Ignite Creation Date:
2025-12-24 @ 11:40 PM
Ignite Modification Date:
2025-12-25 @ 9:30 PM
Study NCT ID:
NCT05768451
Status:
UNKNOWN
Last Update Posted:
2023-03-14
First Post:
2022-12-05
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Ultrasound Radiomics for Predicting Breast Cancer and Axillary Lymph Node Metastasis
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D001943', 'term': 'Breast Neoplasms'}], 'ancestors': [{'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D001941', 'term': 'Breast Diseases'}, {'id': 'D012871', 'term': 'Skin Diseases'}, {'id': 'D017437', 'term': 'Skin and Connective Tissue Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'CASE_CONTROL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 200}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2023-04-01', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2023-03', 'completionDateStruct': {'date': '2025-08-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2023-03-13', 'studyFirstSubmitDate': '2022-12-05', 'studyFirstSubmitQcDate': '2023-03-13', 'lastUpdatePostDateStruct': {'date': '2023-03-14', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2023-03-14', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-12-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Accuracy of differential diagnosis between benign and malignant', 'timeFrame': '2022.12.15-2023.12.30', 'description': 'ROC curve, sensitivity, specificity, accuracy, decision curve'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['breast cancer', 'multi-modal ultrasound', 'radiomics'], 'conditions': ['Breast Cancer', 'Axillary Lymph Node Metastasis']}, 'descriptionModule': {'briefSummary': 'The project is proposed based on multimodal ultrasonic imaging omics building used for accurate prediction of the breast cancer and axillary lymph node metastasis load artificial intelligence forecasting model, this method can dig the hidden features of ultrasonic image is not visible to the naked eye, make up the subjectivity in the process of clinical doctors in diagnosis and treatment, provide accurate, objective basis for clinical decision making.'}, 'eligibilityModule': {'sex': 'FEMALE', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '90 Years', 'minimumAge': '18 Years', 'genderBased': True, 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Patients with breast tumors seen in Nanjing Gulou Hospital in September 2018 and later and confirmed by histological pathology were selected, and all patients had complete preoperative US, UE and CEUS examination data.', 'genderDescription': 'Female patients with breast tumors', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* patients who have not received breast puncture biopsy or neoadjuvant chemotherapy, etc. prior to ultrasonography;\n* patients who are not allergic to the ultrasound contrast agent (SonoVue) and have signed an informed consent form for ultrasonography\n* patients with breast tumors who have undergone surgical treatment at our hospital and have complete case histories.\n\nExclusion Criteria:\n\n* patients with incomplete case data;\n* cases with large breast masses that do not completely show the region of interest (ROI);\n* patients who have undergone breast aspiration biopsy or other treatments such as neoadjuvant chemotherapy or endocrine therapy before ultrasound examination.'}, 'identificationModule': {'nctId': 'NCT05768451', 'briefTitle': 'Ultrasound Radiomics for Predicting Breast Cancer and Axillary Lymph Node Metastasis', 'organization': {'class': 'OTHER', 'fullName': 'The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School'}, 'officialTitle': 'Accurate Prediction of Breast Cancer and Axillary Lymph Node Metastasis Burden by Multi-modal Ultrasound-based Radiomics', 'orgStudyIdInfo': {'id': '2022-YXZX-YX-08'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'benign', 'interventionNames': ['Other: Ultrasonic image analysis']}, {'label': 'malignant', 'interventionNames': ['Other: Ultrasonic image analysis']}], 'interventions': [{'name': 'Ultrasonic image analysis', 'type': 'OTHER', 'description': 'Preoperative conventional ultrasound (US), elastic ultrasound (UE) and contrast-enhanced ultrasound (CEUS) images were analyzed. Histopathological results were used as the gold standard. The cases were randomly divided into training set and test set with a ratio of 7:3. The US image, UE image and CEUS image of the maximum long-axis section of each lesion were selected, and the region of interest (ROI) of the lesion was manually delineated.', 'armGroupLabels': ['benign', 'malignant']}]}, 'contactsLocationsModule': {'centralContacts': [{'name': 'baojie wen, doctor', 'role': 'CONTACT', 'email': '359408031@qq.com', 'phone': '02583106666', 'phoneExt': '53500'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}