Lung Cancer Clinical Trial
Official title:
Development of an Artificial Intelligence System for Assessment of Tumor Risk and Diagnosis and Treatment Based on Multimodal Data Fusion Using Deep Learning Technology
NCT number | NCT05426135 |
Other study ID # | Jin_cancer risk |
Secondary ID | |
Status | Recruiting |
Phase | |
First received | |
Last updated | |
Start date | June 1, 2022 |
Est. completion date | October 2026 |
Verified date | June 2022 |
Source | Wuhan Union Hospital, China |
Contact | Yang Jin |
Phone | 15107177084 |
whuhjy[@]126.com | |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
To improve the accuracy of risk prediction, screening and treatment outcome of cancer, we aim to establish a medical database that includes standardized and structured clinical diagnosis and treatment information, image features, pathological features, and multi-omics information and to develop a multi-modal data fusion-based technology system using artificial intelligence technology based on database.
Status | Recruiting |
Enrollment | 3000 |
Est. completion date | October 2026 |
Est. primary completion date | October 2025 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 18 Years to 75 Years |
Eligibility | Inclusion Criteria: 1. Participants with the suspected of lung cancer/node, or stomach cancer/lesion, or colorectal cancer/leision 2. Participants that have signed informed consent. 3. Participants with detailed electronic medical records, image records, pathological records, multi-omics information, and other important clinical diagnostic information. 4. Healthy participants with no clinical diagnosis of lung cancer/node, or stomach cancer/lesion, or colorectal cancer/leision. Exclusion Criteria: 1. Participants with primary clinical and pathological data missing. 2. Participants lost to follow-up. 3. Participants with too poor medical image quality to perform segment and mark ROI accurately |
Country | Name | City | State |
---|---|---|---|
China | Union Hospital, Tongji Medical College, Huazhong University of Science and Technology | Wuhan | Hubei |
Lead Sponsor | Collaborator |
---|---|
Wuhan Union Hospital, China |
China,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | The outcome of clinical diagnosis of suspected patients with lung cancer/pulmonary nodular (Benign/Malignant nodule) | The outcome of clinical diagnosis of patients with lung cancer/pulmonary nodular (Benign/Malignant nodule).
? Benign nodule ? Malignant neoplasm/nodule: squamous cell carcinoma, adenocarcinoma, small cell carcinoma, and large cell carcinoma. |
2022-2026 | |
Primary | The outcome of clinical diagnosis of suspected patients with stomach cancer or lesion (Benign/Malignant). | ? Benign
? Malignant |
2022-2026 | |
Primary | The outcome of clinical diagnosis of suspected patients with colorectal cancer or lesion (Benign/Malignant). | ? Benign
? Malignant |
2022-2026 | |
Primary | Treatment response of anti-cancer therapy at first evaluation in patients with lung/stomach/colorectal cancer (CR, PR, PD, SD). | The treatment response of anti-cancer therapy at first evaluation in patients with lung/stomach/colorectal cancer follows The Response Evaluation Criteria In Solid Tumors (RECIST version 1.1) from the World Health Organization (WHO). The evaluation index is as follows.
CR (complete response): Disappearance of all target lesions and reduction in the short axis measurement of all pathologic lymph nodes to =10 mm. PR (partial response): 30% decrease in the sum of the longest diameter of the target lesions compared with baseline. PD (progressive disease):=20% increase of at least 5 mm in the sum of the longest diameter of the target lesions compared with the smallest sum of the longest diameter recorded OR The appearance of new lesions, including those detected by FDG-PET (fludeoxyglucose positron emission tomography). SD (stable disease): Neither PR nor PD. |
2022-2026 |
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