Diagnostic values of shear wave elastography and strain elastography for breast lesions

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.

Antecedentes: La elastografía de deformación (SE) y de onda cortante (SWE) son útiles para el diagnóstico de lesiones mamarias, pero falta definir los parámetros óptimos. Objetivo: Evaluar el valor diagnóstico de SE y SWE en lesiones mamarias usando una regresión logística multivariable. Material y Métodos: Ciento treinta y dos pacientes con 164 tumores mamarios fueron evaluados, los que se clasificaron usando el sistema BI-RADS (breast imaging reporting and data system). El módulo elástico máximo, promedio y su desviación estándar (Esd), la razón entre la elasticidad de la lesión y de la grasa y la clasificación elastográfica se obtuvieron con SWE. La razón de deformación (SR) y el puntaje elastográfico se obtuvieron con SE. Se efectuó una regresión logística y las eficiencias diagnósticas de la clasificación BI-RADS, SWE and SE y su combinación se compararon usando curvas ROC (receiver operating characteristic curves). Resultados: Ciento diez lesiones fueron benignas y 54 malignas. Estas tenían parámetros SWE y SE significativamente diferentes. En la ecuación de regresión logística, se incluyeron la clasificación elastográfica y el Esd obtenidos por SWE y el puntaje elastográfico obtenido por SE. Cuando se combinó SWE y SE, se incluyeron en la ecuación el Esd, SR y la clasificación por SWE. Las áreas bajo la curva ROC para la clasificación BI-RADS, SWE y SE y la combinación de ambas fueron 0.75, 0.88, 079 y 0.89 respectivamente. Conclusiones: La combinación de SWE y SE tuvo un mejor rendimiento diagnóstico para lesiones mamarias que cada parámetro por separado. Esd tuvo un buen rendimiento diagnóstico cuando se utilizó SWE sola o combinada con SE.

Diagnostic values of shear wave elastography and strain elastography for breast lesions.

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.