Nomogram using bi-modal imaging for predicting low-level HER2 expression status in breast cancer

Area of Science:

• Radiology
• Oncology
• Breast Cancer Imaging

Background:

• Human epidermal growth factor receptor 2-low (HER2-low) expression is increasingly recognized in breast cancer.
• Accurate prediction of HER2-low status is crucial for treatment selection and prognosis.
• Current methods for determining HER2-low status can be invasive or time-consuming.

Purpose of the Study:

• To develop and validate a predictive nomogram for HER2-low expression status in breast cancer.
• To utilize readily available ultrasound and mammographic imaging features for prediction.
• To assess the clinical utility and prognostic implications of the developed nomogram.

Main Methods:

• Retrospective analysis of 316 patients with HER2-negative breast cancer, divided into training (n=221) and validation (n=95) cohorts.
• Identification of independent imaging predictors (e.g., tumor diameter, margin, acoustic shadowing, elasticity) through univariate and multivariate analyses.
• Development and validation of a nomogram model, with assessment of calibration, discrimination (AUC), and clinical net benefit using ROC and decision curve analyses.

Main Results:

• Key imaging features including longer diameter, non-circumscribed margins, posterior acoustic shadowing, and higher maximum elasticity were significant predictors of HER2-low status.
• The nomogram demonstrated good predictive performance with an AUC of 0.783 in the training cohort and 0.810 in the validation cohort.
• The nomogram showed good calibration and clinical utility, and HER2-low expression was associated with improved progression-free survival.

Conclusions:

• The developed nomogram effectively predicts HER2-low expression status in breast cancer using ultrasound and mammography.
• This imaging-based tool offers a non-invasive method to identify patients who may benefit from specific management strategies.
• The nomogram can serve as a valuable reference for clinicians in optimizing patient care and treatment selection for HER2-low breast cancer.