NCT07051083Recruiting
Bladder Cancer Staging and Prediction of New Adjuvant Chemotherapy Efficacy Based on Deep Learning and Transfer Learning in Ultrasound-Magnetic Resonance-Pathology Multimodal Multiscale
Intelligent Diagnosis of Bladder Cancer Staging and Prediction of New Adjuvant Chemotherapy Efficacy Based on Deep Learning and Transfer Learning in Ultrasound-Magnetic Resonance-Pathology Multimodal Multiscale
Source: ClinicalTrials.gov · Last updated 3 Jul 2025 · Not updated for over 12 months - ask the site whether it is still open
Brief summary (registry, in English)
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.
- Status (registry)
- Recruiting
- Study type
- Observational
- Enrollment
- 480 (estimated)
- First submitted
- 6 Jan 2024
- Start date
- 1 Jan 2024
- Primary completion date
- 31 Dec 2026
- Lead sponsor
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
- Diseases
- Bladder cancer, Childhood cancers
- NCT number
- NCT07051083
What you commit to
- Study type: Observational
- Planned participants: 480
- From 1 Jan 2024 to the primary completion date, 31 Dec 2026
- 1 site in 1 country
- Visits and tests: ask the trial team, the registry does not list them
Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.
Who cannot take part
Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.
Prior treatment
- Individuals unable to tolerate surgery;
- Patients who have undergone chemotherapy or radiation therapy.
Other illness
- Individuals allergic to ultrasound contrast agents, unable to undergo ultrasound contrast examination;
- Postoperative pathology does not indicate bladder cancer;
Other
- Unsuccessful preoperative ultrasound contrast examination or non-compliant patients;
Who the study is looking for
- Ultrasound and other imaging examinations (CT, MR, etc.) suggest bladder masses and are suspicious for bladder cancer patients.
- The bladder is well filled, and no allergic reactions to ultrasound contrast agents are found.
- No surgery or radiotherapy/chemotherapy has been performed.
- Patients who meet the indications for surgical resection and are planned for surgical treatment, including one of the following:
- Clinical symptoms consistent with suspected bladder cancer (such as gross hematuria, etc.);
- Patients with confirmed primary or recurrent bladder cancer by cystoscopic biopsy;
- Rapid urine cytology and urine cytology FISH testing suggest malignancy.
Sex: All · Does not accept healthy volunteers
Sites (1)
Sites in registry order. Pick your city on the disease page to sort them by distance.
| Site | City | Country | Site status |
|---|---|---|---|
| Sun Yat-sen Memorial Hospital, Sun Yat-sen University Coordinator of this site? Confirm its status | Guangzhou | China | Recruiting |
This page is information, not medical advice. Discuss any trial with your doctor.