Huiwen Jiang1, Xiaodan Yu2, Lina Zhang3, Linxiao Song4, Xiuhua Gao5. 1. Department of Ultrasonography, Weihai Central Hospital, Weihai, China. 2. Blood Purification Center, Weihai Central Hospital, Weihai, China. 3. Penglai People's Hospital, Penglai, Shandong Province, China. 4. Zhifu District Maternal and Child Health Family Planning Service Center, Yantai, China. 5. Department of Breast Surgery, Weihai Central Hospital, Weihai, China.
Abstract
BACKGROUND: Strain elastography (SE) and shear wave elastography (SWE) have high diagnostic yield for breast lesions, but the optimal parameters remain elusive. AIM: To evaluate the diagnostic yield of SWE and SE for breast lesions by multivariate logistic regression analysis. MATERIAL AND METHODS: A total of 132 patients with 164 breast tumors were enrolled. Breast lesions were classified with the breast imaging reporting and data system (BI-RADS). Maximum (Emax), mean (Emean) and standard deviation (Esd) of elastic modulus, lesion/fat elasticity ratio and elastographic classification were obtained by SWE. Strain ratio (SR) and elastographic score were obtained by SE. A multivariate logistic regression analysis was performed. The diagnostic efficiencies of BI-RADS classification, SWE, SE and their combination were compared plotting ROC curves. RESULTS: There were 110 benign and 54 malignant lesions which had significantly different SWE and SE parameters. The parameters included in the logistic regression were Esd and elastographic classification obtained by SWE and the elastographic score obtained by SE. When combining SWE with SE, Esd, SR and SWE classification were included in the equation. The areas under ROC curves for BI-RADS classification, SWE, SE and their combination were 0.75, 0.88, 0.79 and 0.89, respectively. CONCLUSIONS: The diagnostic value of SWE in combination with SE for breast lesions exceeded that of SE or SWE alone. Esd showed a good diagnostic yield when SWE was used alone or combined with SE.
BACKGROUND: Strain elastography (SE) and shear wave elastography (SWE) have high diagnostic yield for breast lesions, but the optimal parameters remain elusive. AIM: To evaluate the diagnostic yield of SWE and SE for breast lesions by multivariate logistic regression analysis. MATERIAL AND METHODS: A total of 132 patients with 164 breast tumors were enrolled. Breast lesions were classified with the breast imaging reporting and data system (BI-RADS). Maximum (Emax), mean (Emean) and standard deviation (Esd) of elastic modulus, lesion/fat elasticity ratio and elastographic classification were obtained by SWE. Strain ratio (SR) and elastographic score were obtained by SE. A multivariate logistic regression analysis was performed. The diagnostic efficiencies of BI-RADS classification, SWE, SE and their combination were compared plotting ROC curves. RESULTS: There were 110 benign and 54 malignant lesions which had significantly different SWE and SE parameters. The parameters included in the logistic regression were Esd and elastographic classification obtained by SWE and the elastographic score obtained by SE. When combining SWE with SE, Esd, SR and SWE classification were included in the equation. The areas under ROC curves for BI-RADS classification, SWE, SE and their combination were 0.75, 0.88, 0.79 and 0.89, respectively. CONCLUSIONS: The diagnostic value of SWE in combination with SE for breast lesions exceeded that of SE or SWE alone. Esd showed a good diagnostic yield when SWE was used alone or combined with SE.
Authors: Ekaterina V Gubarkova; Aleksander A Sovetsky; Dmitry A Vorontsov; Pavel A Buday; Marina A Sirotkina; Anton A Plekhanov; Sergey S Kuznetsov; Aleksander L Matveyev; Lev A Matveev; Sergey V Gamayunov; Alexey Y Vorontsov; Vladimir Y Zaitsev; Natalia D Gladkova Journal: Biomed Opt Express Date: 2022-04-21 Impact factor: 3.562