Differentiating benign from malignant solid breast masses: comparison of two-dimensional and three-dimensional US.
OBJECTIVE
To compare prospectively obtained static two-dimensional (2D) and three-dimensional (3D) ultrasonographic (US) images in the diagnostic performance of radiologists with respect to the differentiation of benign from malignant solid breast masses with histopathologic examination as the reference standard.


METHODS
This study had institutional review board approval, and patient informed consent was obtained. Conventional 2D and 3D US images were obtained from 141 patients (age range, 25-71 years; mean age, 46 years) with 150 solid breast masses (60 cancers and 90 benign lesions) before excisonal or needle biopsy. Four radiologists who had not performed the examinations independently reviewed 2D US images and stored 3D US data and provided a level of suspicion concerning probability of malignancy. The sensitivity, specificity, and negative predictive values of 2D images were compared with those of 3D US images.


RESULTS
For all readers, 3D US images were the same as or better than 2D US images in terms of sensitivity (100% vs 100% for reader 1; 100% vs 98% for reader 2; 98% vs 93% for reader 3; 93% vs 92% for reader 4), specificity (58% vs 56% for reader 1; 51% vs 46% for reader 2; 83% vs 72% for reader 3; 86% vs 84% for reader 4), and negative predictive values (100% vs 100% for reader 1; 100% vs 98% for reader 2; 99% vs 94% for reader 3; 95% vs 94% for reader 4). These differences, however, were not statistically significant (P > .05).


CONCLUSIONS
The performance of the radiologists with respect to the characterization of solid breast masses with static 2D US images was similar to that with 3D US data.
Cho
Nariya
N
Department of Radiology and Clinical Research Institute, Seoul National University Hospital, 28 Yongon-dong, Chongno-gu, Seoul 100-744, Korea.
Moon
Woo Kyung
WK
Cha
Joo Hee
JH
Kim
Sun Mi
SM
Han
Boo-Kyung
BK
Kim
Eun-Kyung
EK
Kim
Mi Hye
MH
Chung
Soo Young
SY
Choi
Hye-Young
HY
Im
Jung-Gi
JG