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


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.
Radiology Department, Institut Gustave Roussy, Villejuif, France.
Marie-Laure
ML
Chabi
Isabelle
I
Borget
Rosario
R
Ardiles
Ghassen
G
Aboud
Samia
S
Boussouar
Vanessa
V
Vilar
Clarisse
C
Dromain
Corinne
C
Balleyguier
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D005260:Female; D005602:France; D006801:Humans; D008875:Middle Aged; D015588:Observer Variation; D010363:Pattern Recognition, Automated / Q000379:methods*; D010820:Physicians / Q000706:statistics & numerical data*; D011361:Professional Competence / Q000706:statistics & numerical data*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016217:Ultrasonography, Mammary / Q000379:methods*; D055815:Young Adult