RecruitingNCT06448897

Development of an Imaging Prediction Model for Pelvic Lymph Node Metastasis of Cervical Cancer Using Artificial Intelligence Techniques.


Sponsor

Obstetrics & Gynecology Hospital of Fudan University

Enrollment

4,000 participants

Start Date

Feb 1, 2024

Study Type

OBSERVATIONAL

Conditions

Summary

This study is a retrospective exploratory trial conducted at a single center, aiming to develop and validate a preoperative lymphatic metastasis model for cervical cancer using artificial intelligence deep learning. The model is trained using preoperative imaging and postoperative pathological findings of cervical cancer patients, with the goal of enhancing the accuracy of lymphatic metastasis prediction through preoperative imaging and offering insights for treatment decisions.


Eligibility

Sex: FEMALEMin Age: 18 YearsMax Age: 80 Years

Plain Language Summary

Simplified for easier understanding

This study uses artificial intelligence (AI) to analyze MRI images and develop a model that can predict whether cervical cancer has spread to nearby pelvic lymph nodes — without invasive procedures. The data comes from patients who already underwent surgery. **You may be eligible if...** - You are between 18 and 80 years old - You were diagnosed with invasive cervical cancer (stage I–III) - You had radical surgery including pelvic lymph node removal - You had a full pelvic MRI scan and your pathology and clinical data are complete **You may NOT be eligible if...** - You were pregnant or within 42 days of an abortion at the time of surgery - You received chemotherapy or radiation before surgery - Your imaging or clinical data is incomplete Talk to your doctor to see if this trial is right for you.

This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.

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Locations(1)

The Obstetrics and Gynecology Hospital of Fudan University

Shanghai, Shanghai Municipality, China

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NCT06448897


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