NCT07051083 Bladder Cancer Staging and Prediction of New Adjuvant Chemotherapy Efficacy Based on Deep Learning and Transfer Learning in Ultrasound-Magnetic Resonance-Pathology Multimodal Multiscale
| NCT ID | NCT07051083 |
| Status | Recruiting |
| Phase | — |
| Sponsor | Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University |
| Condition | Bladder Cancer |
| Study Type | OBSERVATIONAL |
| Enrollment | 480 participants |
| Start Date | 2024-01-01 |
| Primary Completion | 2026-12-31 |
Eligibility & Interventions
Eligibility Fast-Check
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What to Expect as a Participant
This is an observational study. You will not receive an experimental treatment; researchers will collect data based on your existing condition or standard treatment.
This trial targets 480 participants in total. It began in 2024-01-01 with a primary completion date of 2026-12-31.
⚠ This information is for research awareness only. Always consult your physician before joining any clinical trial. Participation is voluntary and you may withdraw at any time.
Brief Summary
Bladder cancer is the most common malignant tumor of the urinary system. The presence or absence of muscle invasion in early bladder cancer is an independent prognostic factor. The involvement of muscle invasion affects the choice of surgical methods and treatment. Preoperatively, the precise assessment of bladder cancer staging has important practical value. A more accurate preoperative assessment of bladder cancer staging can reduce overtreatment and provide a favorable basis for clinicians to choose more reasonable and effective surgical methods. Clinically, there has been a longstanding desire to diagnose the staging of bladder cancer through a simple, convenient, effective, and non-invasive examination. As relevant research progresses, a multi-omics diagnostic model will be beneficial in improving diagnostic efficiency. This project aims to establish a multi-omics artificial intelligence system based on deep learning and transfer learning to accurately diagnose the staging of bladder cancer and predict the efficacy of neoadjuvant chemotherapy. This system will assist in clinical treatment decision-making.
Eligibility Criteria
Inclusion Criteria: 1. Ultrasound and other imaging examinations (CT, MR, etc.) suggest bladder masses and are suspicious for bladder cancer patients. 2. The bladder is well filled, and no allergic reactions to ultrasound contrast agents are found. 3. No surgery or radiotherapy/chemotherapy has been performed. 4. Patients who meet the indications for surgical resection and are planned for surgical treatment, including one of the following: 1. Clinical symptoms consistent with suspected bladder cancer (such as gross hematuria, etc.); 2. Patients with confirmed primary or recurrent bladder cancer by cystoscopic biopsy; 3. Rapid urine cytology and urine cytology FISH testing suggest malignancy. Exclusion Criteria: 1. Individuals unable to tolerate surgery; 2. Individuals allergic to ultrasound contrast agents, unable to undergo ultrasound contrast examination; 3. Unsuccessful preoperative ultrasound contrast examination or non-compliant patients; 4. Postoperative pathology does not indicate bladder cancer; 5. Patients who have undergone chemotherapy or radiation therapy.
Contact & Investigator
Qiyun Ou, Dr.
PRINCIPAL INVESTIGATOR
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Frequently Asked Questions
Who can join the NCT07051083 clinical trial?
This trial is open to participants of all sexes, studying Bladder Cancer. Full inclusion and exclusion criteria are listed in the Eligibility Criteria section. Always confirm your eligibility with the research team before applying.
Is NCT07051083 currently recruiting?
Yes, NCT07051083 is actively recruiting participants. Contact the research team at ouqy5@mail.sysu.edu.cn for enrollment information.
Where is the NCT07051083 trial being conducted?
This trial is being conducted at Guangzhou, China.
Who is sponsoring the NCT07051083 clinical trial?
NCT07051083 is sponsored by Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University. The principal investigator is Qiyun Ou, Dr. at Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University. The trial plans to enroll 480 participants.
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