Study on the Staging and Prognosis Model of Bladder Cancer (2024-SR-386)

Nanjing Medical University

Status: Active, not recruiting

Conditions: Bladder Cancer

Study type: Observational

Funder types: Other

Identifiers

NCT06565923

2024-SR-386

Details and patient eligibility

About

Firstly, we retrospectively gathered the patient information who compliant with the criteria from 2012 to 2023, encompassing basic information, clinical information, along with MRI images, blood/urine samples, and tissue samples, for conducting relevant analyses of radiomics. Subsequently, based on artificial intelligence technology, deep learning and machine learning models were established on the basis of MRI radiomics and pathological histomics. Ultimately, the following research aims were accomplished: 1. Primary research objective: To explore the role of artificial intelligence and multimodal omics features in the staging and prognosis monitoring of bladder cancer. 2. Secondary objective: To explore the correlations among radiomics, case histomics, and test omics.

Enrollment: 200 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• 1. Patients with bladder cancer in preoperative examination; 2. Gender is not limited; 3. Age≥ 18 years old; 4. Be able to provide MRI images, pathological data and laboratory examination data before the operation; 5. Agree to provide basic personal clinical information and pathological and imaging data for scientific research use, and sign the informed consent form; 6. Agree to provide monitoring results during follow-up recurrence monitoring;

Exclusion criteria

• 1. Incomplete clinicopathological data; 2. Combined with upper tract urothelial carcinoma or previously diagnosed upper tract urothelial carcinoma; 3. Is participating in the rest of the clinical studies; Unable to cooperate with the relevant examinations of this project, and do not agree to sign the informed consent form.

Trial design

200 participants in 1 patient group

Adult bladder cancer patients with MRI, pathology, and laboratory data provided