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

Obstetrics & Gynecology Hospital of Fudan University

Status: Enrolling

Conditions: Lymph Node Metastasis; Artificial Intelligence; Cervical Cancer

Study type: Observational

Funder types: Other

Identifiers

NCT06448897

FUOBGY2024-33

Details and patient eligibility

About

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.

Enrollment: 4,000 estimated patients

Sex: Female

Ages: 18 to 80 years old

Volunteers: No Healthy Volunteers

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