Ultrasound Radiomics for Predicting Breast Cancer and Axillary Lymph Node Metastasis

Study Overview
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Brief Summary
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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.

Official Title
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Accurate Prediction of Breast Cancer and Axillary Lymph Node Metastasis Burden by Multi-modal Ultrasound-based Radiomics

Conditions
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Breast Cancer, Axillary Lymph Node Metastasis

Intervention / Treatment
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* Other: Ultrasonic image analysis


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: patients who have not received breast puncture biopsy or neoadjuvant chemotherapy, etc. prior to ultrasonography; patients who are not allergic to the ultrasound contrast agent (SonoVue) and have signed an informed consent form for ultrasonography patients with breast tumors who have undergone surgical treatment at our hospital and have complete case histories. Exclusion Criteria: patients with incomplete case data; cases with large breast masses that do not completely show the region of interest (ROI); patients who have undergone breast aspiration biopsy or other treatments such as neoadjuvant chemotherapy or endocrine therapy before ultrasound examination.

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 90 Years

Sexes Eligible for Study
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Female

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| benign<br> | Other: Ultrasonic image analysis<br>* 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.<br>|
| malignant<br> | Other: Ultrasonic image analysis<br>* 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.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Accuracy of differential diagnosis between benign and malignant | ROC curve, sensitivity, specificity, accuracy, decision curve | 2022.12.15-2023.12.30 | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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breast cancer, multi-modal ultrasound, radiomics