Early prediction of pathological outcomes to neoadjuvant chemotherapy in breast cancer patients using automated breast ultrasound

Objective： Early assessment of response to neoadjuvant chemotherapy （NAC） for breast cancer allows therapy to be individualized. The optimal assessment method has not been established. We investigated the accuracy of automated breast ultrasound （ABUS） to predict pathological outcomes after NAC. Methods： A total of 290 breast cancer patients were eligible for this study. Tumor response after 2 cycles of chemotherapy was assessed using the product change of two largest perpendicular diameters （PC） or the longest diameter change （LDC）. PC and LDC were analyzed on the axial and the coronal planes respectively. Receiver operating characteristic （ROC） curves were used to evaluate overall performance of the prediction methods. Youden＇s indexes were calculated to select the optimal cut-off value for each method. Sensitivity, specificity, positive and negative predictive values （PPV and NPV） and the area under the ROC curve （AUC） were calculated accordingly.Results： ypT0/is was achieved in 42 patients （14.5%） while ypT0 was achieved in 30 patients （10.3%） after NAC. All four prediction methods （PC on axial planes, LDC on axial planes, PC on coronal planes and LDC on coronal planes） displayed high AUCs （all〉0.82）, with the highest of 0.89 [95% confidence interval （95% CI）, 0.83-0.95] when mid-treatment ＆BUS was used to predict final pathological complete remission （pCR）. High sensitivities （85.7%-88.1%） were observed across all four prediction methods while high specificities （81.5%-85.1%） were observed in two methods used PC. The optimal cut-off values defined by our data replicate the WHO and the RECIST criteria. Lower AUCs were observed when mid-treatment ABUS was used to predict poor pathological outcomes. Conclusions：ABUS is a useful tool in early evaluation of pCR after NAC while less reliable when predicting poor pathological outcomes.