Multi-center strain elastography radiomics for breast cancer diagnosis: integrating intratumoral and peritumoral regions.

OBJECTIVES

This study aimed to develop and validate a novel strain elastography (SE) radiomics nomogram for diagnosing breast cancer (BC) by analyzing intratumoral and peritumoral regions.

METHODS

A cohort of 322 patients, comprising 217 from hospital #1 (06/2021-05/2023) and 105 from hospital #2 (06/2022-05/2023) with breast lesions, was enrolled. Radiomic features were extracted from intratumoral and peritumoral (0-1 mm, 1-2 mm, 2-3 mm) regions on strain elastography images. Significant features were selected using Mann-Whitney U test, Spearman's correlation coefficient, and LASSO logistic regression. A radiomic model was constructed utilizing these features, followed by the development of a radiomic nomogram integrating optimal features.

RESULTS

The intratumoral radiomic model exhibited an area under the receiver operating characteristic curve (AUC) of 0.774 (95% CI: 0.626-0.922) in the internal testing set. Combining peritumoral radiomics, the intratumoral & peritumoral_0-1 mm radiomic model emerged as the optimal model with an AUC of 0.884 (95% CI: 0.766-0.998) in the internal testing set, signifying improved BC identification. The optimal model demonstrated an AUC of 0.841 (95% CI: 0.762-0.920) in the external testing set, indicating robustness and generalization.

CONCLUSIONS

The radiomic model incorporating intratumoral & peritumoral_0-1 mm radiomic features shows promise in diagnosing BC, aiding in devising effective clinical treatment strategies.