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Recruiting NCT06840418

Exploratory Study on NIRFI Technology Combined with ICG Guided Cervical Cancer Lymph Node Metastasis

No phase Interventional Uterine Cervical Neoplasms

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: Indocyanine green (ICG) injection for intraoperative lymph node imaging.
Who it may be relevant to
Registry conditions: Uterine Cervical Neoplasms. Basic parameters: 18 years — 75 years · Female.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
China
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

Exploratory Study on Near-Infrared Fluorescence Imaging Technology Combined with Indocyanine Green Guided Cervical Cancer Lymph Node Metastasis

Overview

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.

Interventions

  • Drug Indocyanine green (ICG) injection for intraoperative lymph node imaging
    Injection is performed at the 3 o'clock and 9 o'clock positions of the cervix, with 1 ml on each side, for a total dose of 2 ml. Injection depth: The tracer is injected into the superficial (2 mm) and deep (1 cm) layers, with the superficial injection performed first, followed by the deep injection.

Primary outcome measures

  • The sensitivity of lymph node metastasis fluorescence imaging(Signal-to-Background Ratio). [Time frame: The time frame was from subject enrollment until surgical pathology results were obtained. The time between subject enrollment and the availability of surgical pathology results was approximately 1 to 1.5 months.]

Eligibility criteria

Inclusion criteria

  • Patients with primary cervical cancer stages I to III, with no restrictions on pathological type.
  • Age ≥18 years old and ≤75 years old.
  • Patients who have undergone radical hysterectomy/modified radical hysterectomy (referring to the Q-M surgery classification, with surgical methods of type B and type C) + pelvic lymph node dissection.
  • Patients with complete preoperative clinical and postoperative pathological data.
  • Normal liver and kidney function and within the normal range of blood routine tests (specific details are as follows): Hemoglobin >60 g/L; Platelets >70 \* 10\^9/L; White blood cells >3 \* 10\^9/L; Creatinine <50 mg/dL; Abnormal liver enzyme indicators ≤3 items; The highest value of liver enzymes does not exceed three times the corresponding normal value.
  • No history of other malignant tumors within 5 years.
  • Not pregnant.
  • Performance status: Karnofsky score ≥60 points or ECOG score 0 to 1 points.
  • Volunteers who willingly join this study, sign the informed consent form, have good compliance, and cooperate with follow-up visits.
  • No mental illness or other serious infectious diseases or immune system diseases (such as lupus erythematosus, myasthenia gravis, HIV infection, etc.)

Exclusion criteria

  • Patients with allergies to ICG or iodine. Individuals with contraindications to various surgeries who cannot undergo surgery.
  • Patients with recurrent cervical cancer.
  • Patients who have participated in other clinical trials within the past 3 months.
  • Other conditions deemed unsuitable for inclusion in this study by the 5.investigator, or patients with other underlying diseases that may confound the study results.

6.Patients who are assessed preoperatively as having systemic and organ conditions that are unlikely to tolerate surgery.

7.Patients or guardians who are unwilling or unable to provide written informed consent or comply with subsequent follow-up requirements.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation
N/A
Model
Single group
Masking
Open label
Primary purpose
Treatment

Study locations

China · 1 center
  • The Obstetrics and Gynecology Hospital of Fudan University — Shanghai

Identifiers

NCT: NCT06840418 · FUOBGY-2024-224

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗