Development and Prospective Validation of a Multimodal Fusion Artificial Intelligence Model for Predicting the Efficacy of Neoadjuvant Treatment of Bladder Cancer

Launched by SUN YAT-SEN MEMORIAL HOSPITAL OF SUN YAT-SEN UNIVERSITY · Apr 1, 2025

Keywords

ClinConnect Summary

This clinical trial is studying a new artificial intelligence (AI) model designed to help doctors predict how well bladder cancer patients will respond to a specific treatment called neoadjuvant therapy, which is given before surgery. The researchers will collect information from about 130 patients who have been diagnosed with bladder cancer and have undergone imaging tests, such as scans, to gather data that will help build and test this AI model. The goal is to improve how doctors assess treatment effectiveness, aiming for better diagnosis and outcomes for patients.

To be eligible for the trial, participants must have confirmed bladder cancer and planned to receive neoadjuvant therapy followed by surgery. Unfortunately, those who haven’t had the required imaging tests or have received other treatments for bladder cancer won’t be able to join. Participants can expect to have their imaging and clinical data analyzed as part of this study, which could lead to advancements in how bladder cancer is treated in the future.

Gender

ALL

Eligibility criteria

• Inclusion Criteria:
• • Bladder occupying lesions, with histopathological confirmation of bladder cancer after resection.
• • Planned neoadjuvant therapy and radical cystectomy.
• Exclusion Criteria:
• • Patients who have not undergone standard bladder imaging examinations or have missing imaging or pathological data.
• • Patients who have received local treatments (such as interventional embolization) or systemic treatments (such as radiotherapy, chemotherapy, immunotherapy, or targeted therapy).
• • Poor quality of imaging or pathological images.