Ignite Creation Date:
2025-12-25 @ 4:52 AM
Ignite Modification Date:
2026-01-05 @ 7:24 PM
Study NCT ID:
NCT06840418
Status:
RECRUITING
Last Update Posted:
2025-02-21
First Post:
2025-02-17
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Exploratory Study on NIRFI Technology Combined with ICG Guided Cervical Cancer Lymph Node Metastasis
Sponsor:
Obstetrics & Gynecology Hospital of Fudan University
Organization:
Study Overview
Official Title:
Exploratory Study on Near-Infrared Fluorescence Imaging Technology Combined with Indocyanine Green Guided Cervical Cancer Lymph Node Metastasis
Status:
RECRUITING
Status Verified Date:
2025-02
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
The goal of this exploratory study is to exploring the lymph node metastasis, tumor margin, blood vessels, ureters, and nerve imaging in cervical cancer surgery using near-infrared fluorescence imaging technology combined with indocyanine green, and establishing an artificial intelligence model for predicting lymph node metastasis of cervical cancer to guide the advancement of refined surgical procedures.And the focus of this study is to investigate the situation of pelvic lymph node metastasis.The sole medication used in this experiment is the fluorescent contrast agent that has been clinically used for over 40 years - Indocyanine Green (ICG).Subsequent pathology results after the surgery will be used as the gold standard to determine the detection rate of lymph node metastasis and the accuracy of the complete resection rate of the surgical margin in cervical cancer.The researchers will also follow up on the quality of life of patients after the surgery.
The main question it aims to answer is:
can artificial intelligence multimodal fusion prediction models improve the accuracy of preoperative diagnosis of pelvic lymph node metastasis in cervical cancer? The researchers compared the AI multimodal fusion prediction model with traditional imaging physician assessments to see if the prediction model could yield more accurate lymph node metastasis determinations. Participants will undergo pelvic MRI after pathologically confirming a diagnosis of cervical cancer, and the results will be used to determine pelvic lymph node metastasis status by the predictive model and the imaging physician, respectively. Subsequent pathology results after surgical lymph node clearance will be used as the gold standard to determine the accuracy of the two preoperative lymph node diagnostic modalities.
The main question it aims to answer is:
can artificial intelligence multimodal fusion prediction models improve the accuracy of preoperative diagnosis of pelvic lymph node metastasis in cervical cancer? The researchers compared the AI multimodal fusion prediction model with traditional imaging physician assessments to see if the prediction model could yield more accurate lymph node metastasis determinations. Participants will undergo pelvic MRI after pathologically confirming a diagnosis of cervical cancer, and the results will be used to determine pelvic lymph node metastasis status by the predictive model and the imaging physician, respectively. Subsequent pathology results after surgical lymph node clearance will be used as the gold standard to determine the accuracy of the two preoperative lymph node diagnostic modalities.
Detailed Description:
None
Study Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
False
Is an FDA AA801 Violation?: