Real-life Prospective Evaluation of Computer-aided Detection (CAD) of Barrett's Neoplasia

Barrett's oesophagus is a pre-cancerous condition in which normal cells in the lining of gullet undergo cell changes and this increases the risk of developing adenocarcinoma (a type of cancer) of the gullet. This type of cancer is the 5th most common type of cancer in the UK. To minimise this risk of developing cancer, patients with Barret's oesophagus have regular gastroscopy (a small camera at the tip of the slim tube) every 2-5 years to detect early cancer cell changes. During the procedure, the whole of oesophagus is carefully inspected, and small tissue samples (biopsies) are taken from visible abnormal area within Barrett's oesophagus and sent to the lab to check for cell changes. This is called targeted biopsies. As the endoscopist cannot always tell during gastroscopy where cells are changing, biopsies from each quarter of the gullet (called quadrantic biopsies) are also taken to reduce the risk of pre-cancerous cells being missed. However, this process is time consuming and expensive as numerous biopsies are required. Recently, there has been a huge development in artificial intelligence (AI). One of these developments is the aid of computer to detect (called computer-aided detection - CAD) the abnormal cell changes within Barrett's during gastroscopy. This system has recently been trained and tested on videos and photos to prove that its performance is as good as expert endoscopists. This system has been already approved to use in the UK. However, this system needs to be tested further and incorporated into real life use to prove that the CAD is useful in detecting cell changes during gastroscopy for targeted biopsies and therefore, the random biopsies can be avoided. A sample of patients with Barrett's oesophagus will be invited to participate in this study. Participants will have a gastroscopy as part of their usual care for Barrett's oesophagus. Endoscopist will inspect Barrett's oesophagus using AI and will take both targeted biopsies if clinically deemed appropriate along with quadrantic biopsies. Participants will continue to receive usual care and no additional follow up or procedures will be required as part of the study.

Sex

All

Inclusion Criteria:

* Anyone aged 18 years and above
* Known Barrett's oesophagus and having a gastroscopy for Barrett's surveillance or assessment of known neoplasia.
* Participant is willing and able to give informed consent for participation in the study

Exclusion Criteria:

* Recent ablation therapy (HALO, APC) to Barrett's oesophagus in the last 6 weeks
* Oesophageal disorder and patient's factors which impairs the ability of endoscopist to adequately assess of Barrett's neoplasia. This includes but not just limiting to severe oesophagitis, candidiasis, and poor patient tolerance.

• BACKGROUNDAbdelrahim M, Saiko M, Maeda N, Hossain E, Alkandari A, Subramaniam S, Parra-Blanco A, Sanchez-Yague A, Coron E, Repici A, Bhandari P. Development and validation of artificial neural networks model for detection of Barrett's neoplasia: a multicenter pragmatic nonrandomized trial (with video). Gastrointest Endosc. 2023 Mar;97(3):422-434. doi: 10.1016/j.gie.2022.10.031. Epub 2022 Oct 23. PMID 36283443