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NCT06448897 Clinical Trial

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

Cervical Cancer Clinical Trial

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

Clinical Trial Details — Status: Recruiting

Administrative data
NCT number NCT06448897
Other study ID # FUOBGY2024-33
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date February 1, 2024
Est. completion date December 2025

Study information
Verified date June 2024
Source Obstetrics & Gynecology Hospital of Fudan University
Contact Xin Wu
Phone (021)33189900
Email wuxin_fc@fudan.edu.cn
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial 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.

Recruitment information / eligibility
Status Recruiting
Enrollment 4000
Est. completion date December 2025
Est. primary completion date December 2025
Accepts healthy volunteers No
Gender Female
Age group 18 Years to 80 Years
Eligibility Inclusion criteria: 1. patients with preoperative diagnosis of invasive cervical cancer stage I-III, with any type of pathology, and patients who underwent radical/modified radical cervical cancer surgery + pelvic lymph node dissection in our hospital. 2. Age =18 years old and =80 years old 3. patients with complete preoperative pelvic MRI images and postoperative pathology and clinical data in our hospital Exclusion criteria: 1. Patients during pregnancy or breastfeeding, patients within 42 days of abortion 2. Patients who have received neoadjuvant chemotherapy or radiotherapy before surgery for this previous cervical cancer 3. Patients with other malignant tumors within 5 years 4. Combination of other underlying diseases that may lead to enlarged pelvic lymph nodes 5. Imaging report more than 1 month prior to surgery 6. Poor image quality and unrecognizable

Study Design

Related Conditions & MeSH terms

Locations
Country Name City State
China The Obstetrics and Gynecology Hospital of Fudan University Shanghai Shanghai

Sponsors (1)
Lead Sponsor Collaborator
Obstetrics & Gynecology Hospital of Fudan University

Country where clinical trial is conducted

China, 

Outcome
Type Measure Description Time frame Safety issue
Primary A model for identifying pelvic lymph node metastases on preoperative imaging Artificial intelligence (AI) technology was utilized to develop a model for identifying pelvic lymph node metastasis from preoperative images in order to enhance the accuracy of preoperative lymph node metastasis detection in cervical cancer. The model was validated with the main diagnostic focus on determining the status of lymph node metastasis. From enrollment to the end of development of model at 24 months
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