Volume 43, Issue 12 pp. 2311-2324

Original Article

Spectral Ultrasound Combined With Clinical Pathological Parameters in Prediction of Axillary Lymph Node Metastasis in Breast Cancer

Pengfei Sun MS,

Pengfei Sun MS

Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China

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Jiaqi Han MS,

Jiaqi Han MS

School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China

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Min Li PhD,

Min Li PhD

Clinical Epidemiology and EBM Unit, Beijing Friendship Hospital, Capital Medical University, Beijing Clinical Research Institute, Beijing, China

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Zhixiang Wang PhD,

Zhixiang Wang PhD

Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China

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Ruifang Guo PhD,

Ruifang Guo PhD

Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China

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Yanning Zhang PhD,

Yanning Zhang PhD

Department of Pathology, Beijing Friendship Hospital, Capital Medical University, Beijing, China

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Linxue Qian PhD,

Linxue Qian PhD

orcid.org/0000-0001-7116-0608

Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China

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Jianguo Ma PhD,

Corresponding Author

Jianguo Ma PhD

[email protected]

orcid.org/0000-0002-7522-1014

School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China

Address correspondence to Jianguo Ma, PhD, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China.

E-mail: [email protected]

Xiangdong Hu, PhD, Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, No. 95, Yong An Road, Xicheng District, Beijing 100050, China.

E-mail: [email protected]

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Xiangdong Hu PhD,

Corresponding Author

Xiangdong Hu PhD

[email protected]

orcid.org/0000-0003-4841-4264

Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China

Address correspondence to Jianguo Ma, PhD, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China.

E-mail: [email protected]

Xiangdong Hu, PhD, Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, No. 95, Yong An Road, Xicheng District, Beijing 100050, China.

E-mail: [email protected]

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Pengfei Sun MS,

Pengfei Sun MS

Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China

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Jiaqi Han MS,

Jiaqi Han MS

School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China

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Min Li PhD,

Min Li PhD

Clinical Epidemiology and EBM Unit, Beijing Friendship Hospital, Capital Medical University, Beijing Clinical Research Institute, Beijing, China

Search for more papers by this author

Zhixiang Wang PhD,

Zhixiang Wang PhD

Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China

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Ruifang Guo PhD,

Ruifang Guo PhD

Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China

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Yanning Zhang PhD,

Yanning Zhang PhD

Department of Pathology, Beijing Friendship Hospital, Capital Medical University, Beijing, China

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Linxue Qian PhD,

Linxue Qian PhD

orcid.org/0000-0001-7116-0608

Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China

Search for more papers by this author

Jianguo Ma PhD,

Corresponding Author

Jianguo Ma PhD

[email protected]

orcid.org/0000-0002-7522-1014

School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China

Address correspondence to Jianguo Ma, PhD, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China.

E-mail: [email protected]

Xiangdong Hu, PhD, Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, No. 95, Yong An Road, Xicheng District, Beijing 100050, China.

E-mail: [email protected]

Search for more papers by this author

Xiangdong Hu PhD,

Corresponding Author

Xiangdong Hu PhD

[email protected]

orcid.org/0000-0003-4841-4264

Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China

Address correspondence to Jianguo Ma, PhD, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China.

E-mail: [email protected]

Xiangdong Hu, PhD, Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, No. 95, Yong An Road, Xicheng District, Beijing 100050, China.

E-mail: [email protected]

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First published: 04 September 2024

https://doi.org/10.1002/jum.16564

Citations: 1

Pengfei Sun and Jiaqi Han contributed equally to this work.

This work was supported by the Capital's Funds for Health Improvement and Research (No. 2022-4-1105) to Pengfei Sun, and National Natural Science Foundation of China (62371027, 61901021) to Jianguo Ma. We express our sincere gratitude to the patients who participated in this study.

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Abstract

Objectives

To explore the clinical value of the nomogram based on spectral Doppler ultrasound combined with clinical pathological parameter in predicting axillary lymph node metastasis in breast cancer.

Methods

We prospectively gathered clinicopathologic and ultrasonic data from 240 patients confirmed breast cancer. The risk factors of axillary lymph node metastasis were analyzed by univariate and multivariate logistic regression, and the prediction model was established. The model calibration, predictive ability, and diagnostic efficiency in the training set and the testing set were analyzed by receiver operating characteristic curve and calibration curve analysis, respectively.

Results

Univariate analysis showed that lymph node metastasis was related with tumor size, Ki-67, axillary ultrasound, ultrasound spectral quantitative parameter, internal echo, and calcification (P < .05). Multivariate logistic regression analysis showed that the Ki-67, axillary ultrasound, quantitative parameter (the mean of the mid-band fit in tumor and posterior tumor) were independent risk factors of axillary lymph node metastasis (P < .05). The models developed using Ki-67, axillary ultrasound, and quantitative parameters for predicting axillary lymph node metastasis demonstrated an area under the receiver operating characteristic curve of 0.83. Additionally, the prediction model exhibited outstanding predictability for axillary lymph node metastasis, as evidenced by a Harrell C-index of 0.83 (95% confidence interval 0.73–0.93).

Conclusion

Axillary ultrasound combined with Ki-67 and spectral ultrasound parameters has the potential to predict axillary lymph node metastasis in breast cancer, which is superior to axillary ultrasound alone.

Open Research

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

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Citing Literature

Volume43, Issue12

December 2024

Pages 2311-2324

Spectral Ultrasound Combined With Clinical Pathological Parameters in Prediction of Axillary Lymph Node Metastasis in Breast Cancer

Abstract

Objectives

Methods

Results

Conclusion

Open Research

Data Availability Statement

References

Citing Literature

References

Information

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Spectral Ultrasound Combined With Clinical Pathological Parameters in Prediction of Axillary Lymph Node Metastasis in Breast Cancer

Abstract

Objectives

Methods

Results

Conclusion

Open Research

Data Availability Statement

References

Citing Literature

References

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