Evaluation of an automated breast volume scanner according to the fifth edition of BI-RADS for breast ultrasound compared with hand-held ultrasound.
Eur J Radiol
; 99: 138-145, 2018 Feb.
Article
in En
| MEDLINE
| ID: mdl-29362145
ABSTRACT
OBJECTIVES:
To investigate the automated breast volume scanner (ABVS) in comparison with hand-held ultrasound (HHUS) according to the fifth edition of BI-RADS ultrasound. MATERIAL ANDMETHODS:
A total of 831 lesions in 786 patients who underwent both HHUS and ABVS were included. Three radiologists independently evaluated the sonographic features of each lesion according to the fifth BI-RADS edition. The kappa coefficient (κ) was calculated for each BI-RADS descriptor and final assessment category. The accuracy of malignancy prediction and diagnostic performance of the BI-RADS descriptors were assessed using multivariate logistic regression and area under the receiver operator characteristic curve (AUC), respectively.RESULTS:
ABVS and HHUS showed moderate to good interobserver agreement (κâ¯=â¯0.53-0.67 and 0.55-0.70, respectively) except in associated features (κâ¯=â¯0.31 and 0.36, respectively) for BI-RADS lexicons. Irregular shape, a non-circumscribed margin, and posterior features (combined or shadowing) were independently associated with malignancy in both ABVS and HHUS. Calcification presence on ABVS (odds ratio [OR], 95% confidence interval [CI] 2.09, 1.11-3.94) and non-parallel orientation on HHUS (OR, 95% CI 2.04, 1.10-3.78) were independently associated with malignancy. There were no significant differences between ABVS and HHUS in sensitivity (84.2% vs. 84.2%), specificity (80.5% vs. 83.9%), or AUC (0.88 vs. 0.90).CONCLUSIONS:
According to the fifth BI-RADS edition, ABVS is not statistically significantly different from HHUS with regard to interobserver variability and diagnostic performance.Key words
Full text:
1
Database:
MEDLINE
Main subject:
Breast
/
Breast Neoplasms
Type of study:
Diagnostic_studies
/
Evaluation_studies
/
Prognostic_studies
Limits:
Adolescent
/
Adult
/
Aged
/
Female
/
Humans
/
Middle aged
Language:
En
Year:
2018
Type:
Article