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

NCT06909643 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 550

Last updated 2025-04-03

No results posted yet for this study

Summary

This study is a multi-center observational study without interventions, including the construction of an AI diagnostic model and retrospective testing of a multi-center cohort. The study participants are bladder cancer patients who have undergone imaging examinations, been pathologically diagnosed, and received neoadjuvant treatment, with complete clinical and pathological data. The study plans to enroll 130 patients from our center, collecting corresponding imaging images, and gathering clinical and genomic data to build and internally validate a multimodal AI model. The model's generalization and robustness will be tested to explore the association between multimodal data and the efficacy of neoadjuvant treatment for bladder cancer. The aim is to assist clinicians in predicting and evaluating the efficacy of neoadjuvant treatment for bladder cancer, with the goal of improving patient diagnosis, treatment outcomes, and prognosis.

Conditions

Interventions

DIAGNOSTIC_TEST

Artificial intelligence (AI)-based diagnostic model

Collect magnetic resonance imaging and pathological slides of resected tumor of the enrolled patients. Analyze the data using the AI model to generate diagnostic results (sensitive or insensitive to the neoadjavant therapy). No intervention to patients would be performed in this diagnostic test study.

Sponsors & Collaborators

  • Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-01-01
Primary Completion
2025-12-31
Completion
2025-12-31

Countries

  • China

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06909643 on ClinicalTrials.gov