Clinical Trials Logo

Clinical Trial Details — Status: Not yet recruiting

Administrative data

NCT number NCT05819099
Other study ID # 2023SDU-QILU-1
Secondary ID
Status Not yet recruiting
Phase
First received
Last updated
Start date December 2023
Est. completion date April 2026

Study information

Verified date April 2023
Source Qilu Hospital of Shandong University
Contact Miaomiao Ma, Bachelor
Phone +8617657686098
Email mmiao6098@163.com
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial 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).


Recruitment information / eligibility

Status Not yet recruiting
Enrollment 200
Est. completion date April 2026
Est. primary completion date April 2025
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years to 75 Years
Eligibility 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.

Study Design


Related Conditions & MeSH terms


Intervention

Diagnostic Test:
An Intelligent Endoscopic Diagnosis System Developed and Verified Based on Deep Learning
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.

Locations

Country Name City State
n/a

Sponsors (1)

Lead Sponsor Collaborator
Qilu Hospital of Shandong University

Outcome

Type Measure Description Time frame Safety issue
Primary Sensitivity The researchers calculated the sensitivity of the established AI model and compared it with endoscopists of different levels. 36 months
Primary Specificity The researchers calculated the specificity of the established AI model and compared it with endoscopists of different levels. 36 months
Primary Negative predictive value The researchers calculated the negative predictive value of the established AI model and compared it with endoscopists of different levels. 36 months
Primary Positive predictive value The researchers calculated the positive predictive value of the established AI model and compared it with endoscopists of different levels. 36 months
Primary Accuracy The researchers calculated accuracy positive predictive value of the established AI model and compared it with endoscopists of different levels. 36 months
See also
  Status Clinical Trial Phase
Recruiting NCT01950572 - Tissue Procurement and Natural History Study of Patients With Malignant Mesothelioma
Recruiting NCT05161572 - Perioperative Chemoimmunotherapy With/Without Preoperative Chemoradiation for Locally Advanced Gastric Cancer Phase 2
Not yet recruiting NCT04351867 - A Clinical Trial of Two Adjuvant Chemotherapy Regimens for Postoperative Gastric Cancer Phase 3
Recruiting NCT02887612 - ctDNA for Prediction of Relapse in Gastric Cancer
Active, not recruiting NCT02930291 - The Effect of Preoperative Inflammation-based Scores on Postoperative Morbidity and Mortality for Laparoscopic Gastrectomy
Completed NCT02649348 - Effects of Prehabilitation in Gastric Cancer Patients With Metabolic Syndrome on Perioperative Outcome N/A
Recruiting NCT02310230 - An Evaluation of the Utility of the ExSpiron Respiratory Variation Monitor During Upper GI Endoscopy N/A
Active, not recruiting NCT01609309 - Multicenter Study on Laparoscopic Distal Subtotal Gastrectomy for Advanced Gastric Cancer (CLASS-01) Phase 3
Completed NCT00382720 - Docetaxel and Oxaliplatin in Gastric Cancer Phase 2
Completed NCT00375999 - Docetaxel and Epirubicin in Advanced Gastric Cancer Phase 2
Completed NCT00980382 - A Phase I/II Study of S-1 and Weekly Docetaxel for Metastatic Gastric Carcinoma Phase 1/Phase 2
Recruiting NCT05007106 - MK-7684A With or Without Other Anticancer Therapies in Participants With Selected Solid Tumors (MK-7684A-005) (KEYVIBE-005) Phase 2
Active, not recruiting NCT05602935 - Efficacy and Safety of SOX Regimen Combined With Camrelizumab as Neoadjuvant Treatment in Locally Advanced Gastric Cancer: a Phase II, Single-arm Study Phase 2
Recruiting NCT05033392 - PD-1 Blockade With JS001 Plus Neoadjuvant Chemotherapy for Gastric/Gastroesophageal Junction Cancer Phase 2
Completed NCT04539769 - Impact of the Type of Reconstruction Methods on Diabetes Following Laparoscopic Distal Gastrectomy in Patients With Gastric Cancer and Type 2 Diabetes Phase 2
Active, not recruiting NCT02845986 - Study on Laparoscopic Spleen-Preserving No. 10 Lymph Node Dissection for Advanced Gastric Cancer Phase 2
Active, not recruiting NCT02930278 - The Effect of Preoperative Hemotologic Markers on Postoperative Long-term and Short-term Outcomes for Laparoscopic Gastrectomy
Completed NCT02902575 - The Safety and Feasibility of Laparoscopic-assisted Gastrectomy for Advanced Gastric Cancer After Neoadjuvant Chemotherapy N/A
Recruiting NCT04222114 - Comparing the Efficacy and Safety of Intra-peritoneal Infusion of Catumaxomab and Treatment of Investigator Choice in Patients With Advanced Gastric Carcinoma With Peritoneal Metastasis Phase 3
Recruiting NCT05068180 - Low-dose Neuroleptanalgesia for Postoperative Delirium in Elderly Patients Phase 4