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This study aims to evaluate the role of mammographic and sonographic features as non-invasive imaging tools in predicting the molecular subtypes of breast cancer, in correlation with histopathological findings.
Breast cancer is the most prevalent form of cancer among women. In the Middle East, it is the primary reason for cancer-related deaths among women
Breast cancer has been classified into various histopathological and molecular subtypes based on its hormone receptor status. Their biological behaviour and prognosis depend on these hormonal subtypes.
Based on gene expression patterns, breast cancer has been classified into five different molecular subtypes by the St. Gallen International Expert Consensus. They include:
Hence, it is important to establish imaging signatures that can play an adjunct role in predicting these subtypes and assist in pre-treatment planning (4)
Mammography (MG) and Ultrasound (US) are routinely used during breast cancer screening, and are commonly used to identify and characterise breast lesions and guide biopsy. Unlike breast MRI, these two modalities are virtually always and everywhere available at the time of cancer diagnosis. In this work, the investigators thus investigate the feasibility of predicting molecular subtypes of breast cancer from the combination of Mammography and Ultrasound.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Diagnostic test: Ultrasound and Mammogram | Other | Patients will receive digital bilateral mammography (craniocaudal and mediolateral oblique views) followed by high-resolution breast ultrasound using a linear transducer, performed by an experienced radiologist. |
| Measure | Description | Time Frame |
|---|---|---|
| Diagnostic performance of imaging features (Mammogram ,ultrasound ,and combined) for predicting molecular subtypes (Luminal A/B, HER2-enriched, TNBC) | The investigators will use mammographic and songraphic features encompassing morphology, margins, posterior echo, blood flow grading, and the presence or absence of calcification ,predict molecular subtypes, then compare it to the hispathological results. | from imaging to histopathological confirmation (up to 2 weeks) |
| Measure | Description | Time Frame |
|---|---|---|
| -AUC, sensitivity, specificity, accuracy, PPV/NPV for each subtype. -Agreement between imaging-based classification and reference standard (histopathology + IHC): -Cohen's kappa (overall and per subtype). | From imaging to histopathological and immunohistochemical confirmation (up to 2 weeks). |
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Inclusion Criteria:
-The patients having BI-RADS IV, V, VI proven breast cancer.
Exclusion Criteria:
-Patients with post-neoadjuvant therapy and a prior history of breast cancer in the same breast with recurrence.
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The study population consists of 122 women aged 18 years and older with suspected breast lesions referred for diagnostic breast ultrasound and mammography with histopathological confirmation.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Mai Abdelbaset Ahmed | Contact | +201094657457 | Mai.17289680@med.aun.edu.eg |
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| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 33628504 | Background | Shaikh S, Rasheed A. Predicting Molecular Subtypes of Breast Cancer with Mammography and Ultrasound Findings: Introduction of Sono-Mammometry Score. Radiol Res Pract. 2021 Feb 9;2021:6691958. doi: 10.1155/2021/6691958. eCollection 2021. |
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| ID | Term |
|---|---|
| D001943 | Breast Neoplasms |
| ID | Term |
|---|---|
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D001941 | Breast Diseases |
| D012871 | Skin Diseases |
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| D017437 |
| Skin and Connective Tissue Diseases |