Prediction of clinical response to neoadjuvant therapy in advanced breast cancer by baseline B-mode ultrasound, shear-wave elastography, and pathological information

Abstract

BackgroundNeoadjuvant therapy (NAT) is the preferred treatment for advanced breast cancer nowadays. The early prediction of its responses is important for personalized treatment. This study aimed at using baseline shear wave elastography (SWE) ultrasound combined with clinical and pathological information to predict the clinical response to therapy in advanced breast cancer.MethodsThis retrospective study included 217 patients with advanced breast cancer who were treated in West China Hospital of Sichuan University from April 2020 to June 2022. The features of ultrasonic images were collected according to the Breast imaging reporting and data system (BI-RADS), and the stiffness value was measured at the same time. The changes were measured according to the Response evaluation criteria in solid tumors (RECIST1.1) by MRI and clinical situation. The relevant indicators of clinical response were obtained through univariate analysis and incorporated into a logistic regression analysis to establish the prediction model. The receiver operating characteristic (ROC) curve was used to evaluate the performance of the prediction models.ResultsAll patients were divided into a test set and a validation set in a 7:3 ratio. A total of 152 patients in the test set, with 41 patients (27.00%) in the non-responders group and 111 patients (73.00%) in the responders group, were finally included in this study. Among all unitary and combined mode models, the Pathology + B-mode + SWE model performed best, with the highest AUC of 0.808 (accuracy 72.37%, sensitivity 68.47%, specificity 82.93%, P<0.001). HER2+, Skin invasion, Post mammary space invasion, Myometrial invasion and Emax were the factors with a significant predictive value (P<0.05). 65 patients were used as an external validation set. There was no statistical difference in ROC between the test set and the validation set (P>0.05).ConclusionAs the non-invasive imaging biomarkers, baseline SWE ultrasound combined with clinical and pathological information can be used to predict the clinical response to therapy in advanced breast cancer.

Predictive value of multimodal ultrasound imaging and BCL-2 expression levels in the outcome of neoadjuvant chemotherapy for breast cancer

“…The primary criterion for evaluating the effectiveness of NAC using two-dimensional ultrasound (2D US) is the reduction in tumor size. However, some studies have shown that a significant proportion of patients initially categorized as having an inadequate response based on ultrasound evaluations were found to have actually responded positively to NAC based on postoperative pathological findings [17][18][19] relying solely on 2D US and changes in tumor size to assess NAC efficacy has limitations. In certain cases, NAC treatment for breast cancer results in tumor cell necrosis, leading to the formation of granulation and proliferation of fibrous tissue.…”

A real-world clinicopathological model for predicting pathological complete response to neoadjuvant chemotherapy in breast cancer

“…Circulating tumor cells (CTCs), which are a subset of tumor cells shed into the peripheral blood as a result of tumor tissue instability, have been identified as independent predictors of pCR and prognosis (20,21). Additionally, traditional diagnostics, such as ultrasound paired with molecular markers like CA15-3 and CEA, also correlate with pCR and prognosis (22)(23)(24). Recent advances highlight the significance of combining imaging, pathology, and hematology in assessing treatment efficacy, as shown in Wang et al's model which integrates clinical and radiomics features such as background parenchymal enhancement (BPE), human epidermal growth factor receptor-2 (HER-2) status, and the Ki-67 index (25).…”