Application of automated breast volume scanner and mammography in differentiation of small breast lesions with BI-RADS-US 4 / 中南大学学报(医学版)
Zhongnan Daxue xuebao. Yixue ban
; (12): 1131-1136, 2018.
Article
in Zh
| WPRIM
| ID: wpr-813143
Responsible library:
WPRO
ABSTRACT
To evaluate the value of automatic breast volume scanner (ABVS) and mammography (MG) in differential diagnosis for small breast lesions with breast imaging reporting and data system ultrasound (BI-RADS-US) 4.
Methods: ABVS and MG were performed for 103 patients with 109 breast lesions, which were classified as BI-RADS-US 4 by conventional ultrasound (US). Postoperative pathological diagnosis served as gold standard. The diagnostic efficacy for US, US combined with MG, US combined with ABVS and the combination of three methods were compared.
Results: The sensitivity of US, US combined with MG, US combined with ABVS and the combination of three methods were 85.5%, 86.8%, 94.7% and 96.0%, respectively. The specificity for them were 66.7%, 69.7%, 81.8% and 84.9%, respectively. The accuracy for them were 79.8%, 81.6%, 90.8% and 92.7%, respectively. The area under the receiver operating characteristic (ROC) curve (AUC) for them were 0.76, 0.78, 0.88 and 0.90, respectively. The accuracy and AUC for US combined with ABVS in differential diagnosis of BI-RADS-US 4 small breast lesions were significantly higher than those of US and US combined with MG (P0.05). No significant difference was found in sensitivity, specificity, accuracy, and AUC between US combined with ABVS and the combination of three methods (P>0.05).
Conclusion: Combination of US with ABVS can improve the diagnostic efficacy of conventional US in differential diagnosis for BI-RADS-US 4 small breast lesions, and it is superior to US combined with MG.
Full text:
1
Index:
WPRIM
Main subject:
Breast
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Breast Neoplasms
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Diagnostic Imaging
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Mammography
/
Reproducibility of Results
/
Ultrasonography, Mammary
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Sensitivity and Specificity
Type of study:
Diagnostic_studies
/
Prognostic_studies
Limits:
Female
/
Humans
Language:
Zh
Journal:
Zhongnan Daxue xuebao. Yixue ban
Year:
2018
Type:
Article