BACKGROUND: Elastography has shown potential in differentiating benign from malignant breast tumors, but interobserver variability between experienced and inexperienced readers limits its wide usage. PURPOSE: To compare the diagnostic performance of computer-assisted quantification and visual assessment of lesion stiffness with the use of sonographic elastography for the differentiation of benign from malignant nonpalpable breast masses. MATERIAL AND METHODS: Sonographic elasticity images of 120 nonpalpable breast masses (70 benign and 50 malignant masses) were obtained in 120 women prior to performing a core biopsy. After subtraction of B-mode images from color elasticity images, the mean strain value of the lesion was computed. Elasticity images were also reviewed and were assigned a score on a five-point scale by two breast radiologists in consensus. Results were evaluated by using receiver operating characteristic (ROC) curve analysis. RESULTS: The mean +/- standard deviation values of strain were 221+/-18 for malignant lesions and 175+/-21 for benign lesions (P<0.001). For the elasticity score, the mean score was 3.5+/-0.1 for the malignant masses and 2.0+/-0.9 for the benign masses (P<0.001). The overall Pearson's correlation coefficient between the strain values and elasticity score was 0.689 (P<0.001). The area under the ROC curve (A(z)) value was 0.878 for use of the computer-assisted quantification method and 0.850 for visual assessment by the radiologists. The difference was not statistically significant (P=0.198). CONCLUSION: Computer-assisted quantification and visual assessment of lesion stiffness with the use of sonographic elasticity images had comparable diagnostic performance for the differentiation of nonpalpable breast masses.
BACKGROUND: Elastography has shown potential in differentiating benign from malignant breast tumors, but interobserver variability between experienced and inexperienced readers limits its wide usage. PURPOSE: To compare the diagnostic performance of computer-assisted quantification and visual assessment of lesion stiffness with the use of sonographic elastography for the differentiation of benign from malignant nonpalpable breast masses. MATERIAL AND METHODS: Sonographic elasticity images of 120 nonpalpable breast masses (70 benign and 50 malignant masses) were obtained in 120 women prior to performing a core biopsy. After subtraction of B-mode images from color elasticity images, the mean strain value of the lesion was computed. Elasticity images were also reviewed and were assigned a score on a five-point scale by two breast radiologists in consensus. Results were evaluated by using receiver operating characteristic (ROC) curve analysis. RESULTS: The mean +/- standard deviation values of strain were 221+/-18 for malignant lesions and 175+/-21 for benign lesions (P<0.001). For the elasticity score, the mean score was 3.5+/-0.1 for the malignant masses and 2.0+/-0.9 for the benign masses (P<0.001). The overall Pearson's correlation coefficient between the strain values and elasticity score was 0.689 (P<0.001). The area under the ROC curve (A(z)) value was 0.878 for use of the computer-assisted quantification method and 0.850 for visual assessment by the radiologists. The difference was not statistically significant (P=0.198). CONCLUSION: Computer-assisted quantification and visual assessment of lesion stiffness with the use of sonographic elasticity images had comparable diagnostic performance for the differentiation of nonpalpable breast masses.
Authors: Jose I Lopez; Inkyung Kang; Weon-Kyoo You; Donald M McDonald; Valerie M Weaver Journal: Integr Biol (Camb) Date: 2011-08-15 Impact factor: 2.192
Authors: Haiyan Xu; Min Rao; Tomy Varghese; Amy Sommer; Sara Baker; Timothy J Hall; Gale A Sisney; Elizabeth S Burnside Journal: Ultrasound Med Biol Date: 2010-11 Impact factor: 2.998
Authors: Andrew Evans; Patsy Whelehan; Kim Thomson; Denis McLean; Katrin Brauer; Colin Purdie; Lee Jordan; Lee Baker; Alastair Thompson Journal: Breast Cancer Res Date: 2010-12-01 Impact factor: 6.466
Authors: Jonathan Frederik Carlsen; Caroline Ewertsen; Adrian Săftoiu; Lars Lönn; Michael Bachmann Nielsen Journal: PLoS One Date: 2014-02-12 Impact factor: 3.240