Literature DB >> 23568482

Ultrasonographic assessment of breast density.

Won Hwa Kim1, Woo Kyung Moon, Seung Ja Kim, Ann Yi, Bo La Yun, Nariya Cho, Jung Min Chang, Hye Ryoung Koo, Mi Young Kim, Min Sun Bae, Su Hyun Lee, Jin You Kim, Eun Hee Lee.   

Abstract

Ultrasonographic (US) assessment of breast density has the potential to provide a nonionizing method. This study was to prospectively evaluate intermodality and interobserver agreements for assessment of breast density between US and mammography. Institutional review board approval was obtained. Forty-one women (mean 52.1 years; range 25-72 years) with variable breast density consented to participate. Eight radiologists blinded to mammographic information performed breast US for all participants and assessed each breast density using four categories based on the proportion of the breast occupied by the fibroglandular tissue. All participants underwent full-field digital mammography and mammographic density was independently assessed by eight radiologists 2 weeks after US using the breast imaging reporting and data system (BI-RADS) 4-category system. Intermodality agreements between US and mammographic assessments and interobserver agreements among radiologists were assessed using kappa statistics (к) and intraclass correlation coefficients (ICCs). There was substantial intermodality agreement between the US and mammographic assessments of breast density (к = 0.65 and ICC = 0.80), and 68 % (222/328) of the assessments had exact agreement. When categories were dichotomized into fatty (categories 1 and 2) and dense (categories 3 and 4), 86 % (282/328) of the assessments had exact agreement (к = 0.71). The interobserver agreement for the US assessments of breast density was substantial (average к = 0.63, ICC = 0.82) and not significantly different from that for the mammographic assessments (average к = 0.74, ICC = 0.85) (P = 0.701). US and mammography demonstrated substantial intermodality and interobserver agreement for assessment of breast density.

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Year:  2013        PMID: 23568482     DOI: 10.1007/s10549-013-2506-1

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  6 in total

1.  Differences in breast density assessment using mammography, tomosynthesis and MRI and their implications for practice.

Authors:  A Tagliafico; G Tagliafico; N Houssami
Journal:  Br J Radiol       Date:  2013-10-28       Impact factor: 3.039

2.  Performance of novel deep learning network with the incorporation of the automatic segmentation network for diagnosis of breast cancer in automated breast ultrasound.

Authors:  Qiucheng Wang; He Chen; Gongning Luo; Bo Li; Haitao Shang; Hua Shao; Shanshan Sun; Zhongshuai Wang; Kuanquan Wang; Wen Cheng
Journal:  Eur Radiol       Date:  2022-04-30       Impact factor: 7.034

Review 3.  Glandular Tissue Component on Breast Ultrasound in Dense Breasts: A New Imaging Biomarker for Breast Cancer Risk.

Authors:  Su Hyun Lee; Woo Kyung Moon
Journal:  Korean J Radiol       Date:  2022-06       Impact factor: 7.109

Review 4.  Imaging Breast Density: Established and Emerging Modalities.

Authors:  Jeon-Hor Chen; Gultekin Gulsen; Min-Ying Su
Journal:  Transl Oncol       Date:  2015-12       Impact factor: 4.243

5.  False-negative results on computer-aided detection software in preoperative automated breast ultrasonography of breast cancer patients.

Authors:  Youngjune Kim; Jiwon Rim; Sun Mi Kim; Bo La Yun; So Yeon Park; Hye Shin Ahn; Bohyoung Kim; Mijung Jang
Journal:  Ultrasonography       Date:  2020-03-24

6.  Impact of a randomized weight loss trial on breast tissue markers in breast cancer survivors.

Authors:  Christina M Dieli-Conwright; Maura Harrigan; Brenda Cartmel; Anees Chagpar; Yalai Bai; Fang-Yong Li; David L Rimm; Lajos Pusztai; Lingeng Lu; Tara Sanft; Melinda L Irwin
Journal:  NPJ Breast Cancer       Date:  2022-03-07
  6 in total

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