Actively Recruiting
Development of an Imaging Prediction Model for Pelvic Lymph Node Metastasis of Cervical Cancer Using Artificial Intelligence Techniques
Led by Obstetrics & Gynecology Hospital of Fudan University · Updated on 2024-06-07
4000
Participants Needed
1
Research Sites
N/A
Total Duration
On this page
AI-Summary
What this Trial Is About
Researchers are conducting a retrospective exploratory study at a single center to develop and validate a model that uses artificial intelligence deep learning to predict pelvic lymph node metastasis in patients with cervical cancer. This model is trained using preoperative pelvic MRI images combined with postoperative pathological and clinical data. The goal is to improve the accuracy of predicting lymphatic metastasis before surgery and to provide valuable information to guide treatment decisions. The study involves analyzing existing data from patients diagnosed with invasive cervical cancer stages I to III who underwent radical or modified radical cervical cancer surgery with pelvic lymph node dissection. The model development will use imaging and pathology findings collected from these patients, focusing on preoperative pelvic MRI scans and postoperative pathology reports. The study period for model development spans 24 months from enrollment. Participants will not receive any new treatments as this is an observational study using existing clinical data. Researchers will review imaging and pathology results to build and test the prediction model. The primary outcome measured is the accuracy of the model in identifying pelvic lymph node metastases from preoperative imaging. The study will conclude after the model development phase is complete, with no direct intervention or follow-up required from participants.
CONDITIONS
Brief Title
Development of an Imaging Prediction Model for Pelvic Lymph Node Metastasis of Cervical Cancer Using Artificial Intelligence Techniques.
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Patients with preoperative diagnosis of invasive cervical cancer stage I-III, any pathology type, who underwent radical or modified radical cervical cancer surgery with pelvic lymph node dissection at the hospital
- Age 18 years or older and 80 years or younger
- Patients with complete preoperative pelvic MRI images and postoperative pathology and clinical data available at the hospital
You will not qualify if you...
- Patients who are pregnant or breastfeeding, or within 42 days of abortion
- Patients who received neoadjuvant chemotherapy or radiotherapy before surgery for cervical cancer
- Patients with other malignant tumors within the past 5 years
- Patients with other underlying diseases that cause pelvic lymph node enlargement
- Imaging reports dated more than 1 month before surgery
- Poor quality or unrecognizable imaging
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Your Study Journey
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person)
Duration - Up to 1 month before surgery
Participants undergo preoperative pelvic MRI imaging and clinical data collection to develop an imaging prediction model.
1 to 2 visits depending on imaging availability
Duration - Up to 24 months
Participants are monitored through data analysis for development of the imaging prediction model.
No additional visits; data is collected from existing clinical records
Trial Site Locations
Total: 1 location
1
The Obstetrics and Gynecology Hospital of Fudan University
Shanghai, Shanghai Municipality, China, 200090
Actively Recruiting
Research Team
X
Xin Wu
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
0
Similar Trials
Frequently Asked Questions
Have more questions? Get in touch with our team for quick support
Not the Right Trial for You?
Explore thousands of other clinical trials that might be a better match.
Sign up to get personalized trial recommendations delivered to your inbox.
Already have an account? Log in here