AI-Based Imaging Model for Bladder Cancer Prediction

Launched by THIRD AFFILIATED HOSPITAL, SUN YAT-SEN UNIVERSITY · May 30, 2024

Keywords

ClinConnect Summary

This clinical trial is focused on developing a new way to predict bladder cancer using advanced imaging techniques. Specifically, researchers are creating a model that uses CT scans and deep learning algorithms to identify tumor budding, which is an important indicator of how aggressive the cancer might be. The goal is to help doctors assess patients' conditions before surgery, allowing them to create more tailored treatment plans that can improve outcomes for patients.

To participate in this study, patients should be between the ages of 65 and 74 and have been treated for bladder cancer between January 2014 and January 2023. They must have undergone a specific type of surgery called transurethral resection of bladder tumor (TURBT) or radical cystectomy, and their medical records must include complete information about their condition and CT scans. Patients with prior surgeries for bladder cancer at other hospitals or those with other pelvic cancers may not be eligible. If you join this trial, you can expect to contribute to important research that could enhance how bladder cancer is treated in the future.

Gender

ALL

Eligibility criteria

• Inclusion Criteria:
• • 1. Bladder cancer patients treated from January 1, 2014, to January 1, 2023;
• • 2. Hospitalized and underwent transurethral resection of bladder tumor (TURBT) or radical cystectomy;
• • 3. Complete clinical, preoperative CT, and pathological data.
• Exclusion Criteria:
• • 1. Patients who previously underwent surgical treatment for bladder cancer at other centers, making it difficult to obtain their preoperative data;
• • 2. Patients with other concurrent pelvic or urinary system malignancies;
• • 3. Patients with poor quality, low resolution, or faded CT or pathological images.