Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D002583', 'term': 'Uterine Cervical Neoplasms'}], 'ancestors': [{'id': 'D014594', 'term': 'Uterine Neoplasms'}, {'id': 'D005833', 'term': 'Genital Neoplasms, Female'}, {'id': 'D014565', 'term': 'Urogenital Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D002577', 'term': 'Uterine Cervical Diseases'}, {'id': 'D014591', 'term': 'Uterine Diseases'}, {'id': 'D005831', 'term': 'Genital Diseases, Female'}, {'id': 'D052776', 'term': 'Female Urogenital Diseases'}, {'id': 'D005261', 'term': 'Female Urogenital Diseases and Pregnancy Complications'}, {'id': 'D000091642', 'term': 'Urogenital Diseases'}, {'id': 'D000091662', 'term': 'Genital Diseases'}]}, 'interventionBrowseModule': {'meshes': [{'id': 'D007208', 'term': 'Indocyanine Green'}, {'id': 'D007267', 'term': 'Injections'}], 'ancestors': [{'id': 'D007211', 'term': 'Indoles'}, {'id': 'D006574', 'term': 'Heterocyclic Compounds, 2-Ring'}, {'id': 'D000072471', 'term': 'Heterocyclic Compounds, Fused-Ring'}, {'id': 'D006571', 'term': 'Heterocyclic Compounds'}, {'id': 'D004333', 'term': 'Drug Administration Routes'}, {'id': 'D004358', 'term': 'Drug Therapy'}, {'id': 'D013812', 'term': 'Therapeutics'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'NA', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'TREATMENT', 'interventionModel': 'SINGLE_GROUP'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 15}}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2025-01-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-02', 'completionDateStruct': {'date': '2027-12', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-02-17', 'studyFirstSubmitDate': '2025-02-17', 'studyFirstSubmitQcDate': '2025-02-17', 'lastUpdatePostDateStruct': {'date': '2025-02-21', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-02-21', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2027-12', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'The sensitivity of lymph node metastasis fluorescence imaging(Signal-to-Background Ratio).', 'timeFrame': '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.'}]}, 'oversightModule': {'isUsExport': False, 'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Uterine Cervical Neoplasms']}, 'descriptionModule': {'briefSummary': '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.\n\nThe main question it aims to answer is:\n\ncan 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.'}, 'eligibilityModule': {'sex': 'FEMALE', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '75 Years', 'minimumAge': '18 Years', 'genderBased': True, 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n1. Patients with primary cervical cancer stages I to III, with no restrictions on pathological type.\n2. Age ≥18 years old and ≤75 years old.\n3. 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.\n4. Patients with complete preoperative clinical and postoperative pathological data.\n5. 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.\n6. No history of other malignant tumors within 5 years.\n7. Not pregnant.\n8. Performance status: Karnofsky score ≥60 points or ECOG score 0 to 1 points.\n9. Volunteers who willingly join this study, sign the informed consent form, have good compliance, and cooperate with follow-up visits.\n10. No mental illness or other serious infectious diseases or immune system diseases (such as lupus erythematosus, myasthenia gravis, HIV infection, etc.)\n\nExclusion Criteria:\n\n1. Patients with allergies to ICG or iodine. Individuals with contraindications to various surgeries who cannot undergo surgery.\n2. Patients with recurrent cervical cancer.\n3. Patients who have participated in other clinical trials within the past 3 months.\n4. 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.\n\n6.Patients who are assessed preoperatively as having systemic and organ conditions that are unlikely to tolerate surgery.\n\n7.Patients or guardians who are unwilling or unable to provide written informed consent or comply with subsequent follow-up requirements.'}, 'identificationModule': {'nctId': 'NCT06840418', 'briefTitle': 'Exploratory Study on NIRFI Technology Combined with ICG Guided Cervical Cancer Lymph Node Metastasis', 'organization': {'class': 'OTHER', 'fullName': 'Obstetrics & Gynecology Hospital of Fudan University'}, 'officialTitle': 'Exploratory Study on Near-Infrared Fluorescence Imaging Technology Combined with Indocyanine Green Guided Cervical Cancer Lymph Node Metastasis', 'orgStudyIdInfo': {'id': 'FUOBGY-2024-224'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Lymph node metastasis fluorescence imaging group', 'interventionNames': ['Drug: Indocyanine green (ICG) injection for intraoperative lymph node imaging']}], 'interventions': [{'name': 'Indocyanine green (ICG) injection for intraoperative lymph node imaging', 'type': 'DRUG', 'description': "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.", 'armGroupLabels': ['Lymph node metastasis fluorescence imaging group']}]}, 'contactsLocationsModule': {'locations': [{'zip': '200090', 'city': 'Shanghai', 'state': 'Shanghai Municipality', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Wu Xin', 'role': 'CONTACT', 'email': 'wuxin_fc@fudan.edu.cn', 'phone': '86-02133189900', 'phoneExt': '8613764046908'}], 'facility': 'The Obstetrics and Gynecology Hospital of Fudan University', 'geoPoint': {'lat': 31.22222, 'lon': 121.45806}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Obstetrics & Gynecology Hospital of Fudan University', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}