Literature DB >> 31793847

Effect of Digital Mammography for Breast Cancer Screening: A Comparative Study of More than 8 Million Korean Women.

Seri Hong1, Soo Yeon Song1, Boyoung Park1, Mina Suh1, Kui Son Choi1, Seung Eun Jung1, Min Jung Kim1, Eun Hye Lee1, Chan Wha Lee1, Jae Kwan Jun1.   

Abstract

BackgroundFull-field digital mammography (FFDM) has been accepted as a superior modality for breast cancer screening compared with conventional screen-film mammography (SFM), especially in women younger than 50 years or with dense breasts.PurposeTo evaluate the accuracy of FFDM for breast cancer screening.Materials and MethodsData from January 1, 2011 to December 31, 2013 in the database from a nationwide breast cancer screening program linked with the national cancer registry were retrospectively analyzed. The study included Korean women aged 40-79 years who had undergone screening mammography with SFM, computed radiography (CR), or FFDM. The sensitivity, specificity, positive predictive value (PPV), and absolute and relative differences among these modalities were calculated, followed by pairwise comparison tests with multiple testing corrections. The areas under the receiver operating characteristic curve (AUCs) were also estimated and compared by using the DeLong method with Bonferroni correction.ResultsAmong the 8 482 803 women included (mean age, 55 years ± 10), 34.4% (2 920 279 of 8 482 803), 51.7% (4 385 807 of 8 482 803), and 13.9% (1 176 717 of 8 482 803) underwent SFM, CR, and FFDM, respectively. The sensitivity and PPV were higher for FFDM than for SFM (adjusted odds ratio, 1.77 [95% confidence interval {CI}: 1.62, 1.95] for sensitivity and 1.36 [95% CI: 1.29, 1.43] for PPV) and CR (adjusted odds ratio, 1.70 [95% CI: 1.56, 1.85] for sensitivity and 1.26 [95% CI: 1.20, 1.32] for PPV), whereas specificity was lower with FFDM. The overall AUC for FFDM was 0.80 (95% CI: 0.80, 0.81), which was higher than that for SFM (0.75 [95% CI: 0.75, 0.76]) and CR (0.76 [95% CI: 0.75, 0.76]). P < .05 was found for differences in sensitivity, PPV, and AUC among modalities overall and in most of the subgroups of age, breast density, and screening round.ConclusionFull-field digital mammography allows better discrimination or prediction of breast cancer in the general female population than screen-film mammography or computed radiography, regardless of age, breast density, or screening round.© RSNA, 2019Online supplemental material is available for this article.

Entities:  

Year:  2019        PMID: 31793847     DOI: 10.1148/radiol.2019190951

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  7 in total

Review 1.  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

2.  Automated Segmentation of Mass Regions in DBT Images Using a Dilated DCNN Approach.

Authors:  Jianming Ye; Weiji Yang; Jianqing Wang; Xiaomei Xu; Liuyi Li; Chun Xie; Gang Chen; Xiangcai Wang; Xiaobo Lai
Journal:  Comput Intell Neurosci       Date:  2022-02-02

3.  Artificial Intelligence for Breast Cancer Screening in Mammography (AI-STREAM): A Prospective Multicenter Study Design in Korea Using AI-Based CADe/x.

Authors:  Yun-Woo Chang; Jung Kyu Ryu; Jin Kyung An; Nami Choi; Kyung Hee Ko; Ki Hwan Kim; Kyunghwa Han
Journal:  J Breast Cancer       Date:  2022-01-06       Impact factor: 3.588

Review 4.  [Digital Mammography as a Screening Tool in Korea].

Authors:  Soo Yeon Song; Seri Hong; Jae Kwan Jun
Journal:  Taehan Yongsang Uihakhoe Chi       Date:  2021-01-31

5.  Reducing Unnecessary Biopsies Using Digital Breast Tomosynthesis and Ultrasound in Dense and Nondense Breasts.

Authors:  Ibrahim Hadadi; Jillian Clarke; William Rae; Mark McEntee; Wendy Vincent; Ernest Ekpo
Journal:  Curr Oncol       Date:  2022-08-04       Impact factor: 3.109

6.  Detecting Vasodilation as Potential Diagnostic Biomarker in Breast Cancer Using Deep Learning-Driven Thermomics.

Authors:  Bardia Yousefi; Hamed Akbari; Xavier P V Maldague
Journal:  Biosensors (Basel)       Date:  2020-10-31

7.  Evaluation of the Value of Multiplex MicroRNA Analysis as a Breast Cancer Screening in Korean Women under 50 Years of Age with a High Proportion of Dense Breasts.

Authors:  Ji Young Jang; Eun Young Ko; Ji Soo Jung; Kyung Nam Kang; Yeon Soo Kim; Chul Woo Kim
Journal:  J Cancer Prev       Date:  2021-12-30
  7 in total

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