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Clinical Trial Details — Status: Active, not recruiting

Administrative data

NCT number NCT05001321
Other study ID # FirstHCMU_DL_oncology
Secondary ID
Status Active, not recruiting
Phase
First received
Last updated
Start date July 1, 2021
Est. completion date December 31, 2024

Study information

Verified date August 2021
Source First Hospital of China Medical University
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

To assist postoperative pathological diagnosis and classification of gastric cancer by machine learning; To improve the accuracy of pathological diagnosis of gastric cancer by machine learning; To predict the effectiveness of treatment for gastric cancer by deep learning; To construct a model to predict the survival of gastric cancer patients by multimodal deep learning.


Recruitment information / eligibility

Status Active, not recruiting
Enrollment 3300
Est. completion date December 31, 2024
Est. primary completion date January 31, 2022
Accepts healthy volunteers No
Gender All
Age group 18 Years to 79 Years
Eligibility Inclusion Criteria: - The diagnosis of gastric cancer was confirmed by pathology; - Preoperative enhanced abdominal CT; - Available detailed clinical and pathological data; - Integrated follow-up data. Exclusion Criteria: - The patients had severe underlying disease; - Overall survival was less than 3 months; - No detailed information could be collected.

Study Design


Related Conditions & MeSH terms


Intervention

Radiation:
The whole abdomen contrast-enhanced CT scan
All the participants were measured by the whole abdomen contrast-enhanced CT scan.
Other:
H&E stained sections and slides
HE pathological examination was performed on all specimens of enrolled patients.

Locations

Country Name City State
China The fourth People's Hospital of Changzhou Changzhou Jiangsu
China Chaoyang Central Hospital Chaoyang Liaoning
China The General Hospital of Fushun Mining Bureau Fushun Liaoning
China The Second Hospital of Shandong University Ji'nan Shandong
China First Hospital of Jinzhou Medical University Jinzhou Liaoning
China The First Affiliated Hospital of China Medical University Shenyang Liaoning

Sponsors (6)

Lead Sponsor Collaborator
First Hospital of China Medical University Chaoyang Central Hospital, First Hospital of Jinzhou Medical University, The fourth People's Hospital of Changzhou, The General Hospital of Fushun Mining Bureau, The Second Hospital of Shandong University

Country where clinical trial is conducted

China, 

Outcome

Type Measure Description Time frame Safety issue
Primary Maximum diameter of tumor To measure the maximum diameter of tumor on preoperative enhanced abdominal CT of patients with gastric cancer. 1 day
Primary Growth pattern To assess the growth pattern on preoperative enhanced abdominal CT of patients with gastric cancer, including endophytic, exophytic and mixed. 1 day
Primary Enhancement pattern To assess the enhancement pattern on preoperative enhanced abdominal CT of patients with gastric cancer, including homogeneous and heterogeneous. 1 day
Primary Enhancement degree To assess the enhancement degree on preoperative enhanced abdominal CT of patients with gastric cancer, including hypoenhancement, isoenhancement and hyperenhancement. 1 day
Primary Nucleus size To obtain the nucleus size of postoperative H&E stained sections and slides of gastric cancer by deep learning. 1 day
Primary Nucleus shape To obtain the nucleus shape of postoperative H&E stained sections and slides of gastric cancer by deep learning. 1 day
Primary Distribution of pixel intensity To obtain the distribution of pixel intensity of postoperative H&E stained sections and slides of gastric cancer by deep learning. 1 day
Primary Texture of nuclei To obtain the texture of nuclei of postoperative H&E stained sections and slides of gastric cancer by deep learning. 1 day
Secondary Survival status To analyze the survival status of patients with gastric cancer, involving dead and alive. 1 day
Secondary Overall survival To calculate the overall survival of patients with gastric cancer based on days to death and days to last follow-up. 1 day
Secondary Recurrence/metastasis To calculate the days to recurrence/metastasis of patients with gastric cancer. 1 day
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