Literature DB >> 26499000

Digital breast tomosynthesis and breast ultrasound: Additional roles in dense breasts with category 0 at conventional digital mammography.

Won Kyung Lee1, Jin Chung2, Eun-Suk Cha1, Jee Eun Lee1, Jeoung Hyun Kim1.   

Abstract

PURPOSE: To compare the diagnostic performances of digital breast tomosynthesis (DBT) and ultrasound for the dense breasts with category 0 at conventional digital mammography.
MATERIALS AND METHODS: This retrospective study was approved by the institutional review board, and informed consent was waived. Among the 1103 patients who underwent screening digital mammography at our institution, 769 (69.7%) patients had dense breasts. Of the 769 patients, 229 (29.8%) lesions were categorized as 0. DBT, breast ultrasound and digital mammography were performed in 108 (47.2%) patients. BI-RADS final assessments for DBT and ultrasound were recorded. Categories 1-3 were clinically considered as benign, and categories 4 and 5 were clinically considered as malignant. The diagnostic performances of breast ultrasound and DBT were correlated with final pathologic reports or follow-up images.
RESULTS: Among 108 lesions, 17 (15.7%) were malignant and 91 (84.3%) were benign. Sensitivity was 100% for both ultrasound (17/17) and DBT (17/17) and negative predictive value was also 100% for both ultrasound (49/49) and DBT (74/74). Specificity and positive predictive value for ultrasound were 53.9% (49/91) and 28.8% (17/59), respectively. Specificity and positive predictive value for DBT were 81.3% (74/91) and 50% (17/34), respectively. DBT showed higher diagnostic accuracy than that of breast ultrasound (DBT: 84.3%, 91/108; ultrasound: 61.1%, 66/108; p<0.001). The benign biopsy rate of DBT (50%, 17/34) was lower than that of ultrasound (71.2%, 42/59).
CONCLUSION: DBT showed better diagnostic performance than breast ultrasound for dense breasts with category 0. DBT may reduce the benign biopsy rate and short term follow-up.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Breast; Dense breast; Digital breast tomosynthesis; Digital mammography; Ultrasound

Mesh:

Year:  2015        PMID: 26499000     DOI: 10.1016/j.ejrad.2015.09.026

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  4 in total

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Journal:  Sensors (Basel)       Date:  2022-05-09       Impact factor: 3.847

2.  The added value of an artificial intelligence system in assisting radiologists on indeterminate BI-RADS 0 mammograms.

Authors:  Chunyan Yi; Yuxing Tang; Rushan Ouyang; Yanbo Zhang; Zhenjie Cao; Zhicheng Yang; Shibin Wu; Mei Han; Jing Xiao; Peng Chang; Jie Ma
Journal:  Eur Radiol       Date:  2021-09-15       Impact factor: 7.034

3.  Synergy in combining findings from mammography and ultrasonography in detecting malignancy in women with higher density breasts and lesions over 2 cm in Albania.

Authors:  Altin Malaj; Albana Shahini
Journal:  Contemp Oncol (Pozn)       Date:  2017-01-12

4.  A multicenter hospital-based diagnosis study of automated breast ultrasound system in detecting breast cancer among Chinese women.

Authors:  Xi Zhang; Xi Lin; Yanjuan Tan; Ying Zhu; Hui Wang; Ruimei Feng; Guoxue Tang; Xiang Zhou; Anhua Li; Youlin Qiao
Journal:  Chin J Cancer Res       Date:  2018-04       Impact factor: 5.087

  4 in total

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