NCT05928819

Brief Summary

Upper gastrointestinal (GI) cancers are one of the most common cancers worldwide. Except for cardia cancers, the incidence of gastric cancer has decreased consistently since 1980, but remains at a high level. In France, gastric cancers are the 6th most common cause of cancer-related mortality. The risk factors of upper GI cancers are well known and their control could prevent the development of cancers: smoking cessation, reduction of obesity, alcohol, eradication of Helicobacter pylori. But late presentation with upper GI cancer results in a poorer prognosis. Patients with advanced (Stage IV) gastric cancer have a five-year survival rate of 3.7% whereas patients whose gastric cancer is discovered in its early stage (Stage I) have a significantly higher five-year survival rate of 88.4%. Therefore, endoscopic detection of upper GI lesions at an earlier stage is the single most effective measure for reducing cancer mortality. But upper GI cancer is also often missed during examinations, and some studies demonstrated a missed cancer rate of 2.3-13.9% in Western populations. In the past decade, accurate diagnosis during endoscopy has become particularly important as dysplastic lesions and early gastric cancers can be treated effectively with both endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD), avoiding the morbidity and mortality associated with gastrectomy. However, these early neoplastic lesions can be sometimes difficult to distinguish from background mucosa, even with advanced imaging techniques (high definition, chromoendoscopy). In recent years, image recognition using artificial intelligence (AI) with deep learning has dramatically improved and opened the door to more detailed image analysis and real time application in various medical field, including endoscopy. For example, in the colorectal cancer screening area, real time computer-aided detection systems (CADe) can lead to significant increases in both polyp and adenoma detection rates. CADe has also shown good performance in detection of Barrett's neoplasia during live endoscopic procedures in order to more accurately locate the area to be biopsied. Recently, a Chinese study showed that CADe achieved high diagnostic accuracy in detecting upper GI cancers, with sensitivity similar to that of expert endoscopists and superior to that of non-experts. This system could support non-experts by improving their diagnostic accuracy to a level similar to that of experts and provide assistance for improving the effectiveness of upper GI cancer diagnosis and screening. Although encouraging results have been published regarding the use of AI in the diagnosis of upper GI cancers, the clinical applicability of such systems in a European population has yet to be investigated. Therefore, we want to evaluate the diagnostic capability of a recent CADx compared to endoscopists in order to improve the real-time detection of early gastric cancers in our European center Edouard Herriot Hospital, Lyon, France, as well as 3 other tertiary centers in France (Limoges, Rennes and Nancy University Hospitals). With a high prevalence of stomach cancer, Japan is a world leader in high-quality diagnostic upper GI endoscopy, and the clinical routine in this country differs substantially from Western practice, with population-based screening programs. We will use for our study a CADx developed by AI medical service Inc. (1-18-1, Higashiikebukuro, Toshima-ku, Tokyo 170-0013, Japan), a Japanese company developing AI systems that supports endoscopist's diagnosis for the digestive tract. A recent study involving AI medical service system showed good results in the diagnosis of early gastric cancer compared to endoscopists, with a significantly higher sensitivity.

Trial Health

43
At Risk

Trial Health Score

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

Trial has exceeded expected completion date
Enrollment
120

participants targeted

Target at P50-P75 for all trials

Timeline
Completed

Started Jan 2023

Geographic Reach
1 country

1 active site

Status
unknown

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

Study Start

First participant enrolled

January 1, 2023

Completed
6 months until next milestone

First Submitted

Initial submission to the registry

June 23, 2023

Completed
10 days until next milestone

First Posted

Study publicly available on registry

July 3, 2023

Completed
12 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

June 30, 2024

Completed
2 months until next milestone

Study Completion

Last participant's last visit for all outcomes

August 31, 2024

Completed
Last Updated

July 3, 2023

Status Verified

June 1, 2023

Enrollment Period

1.5 years

First QC Date

June 23, 2023

Last Update Submit

June 23, 2023

Conditions

Keywords

diagnostic toolAICADgastric cancertherapeutic choice guidance

Outcome Measures

Primary Outcomes (1)

  • Evaluation of the proportion of gastric neoplastic lesions detected by a computer-aided diagnosis system (CADx) compared with experienced endoscopists and correlation with final histology reading.

    Time point can be reached either 2 weeks after endoscopic resection at first visit or between 2-4 months later in case of surgery at third visit

Study Arms (1)

Gastric lesion diagnostic

Every patient referred to our center for upper gastrointestinal endoscopy for investigation and/or resection of gastric neoplastic lesion can join the cohort of this study and will benefit from diagnosis and treatment by experienced endoscopists.

Procedure: Evaluation of the proportion of gastric neoplastic lesions detected by a computer-aided diagnosis system (CADx) compared with experienced endoscopists.

Interventions

Evaluation of the proportion of gastric neoplastic lesions detected by a computer-aided diagnosis system (CADx) compared with experienced endoscopists.

Gastric lesion diagnostic

Eligibility Criteria

Age18 Years+
Sexall
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodProbability Sample
Study Population

Every patient referred to our center for upper gastrointestinal endoscopy for investigation and/or resection of gastric neoplastic lesion can join the cohort of this study and will benefit from diagnosis and treatment by experienced endoscopists.

You may qualify if:

  • both gender patients even or older than 18 years old
  • patient in need of proven diagnostic or therapeutic gastroscopy for gastric lesion resection
  • patient with French Health Insurance coverage
  • obtaining of oral non opposition to research after loyal, clear and complete delivery of information

You may not qualify if:

  • previous attempt of lesion resection
  • patient with no gastric lesion
  • inadequate examination quality (gastroparesis)
  • patient with health disorders needing short procedure times

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Hôpital Edouard Herriot

Lyon, 69437, France

RECRUITING

MeSH Terms

Conditions

Stomach Neoplasms

Condition Hierarchy (Ancestors)

Gastrointestinal NeoplasmsDigestive System NeoplasmsNeoplasms by SiteNeoplasmsDigestive System DiseasesGastrointestinal DiseasesStomach Diseases

Central Study Contacts

Pierre LAFEUILLE, MD

CONTACT

Matthieu PIOCHE, MD

CONTACT

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
PROSPECTIVE
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

June 23, 2023

First Posted

July 3, 2023

Study Start

January 1, 2023

Primary Completion

June 30, 2024

Study Completion

August 31, 2024

Last Updated

July 3, 2023

Record last verified: 2023-06

Locations