Automated ultrasound of the breast for diagnosis: interobserver agreement on lesion detection and characterization.

OBJECTIVE

The purpose of this study was to prospectively evaluate interobserver agreement on lesion detection and characterization in the review of automated ultrasound images of the breast by five radiologists.

SUBJECTS AND METHODS

From August to October 2009, bilateral whole-breast ultrasound examinations were performed with an automated technique and with a handheld device for 55 women consecutively scheduled to undergo diagnostic ultrasound. Three-dimensional volume data from automated ultrasound were reviewed by five radiologists, who were unaware of the results of ultrasound with a handheld device and mammography and of the clinical information. If a lesion was detected with automated ultrasound, clock-face position, distance from the nipple, largest diameter, and BI-RADS final assessment category were evaluated. If the lesion was a mass, shape, orientation, margin, echogenicity, and posterior feature were analyzed. Intraclass correlation coefficients and kappa statistics were used for statistical analysis.

RESULTS

At least two observers identified 145 lesions with automated ultrasound. Among 725 possible detections, 587 (81%) detections were made. Individual investigators detected between 74% (107/145) and 88% (127/145) of the lesions. The rate of detection of lesions larger than 1.2 cm was 92%. Most lesions detected only with handheld ultrasound (11/12, 92%) or automated ultrasound (34/36, 94%) were cysts or probably benign masses. All intraclass correlation coefficients for lesion location and size exceeded 0.75, indicating high reliability. Substantial agreement was found for mass shape (κ = 0.71), orientation (κ = 0.72), margin (κ = 0.61), and BI-RADS final assessment category (κ = 0.63).

CONCLUSION

Detection of lesions larger than 1.2 cm in greatest diameter was reliable. High reliability was obtained for reporting lesion size and location. Substantial agreement was obtained for description of key feature and final assessment category.