Diagnostic value of multimodal ultrasound for breast cancer and prediction of sentinel lymph node metastases

Hui Li ¹, Lixia Chen ¹, Meikuai Liu ¹

⁰Department of Ultrasound Imaging, The First Affiliated Hospital of Wenzhou Medical University, New District of the First Affiliated Hospital of Wenzhou Medical University, Wenzhou City, China.

Frontiers in Cell and Developmental Biology +

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September 20, 2024

View abstract on PubMed

Summary

A new Lasso regression model using multimodal ultrasound accurately predicts sentinel lymph node metastasis in breast cancer. This advancement aids in better prognosis and treatment planning for breast cancer patients.

Area Of Science

Oncology
Medical Imaging

Background

Sentinel lymph node metastasis (SLNM) is crucial for breast cancer (BC) prognosis and treatment planning.
Accurate SLNM prediction is essential for improving patient outcomes.

Purpose Of The Study

To develop a Lasso regression model integrating multimodal ultrasound (US) techniques.
To enhance the predictive accuracy of SLNM in breast cancer.
To provide precise clinical treatment guidance.

Main Methods

Utilized multimodal ultrasound techniques: standard US, shear wave elastography (SWE), and contrast-enhanced ultrasound (CEUS).
Constructed a Lasso regression model incorporating these US modalities.
Evaluated model performance in diagnosing benign/malignant nodules and SLNM.

Main Results

The Lasso model achieved an AUC of 0.966 for diagnosing benign and malignant nodules.
The model demonstrated an AUC of 0.832 for diagnosing SLNM.
Significant differences were observed between benign and malignant groups across various clinical and imaging features.

Conclusions

A validated Lasso regression model based on multimodal US effectively predicts SLNM in breast cancer.
The developed model exhibits high diagnostic accuracy for SLNM prediction.

Keywords:

LASSO regression breast cancer contrast-enhanced ultrasound lymph node metastases multimodal ultrasound shear wave elastography