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

NCT ID: NCT06448897

Last Updated: 2024-06-07

Basic Information

• Recruitment Status: RECRUITING
• Total Enrollment: 4000 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2024-02-01
• Study Completion Date: 2025-12-31

Brief 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.

Conditions

Cervical Cancer; Lymph Node Metastasis; Artificial Intelligence

Study Design

• Observational Model Type: OTHER
• Study Time Perspective: RETROSPECTIVE

Eligibility Criteria

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

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 80 Years
• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: No

Sponsors

Obstetrics & Gynecology Hospital of Fudan University

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

The Obstetrics and Gynecology Hospital of Fudan University

Shanghai, Shanghai Municipality, China

Site Status: RECRUITING

Countries

China

Central Contacts

Xin Wu

Role: CONTACT

wuxin_fc@fudan.edu.cn

(021)33189900

Facility Contacts

Xin Wu

Role: primary

wuxin_fc@fudan.edu.cn

8613764046908

Other Identifiers

FUOBGY2024-33

Identifier Type: -

Identifier Source: org_study_id