Artificial Intelligence System for Assessment of Tumor Risk and Diagnosis and Treatment

Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18-75
SponsorUnion Hospital, Tongji Medical College, Huazhong University of Science and Technology

About this trial

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.

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

Participants with the suspected of lung cancer/node, or stomach cancer/lesion, or colorectal cancer/leision

Participants that have signed informed consent.

Participants with detailed electronic medical records, image records, pathological records, multi-omics information, and other important clinical diagnostic information.

Healthy participants with no clinical diagnosis of lung cancer/node, or stomach cancer/lesion, or colorectal cancer/leision.

Disqualifiers

Participants with primary clinical and pathological data missing.

Participants lost to follow-up.

Participants with too poor medical image quality to perform segment and mark ROI accurately

Trial population

Patients the suspected of lung cancer/node, or stomach cancer/lesion, or colorectal cancer/leision

Trial design

Design model

Cohort

Time perspective

Prospective

Treatments tested in this trial

Not listed

Trial groups

3,000 Participants
are grouped into 3 trial groups
Group A: Lung cancer group
Group B: Stomach cancer group
Group C: Colorectal cancer group

Trial outcomes

Primary outcomes

1

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). ① Benign nodule ② Malignant neoplasm/nodule: squamous cell carcinoma, adenocarcinoma, small cell carcinoma, and large cell carcinoma.

Time frame
2022-2026
2

The outcome of clinical diagnosis of suspected patients with stomach cancer or lesion (Benign/Malignant).

① Benign ② Malignant

Time frame
2022-2026
3

The outcome of clinical diagnosis of suspected patients with colorectal cancer or lesion (Benign/Malignant).

① Benign ② Malignant

Time frame
2022-2026
4

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.

Time frame
2022-2026

Secondary outcomes

Other outcomes

Sponsors and contacts

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