Predicting outcomes after bladder cancer surgery using deep learning

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This observational study aims to develop and validate a deep learning radiomics model that utilizes preoperative enhanced CT images to predict postoperative survival outcomes in patients with muscle invasive bladder cancer (MIBC) following radical cystectomy. By analyzing radiomic features from CT scans, the study seeks to improve treatment decision-making and patient prognosis. Eligible participants include those with confirmed MIBC who have undergone a recent contrast-CT scan and have complete clinical data. The study excludes patients who have received neoadjuvant therapy or have poor-quality imaging.

Why it matters

Who can join: the full rules

Inclusion Criteria:

* patients with pathologically confirmed MIBC after radical cystectomy;
* contrast-CT scan less than two weeks before surgery;
* complete CT image data and clinical data.

Exclusion Criteria:

* patients who received neoadjuvant therapy;
* non-urothelial carcinoma;
* poor quality of CT images;
* incomplete clinical and follow-up data.

Where it's running

• Department of Urology, The First Affiliated Hospital of Chongqing Medical University
  Chongqing, Chongqing Municipality, China Recruiting

Study contacts

• Study coordinator: Zongjie Wei
• Email: wzj9846@163.com
• Phone: 023-89012557

Similar studies

Other studies for the same condition or treatment. Recruiting studies are listed first.

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.