Evaluation of the accuracy of a computer-aided diagnosis (CAD) system in breast ultrasound according to the radiologist's experience

Acad Radiol. 2012 Mar;19(3):311-9. doi: 10.1016/j.acra.2011.10.023.

Abstract

Rationale and objectives: The aim of this study was to evaluate the performance of a computer-aided diagnosis (CAD) system for breast ultrasound to improve the characterization of breast lesions detected on ultrasound by junior and senior radiologists.

Materials and methods: One hundred sixty ultrasound breast lesions were randomly reviewed blindly by four radiologists with different levels of expertise (from 20 years [radiologist A] to 4 months [radiologist D]), with and without the help of an ultrasound CAD system (B-CAD version 2). All lesions had been biopsied. Sensitivity and specificity with and without CAD were calculated for each radiologist for the following evaluation criteria: Breast Imaging Reporting and Data System category and the final diagnosis (benign or malignant). Intrinsic sensitivity, specificity, and predictive values of CAD alone were also calculated.

Results: CAD detected all cancers, and its use increased radiologists' sensitivity scores when this was possible (with vs without CAD: radiologist A, 99% vs 99%; radiologist B, 96% vs 87%; radiologist C, 95% vs 88%; radiologist D, 91% vs 88%). Seven additional cancers were diagnosed. However, the low specificity of CAD (48%) decreased the specificity of radiologists, especially of the more experienced among them (with vs without CAD: radiologist A, 46% vs 70%; radiologist B, 58% vs 80%; radiologist C, 57% vs 69%; radiologist D, 71% vs 71%).

Conclusions: CAD for breast ultrasound appears to be a useful tool for improving the diagnosis of malignant lesions for junior radiologists. Nevertheless, its low specificity must be taken into account to limit biopsies of benign lesions.

Publication types

  • Randomized Controlled Trial

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Breast Neoplasms / diagnostic imaging*
  • Female
  • France
  • Humans
  • Middle Aged
  • Observer Variation
  • Pattern Recognition, Automated / methods*
  • Physicians / statistics & numerical data*
  • Professional Competence / statistics & numerical data*
  • Radiographic Image Interpretation, Computer-Assisted / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Ultrasonography, Mammary / methods*
  • Young Adult