Sonoelastographic strain index for differentiation of benign and malignant nonpalpable breast masses

J Ultrasound Med. 2010 Jan;29(1):1-7. doi: 10.7863/jum.2010.29.1.1.

Abstract

Objective: The purpose of this study was to evaluate the diagnostic potential of the sonoelastographic strain index for differentiation of nonpalpable breast masses.

Methods: Ninety-nine nonpalpable breast masses (79 benign and 20 malignant) in 94 women (mean age, 45 years; range, 21-68 years) who had been scheduled for a sonographically guided core biopsy were examined with B-mode sonography and sonoelastography. Radiologists who had performed the biopsies analyzed the B-mode sonograms and provided American College of Radiology Breast Imaging Reporting and Data System categories. The strain index (fat to lesion strain ratio) was calculated by dividing the strain value of the subcutaneous fat by that of the mass. The histologic result from the sonographically guided core biopsy was used as a reference standard. The diagnostic performance of the strain index and that of B-mode sonography were compared by receiver operating characteristic (ROC) curve analysis.

Results: The mean strain index values +/- SD were 6.57 +/- 6.62 (range, 1.29-28.69) in malignant masses and 2.63 +/- 4.57 (range, 0.54-38.76) in benign masses (P = .019). The area under the ROC curve values were 0.835 (95% confidence interval [CI], 0.747-0.902) for B-mode sonography and 0.879 (95% CI, 0.798-0.936) for the strain index (P = .490). The sensitivity, specificity, positive predictive value, and negative predictive value were 95% (19 of 20), 75% (59 of 79), 48% (19 of 39), and 98% (59 of 60), respectively, when a best cutoff point of 2.24 was used.

Conclusions: The strain index based on the fat to lesion strain ratio has diagnostic performance comparable with that of B-mode sonography for differentiation of benign and malignant breast masses.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adipose Tissue / diagnostic imaging*
  • Adipose Tissue / physiopathology*
  • Adult
  • Aged
  • Algorithms
  • Breast Neoplasms / diagnostic imaging*
  • Breast Neoplasms / physiopathology*
  • Diagnosis, Differential
  • Elastic Modulus
  • Elasticity Imaging Techniques / methods*
  • Feasibility Studies
  • Female
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods*
  • Middle Aged
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Ultrasonography, Mammary / methods*