NCT05965921

Brief Summary

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.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
137

participants targeted

Target at P50-P75 for all trials

Timeline
Completed

Started Jul 2023

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

June 8, 2023

Completed
2 months until next milestone

Study Start

First participant enrolled

July 26, 2023

Completed
2 days until next milestone

First Posted

Study publicly available on registry

July 28, 2023

Completed
1.6 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

February 27, 2025

Completed
28 days until next milestone

Study Completion

Last participant's last visit for all outcomes

March 27, 2025

Completed
Last Updated

May 31, 2025

Status Verified

May 1, 2025

Enrollment Period

1.6 years

First QC Date

June 8, 2023

Last Update Submit

May 27, 2025

Conditions

GastroscopyBarrett's Esophagus

Keywords

Barrett's oesophagusArtificial intelligenceEndoscopy

Outcome Measures

Primary Outcomes (1)

  • Number of additional Barrett's neoplasia found on quadrantic biopsies

    The primary endpoint of the study is the number of additional neoplasia found on quadrantic biopsies. This will be collected and calculated from histology data of the targeted and quadrantic biopsies.

    From enrolment to end of follow up at 2 month when histology results are available.

Secondary Outcomes (7)

  • Impact of AI (WISE VISION) in real-life

    From enrolment to end of follow up at 2 month when histology results are available.

  • Impact of AI (WISE VISION) in real-life

    From enrolment to end of follow up at 2 month when histology results are available.

  • Impact of AI (WISE VISION) in real-life

    From enrolment to end of follow up at 2 month when histology results are available.

  • Impact of AI (WISE VISION) in real-life

    From enrolment to end of follow up at 2 month when histology results are available.

  • Impact of AI (WISE VISION) in real-life

    From enrolment to end of follow up at 2 month when histology results are available.

  • +2 more secondary outcomes

Study Arms (1)

Barrett's oesophagus

Patients over 18 with known Barrett's oesophagus having gastroscopy for either surveillance or assessment of known Barrett's neoplasia

Eligibility Criteria

Sexall(Gender-based eligibility)
Gender Eligibility DetailsAny self-identified genders
Healthy VolunteersNo
Age GroupsChild (0-17), Adult (18-64), Older Adult (65+)
Sampling MethodProbability Sample
Study Population

Any adults of over 18 years of age with a known Barrett's oesophagus having a gastroscopy for Barrett's surveillance or assessment of known Barrett's neoplasia in a local or tertiary hospital.

You may qualify if:

  • 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

You may not qualify if:

  • 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.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Queen Alexandra Hospital, Portsmouth Hospitals University NHS trust

Portsmouth, Hampshire, PO6 1LY, United Kingdom

Location

Related Publications (1)

  • Abdelrahim 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: 36283443BACKGROUND

MeSH Terms

Conditions

Barrett Esophagus

Condition Hierarchy (Ancestors)

Precancerous ConditionsNeoplasmsEsophageal DiseasesGastrointestinal DiseasesDigestive System Diseases

Study Officials

  • Pradeep Bhandari

    Queen Alexandra Hospital, Portsmouth Hospitals University NHS Trust

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
observational
Observational Model
CASE ONLY
Time Perspective
PROSPECTIVE
Target Duration
1 Month
Sponsor Type
OTHER GOV
Responsible Party
SPONSOR

Study Record Dates

First Submitted

June 8, 2023

First Posted

July 28, 2023

Study Start

July 26, 2023

Primary Completion

February 27, 2025

Study Completion

March 27, 2025

Last Updated

May 31, 2025

Record last verified: 2025-05

Locations

GB(1)