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Trial Title:
The Role of Artificial Intelligence in Endoscopic Diagnosis of Esophagogastric Junctional Adenocarcinomaļ¼A Single Center, Case-control, Diagnostic Study
NCT ID:
NCT05819099
Condition:
Stomach Neoplasms
Conditions: Official terms:
Adenocarcinoma
Stomach Neoplasms
Study type:
Observational
Overall status:
Not yet recruiting
Study design:
Time perspective:
Retrospective
Intervention:
Intervention type:
Diagnostic Test
Intervention name:
An Intelligent Endoscopic Diagnosis System Developed and Verified Based on Deep Learning
Description:
This study will compare the established AI model with the diagnostic results of
endoscopists to evaluate the clinical auxiliary value of the model for endoscopists.
Arm group label:
Test Set
Arm group label:
Training Set
Arm group label:
Verification Set
Summary:
This is a single center, case-control, diagnostic study.The aim of this study is to use
deep learning methods to retrospectively analyze the imaging data of gastrointestinal
endoscopy in Qilu Hospital, and construct an artificial intelligence model based on
endoscopic images for detecting and determining the depth of invasion of esophagogastric
junctional adenocarcinoma.This study will also compare the established AI model with the
diagnostic results of endoscopists to evaluate the clinical auxiliary value of the model
for endoscopists.The research includes stages such as data collection and preprocessing,
artificial intelligence model development, model testing and evaluation. The gastroscopy
image dataset constructed by this research institute mainly includes three modes of
endoscopic imaging: white light endoscopy, optical enhancement endoscopy (OE), and
narrowband imaging endoscopy (NBI).
Criteria for eligibility:
Study pop:
This study included endoscopic images of the esophageal gastric junction retrieved from
the Endoscopy Center of Qilu Hospital for training and testing the model.The study
population underwent pathological examination and the pathological results were used as
the gold standard.
Sampling method:
Non-Probability Sample
Criteria:
Inclusion Criteria:
- This study included endoscopic images of patients aged 18 and above who underwent
endoscopic examination or treatment
- All patients in the case group need to be pathologically confirmed as esophageal
gastric junction adenocarcinoma, and a pathologist has conducted a standardized
pathological evaluation of the tumor classification of the lesion, including the
overall appearance, size, differentiation type, depth of infiltration, presence or
absence of lymphatic/vascular invasion, surgical margin status, etc.
- The endoscopic images of the control group patients need to be confirmed by biopsy
pathology or at least two experienced endoscopists (with operating experience>5000
cases) to jointly confirm that they have clear benign manifestations
Exclusion Criteria:
- The patient has a previous history of endoscopic treatment or surgery for the
esophageal gastric junction.
- Necessary clinical information cannot be provided during the research process
(patient age, gender, lesion characteristics, endoscopic manifestations, endoscopic
images, etc.)
- Low quality endoscopic images, such as those severely affected by bleeding,
aperture, blurring, defocusing, artifacts, or excessive mucus after biopsy.
Gender:
All
Minimum age:
18 Years
Maximum age:
75 Years
Healthy volunteers:
Accepts Healthy Volunteers
Start date:
December 2023
Completion date:
April 2026
Lead sponsor:
Agency:
Qilu Hospital of Shandong University
Agency class:
Other
Source:
Qilu Hospital of Shandong University
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT05819099
