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

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT06448897

Enrollment

4000

Registered

2024-06-07

Start date

2024-02-01

Completion date

2025-12-31

Last updated

2024-06-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Artificial Intelligence, Cervical Cancer, Lymph Node Metastasis

Keywords

Cervical Cancer, Lymph Node Metastasis, Artificial Interlligence

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.

Interventions

None listed

Study design

Observational model

OTHER

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

FEMALE

Age

18 Years to 80 Years

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

Design outcomes

Primary

Measure	Time frame	Description
A model for identifying pelvic lymph node metastases on preoperative imaging	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.

Countries

China

Contacts

Primary ContactXin Wu

wuxin_fc@fudan.edu.cn(021)33189900

Outcome results