Shear Wave Elastography Combined With Ki67 Predicting Pathological Complete Response in Invasive Breast Cancer After...

The aim of this study is to investigate the clinical relevance of shear wave elastography (SWE) in conjunction with Ki67 for predicting pathological complete response (pCR) in invasive breast cancer following neoadjuvant chemotherapy (NAC).

We retrospectively analyzed 167 patients with breast cancer who underwent surgical treatment after NAC. The patients were categorized into pCR (n = 71) and non-pCR (n = 96) groups based on postoperative pathological results. We compared clinical data, changes in tumor long diameter (ΔD), changes in Ki67 expression (ΔKi67), maximum stiffness of breast cancer tissue before and after NAC (SWEmax), maximum stiffness within 2 mm of the tumor (2 mm peritumoral shell SWEmax), and the corresponding changes (ΔSWEmax for both the tumor and the 2 mm shell). Additionally, we utilized multivariate logistic regression to examine the association between ΔD, ΔKi67, SWEmax, 2 mm shell SWEmax, ΔSWEmax, 2 mm shell ΔSWEmax, and the likelihood of achieving pCR. Receiver operating characteristic (ROC) curves were constructed to assess the diagnostic performance of individual parameters and their combined utility in predicting pCR.

Univariate analysis revealed greater changes in tumor long diameter (ΔD) and Ki67 (ΔKi67) in the pCR group compared to the n-pCR group. Following NAC, both SWEmax and the 2 mm shell SWEmax were lower in the pCR group than in the n-pCR group. Conversely, ΔSWEmax and the 2 mm shell ΔSWEmax were higher in the pCR group than in the n-pCR group, showing significant differences (p < 0.05). Multivariate logistic regression analysis identified ΔD, ΔKi67, ΔSWEmax, and the 2 mm shell ΔSWEmax as independent risk factors. In contrast, post-NAC SWEmax and the 2 mm shell SWEmax were independent protective factors for post-NAC pCR in breast cancer. The areas under the ROC curve (AUC) for predicting pCR were 0.724 for ΔD, 0.752 for ΔKi67, 0.763 for ΔSWEmax, and 0.842 for the 2 mm shell ΔSWEmax, with optimal cut-off values of 40.7%, 20.5%, 41.75%, and 18.49%, respectively. Combining all four parameters resulted in an AUC of 0.926 for pCR diagnosis, significantly higher than that of any individual parameter (p < 0.05 for all comparisons).

Following NAC in breast cancer, ters ΔD, ΔKi67, ΔSWEmax, 2 mm shell ΔSWEmax, post-NAC SWEmax, and 2 mm shell SWEmax independently influence the prediction of pCR. The composite predictive model, constructed using both pre- and post-NAC parameters, exhibited high discriminatory ability for evaluating pCR at the end of the treatment. Internal validation confirmed the model's robustness, suggesting its promising clinical utility in assessing the ultimate pathological response post-NAC.