset. The architecture is generally applicable in other areas of image classification. The proposed method has been compared with state-of-the-art including Logistic Regression, Support Vector Machine, Artificial Neural Network and Random Forest. It has reported F1 score of 0.76 on the real world streaming dataset which is comparatively better than traditional methods