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

June 3, 2024 updated by: Obstetrics & Gynecology Hospital of Fudan University
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.

Study Overview

Status

Recruiting

Conditions

Study Type

Observational

Enrollment (Estimated)

4000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • China
    • Shanghai
      • Shanghai, Shanghai, China, 200090
        • Recruiting
        • The Obstetrics and Gynecology Hospital of Fudan University
        • Contact:
        • Principal Investigator:
          • Xin Wu
        • Sub-Investigator:
          • Hua Jiang
        • Sub-Investigator:
          • Xuan Yin
        • Sub-Investigator:
          • Ling Qiu
        • Sub-Investigator:
          • Hui Wang
        • Sub-Investigator:
          • Yang Liu
        • Sub-Investigator:
          • Shen Luo
        • Sub-Investigator:
          • Xiaomei Sun

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Probability Sample

Study Population

All patient information and imaging data were collected from the Obstetrics and Gynecology Hospital of Fudan University. This hospital is a specialized tertiary care facility and is recognized as the leading Obstetrics and Gynecology hospital in China.

Description

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 Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
A model for identifying pelvic lymph node metastases on preoperative imaging
Time Frame: From enrollment to the end of development of model at 24 months
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

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Obstetrics & Gynecology Hospital of Fudan University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

February 1, 2024

Primary Completion (Estimated)

December 1, 2025

Study Completion (Estimated)

December 1, 2025

Study Registration Dates

First Submitted

June 3, 2024

First Submitted That Met QC Criteria

June 3, 2024

First Posted (Actual)

June 7, 2024

Study Record Updates

Last Update Posted (Actual)

June 7, 2024

Last Update Submitted That Met QC Criteria

June 3, 2024

Last Verified

June 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • FUOBGY2024-33

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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