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Contrast-Enhanced Ultrasound-Based Radiomics for the Prediction of Axillary Lymph Nodes Status in Breast Cancer
Haimei Lun1, Mohan Huang2, Yihong Zhao1
1Department of Ultrasound, People's Hospital of Guangxi Zhuang Autonomous Region & Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.
Cancer Reports (Hoboken, N.J.)
|October 18, 2024
Summary
Contrast-enhanced ultrasound (CEUS) radiomics models show promise for noninvasively predicting axillary lymph node (ALN) status in breast cancer patients. These models achieved 71.3% accuracy in identifying lymph node metastasis, aiding clinical decisions.
Area of Science:
- Radiology
- Oncology
- Medical Imaging
Background:
- Breast cancer is a leading cause of cancer death in women.
- Axillary lymph node (ALN) metastasis is common and critical for treatment decisions.
- Accurate, noninvasive assessment of ALN status is clinically important.
Purpose of the Study:
- To develop and validate contrast-enhanced ultrasound (CEUS)-based radiomics models.
- To predict the status of axillary lymph nodes (ALN) noninvasively before treatment.
- To improve medical decision-making for breast cancer patients.
Main Methods:
- Retrospective analysis of clinical data and pretreatment CEUS images (May 2015 - July 2021).
- Radiomics signatures were built using feature selection (mRMR, stepwise logistic regression) and logistic regression.
- Model performance was evaluated using confusion matrix and ROC analysis (AUC 0.713).
Main Results:
- CEUS-based radiomics models with six features were developed.
- The models achieved an area under the ROC curve (AUC) of 0.713 in the test set.
- This indicates predictive accuracy for lymph node metastasis.
Conclusions:
- CEUS-based radiomics shows potential as a reliable noninvasive tool.
- This approach can aid in predicting axillary lymph node (ALN) status.
- Further development could enhance its clinical utility in breast cancer management.
