Eunyoung Kang1, Eung-Jik Lee1, Mijung Jang2, Sun Mi Kim2, Youngwoo Kim3, Minsoo Chun3, Joo Ho Tai4, Wonshik Han5, Sung-Won Kim1,6, Jong Hyo Kim3,4,7. 1. 1 Department of Surgery, Bundang Seoul National University Hospital, Seongnam, South Korea. 2. 2 Department of Radiology, Bundang Seoul National University Hospital, Seongnam, South Korea. 3. 3 Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, 101 Daehak-Ro, Chongno-gu, Seoul 110-744, South Korea. 4. 4 Center for Medical-IT Convergence Technology Research, Advanced Institutes of Convergence Technology, Suwon, South Korea. 5. 5 Department of Surgery, Cancer Research Institute, Seoul National University College of Medicine, Seoul, South Korea. 6. 6 Present address: Department of Surgery, Daerim St. Mary's Hospital, Seoul, South Korea. 7. 7 Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology, Seoul National University, Suwon, South Korea.
Abstract
OBJECTIVE: The purpose of this study was to investigate the reliability of computer-assisted methods of estimating breast density. MATERIALS AND METHODS: Craniocaudal mammograms of 100 healthy subjects were collected from a screening mammography database. Three expert readers independently assessed mammographic breast density twice in a 1-month period using interactive thresholding and semiautomated methods. In addition, fully automated breast density estimation software was used to generate objective breast density estimates. The reliability of the computer-assisted breast density estimation was assessed in terms of concordance correlation coefficients, limits of agreement, systematic difference, and reader variability. RESULTS: Statistically significant systematic bias (paired t test, p < 0.01) and variability (4.75-10.91) were found within and between readers for both the interactive thresholding and the semiautomated methods. Using the semiautomated method significantly reduced the within-reader bias of one reader (p < 0.02) and the between-reader variability of all three readers (p < 0.05). The breast density estimates obtained with the fully automated method had excellent agreement with those of the reference standard (concordance correlation coefficient, 0.93) without a significant systematic difference. CONCLUSION: Reader-dependent variability and systematic bias exist in breast density estimates obtained with the interactive thresholding method, but they may be reduced in part by use of the semiautomated method. Assessing reader performance may be necessary for more reliable breast density estimation, especially for surveillance of breast density over time. The fully automated method has the potential to provide reliable breast density estimates nearly free from reader-dependent systematic bias and reader variability.
OBJECTIVE: The purpose of this study was to investigate the reliability of computer-assisted methods of estimating breast density. MATERIALS AND METHODS: Craniocaudal mammograms of 100 healthy subjects were collected from a screening mammography database. Three expert readers independently assessed mammographic breast density twice in a 1-month period using interactive thresholding and semiautomated methods. In addition, fully automated breast density estimation software was used to generate objective breast density estimates. The reliability of the computer-assisted breast density estimation was assessed in terms of concordance correlation coefficients, limits of agreement, systematic difference, and reader variability. RESULTS: Statistically significant systematic bias (paired t test, p < 0.01) and variability (4.75-10.91) were found within and between readers for both the interactive thresholding and the semiautomated methods. Using the semiautomated method significantly reduced the within-reader bias of one reader (p < 0.02) and the between-reader variability of all three readers (p < 0.05). The breast density estimates obtained with the fully automated method had excellent agreement with those of the reference standard (concordance correlation coefficient, 0.93) without a significant systematic difference. CONCLUSION: Reader-dependent variability and systematic bias exist in breast density estimates obtained with the interactive thresholding method, but they may be reduced in part by use of the semiautomated method. Assessing reader performance may be necessary for more reliable breast density estimation, especially for surveillance of breast density over time. The fully automated method has the potential to provide reliable breast density estimates nearly free from reader-dependent systematic bias and reader variability.
Keywords:
breast cancer risk; computer-assisted estimation; fully automated estimate; mammographic breast density; reader variability; reliability; systematic difference
Authors: Alexander Ciritsis; Cristina Rossi; Ilaria Vittoria De Martini; Matthias Eberhard; Magda Marcon; Anton S Becker; Nicole Berger; Andreas Boss Journal: Br J Radiol Date: 2018-10-01 Impact factor: 3.039