Abstract:

Objective To investigate the value of conventional ultrasound combined with shear wave elastography （SWE） in the differential diagnosis of non-mass ductal carcinoma in situ （DCIS） and invasive breast cancer （IBC）. Methods A total of 102 patients with non-mass breast cancer admitted to Nanjing Drum Tower Hospital， Affiliated Hospital of Nanjing University Medical School from March 2019 to April 2022 were selected as the study objects， including 32 cases of DCIS and 70 cases of IBC. Conventional ultrasound parameters echo， microcalcification， location， posterior echo， blood flow， axillary lymph node， breast imaging reporting and data system （BI-RADS） score and SWE-related parameters maximum shear wave velocity （SWV_max）， minimum shear wave velocity （SWV_min）， mean shear wave velocity （SWV_mean） and median shear wave velocity （SWV_median） were compared between patients with non-mass DCIS and IBC. Binary logistic regression was used to analyze the independent factors for the differential diagnosis of non-mass DCIS and IBC. Based on the results of multivariate analysis， a nomogram prediction model was constructed and the predictive efficacy of the prediction model was evaluated by receiver operator characteristic （ROC） curve. Calibration curve and decision curve analysis （DCA） were used to evaluate the accuracy and practicability of the model. Results There were statistically significant differences in blood flow （χ²=8.47， P=0.004）， axillary lymph nodes （χ²=9.11， P=0.003）， SWV_max （Z=-3.32， P<0.001）， SWV_mean （t=3.00， P=0.003）， SWV_median （Z=-2.69， P=0.007） between patients with non-mass DCIS and IBC. Multivariate analysis showed that， blood flow （OR=3.56， 95%CI： 1.28-9.89， P=0.015）， axillary lymph nodes （OR=3.04， 95%CI： 1.10-8.42， P=0.032） and SWV_max （OR=1.40， 95%CI： 1.13-1.73， P=0.002） were independent factors for distinguishing non-mass DCIS from IBC. A nomogram prediction model was constructed based on blood flow， axillary lymph nodes and SWV_max. ROC curve analysis showed that， the area under the curve of blood flow， axillary lymph nodes， SWV_max， and prediction model for differential diagnosis of non-mass DCIS and IBC were 0.64 （95%CI： 0.52-0.76）， 0.66 （95%CI： 0.55-0.77）， 0.71 （95%CI： 0.60-0.81）， and 0.79 （95%CI： 0.70-0.88）， respectively， and the differential diagnostic value of prediction model was higher than that of blood flow （Z=2.92， P=0.004）， axillary lymph nodes （Z=2.94， P=0.003）， and SWV_max （Z=1.88， P=0.060） alone. The C-index of the prediction model for the differential diagnosis of non-mass DCIS and IBC was 0.77， and the calibration curve showed that the prediction probability of the prediction model was close to the actual probability. DCA showed that this prediction model could provide higher clinical net benefit and had certain clinical practicability. Conclusion Blood flow and axillary lymph nodes in conventional ultrasound parameters and SWV_max of SWE-related parameters are independent factors in the differential diagnosis of non-mass DCIS and IBC. The nomogram prediction model constructed by this method has a high value in the differential diagnosis of non-mass DCIS and IBC.

Key words: Breast neoplasms, Carcinoma， intraductal， noninfiltrating, Ultrasonography, Elasticity imaging techniques, Invasive breast cancer