LI Tingting, XUE Jiping, SU Lili. Prediction of axillary lymph node metastasis by shear wave elastography and conventional ultrasound features of breast cancer and model establishment[J]. Journal of Clinical Medicine in Practice, 2023, 27(5): 11-15. DOI: 10.7619/jcmp.20221769
Citation: LI Tingting, XUE Jiping, SU Lili. Prediction of axillary lymph node metastasis by shear wave elastography and conventional ultrasound features of breast cancer and model establishment[J]. Journal of Clinical Medicine in Practice, 2023, 27(5): 11-15. DOI: 10.7619/jcmp.20221769

Prediction of axillary lymph node metastasis by shear wave elastography and conventional ultrasound features of breast cancer and model establishment

More Information
  • Received Date: June 06, 2022
  • Revised Date: September 15, 2022
  • Available Online: April 06, 2023
  • Objective 

    To explore the predictive value of shear wave elastography (SWE) quantitative parameters and conventional ultrasound features of primary lesions for axillary lymph node metastasis (ALNM) in breast cancer, and to construct a preoperative nomogram model combined with axillary ultrasound.

    Methods 

    A total of 295 breast cancer patients who underwent preoperative SWE and conventional ultrasound were selected. Ultrasonic features of primary lesions and axillary lymph nodes were retrospectively analyzed, and independent risk factors associated with ALNM were screened, based on which a nomogram model was constructed and the predictive value was assessed.

    Results 

    Breast tumor uneven margin, Emax and positive for ALNM by ultrasound diagnosis were independent risk factors for predicting ALNM. On this basis, the area under the curve (AUC) of the nomogram model was 0.842 (95%CI, 0.786 to 0.888), and the prediction efficiency was significantly better than that of a single index (P < 0.05).

    Conclusion 

    The quantitative parameters of SWE and conventional ultrasound characteristics of primary lesions of breast cancer can be used to predict ALNM, and the nomogram model constructed in combination with axillary ultrasound has a good value in predicting ALNM.

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