Mammographic density assessed on paired raw and processed digital images and on paired screen-film and digital images across three mammography systems

doi:10.1186/s13058-016-0787-0

. 2016 Dec 19;18(1):130.

doi: 10.1186/s13058-016-0787-0.

Mammographic density assessed on paired raw and processed digital images and on paired screen-film and digital images across three mammography systems

Anya Burton¹, Graham Byrnes², Jennifer Stone³, Rulla M Tamimi⁴, John Heine⁵, Celine Vachon⁶, Vahit Ozmen⁷, Ana Pereira⁸, Maria Luisa Garmendia⁹, Christopher Scott⁶, John H Hipwell⁹, Caroline Dickens¹⁰, Joachim Schüz², Mustafa Erkin Aribal¹¹, Kimberly Bertrand¹², Ava Kwong^{13

14}, Graham G Giles^{15

16}, John Hopper¹⁶, Beatriz Pérez Gómez¹⁷, Marina Pollán¹⁷, Soo-Hwang Teo^{18

19}, Shivaani Mariapun¹⁹, Nur Aishah Mohd Taib¹⁸, Martín Lajous^{20

21}, Ruy Lopez-Riduara²¹, Megan Rice⁴, Isabelle Romieu²², Anath Arzee Flugelman²³, Giske Ursin^{24

25

26}, Samera Qureshi²⁷, Huiyan Ma²⁸, Eunjung Lee²⁶, Reza Sirous²⁹, Mehri Sirous²⁹, Jong Won Lee³⁰, Jisun Kim³⁰, Dorria Salem³¹, Rasha Kamal³², Mikael Hartman^{33

34}, Hui Miao³⁴, Kee-Seng Chia³⁵, Chisato Nagata³⁶, Sudhir Vinayak³⁷, Rose Ndumia³⁷, Carla H van Gils³⁸, Johanna O P Wanders³⁸, Beata Peplonska³⁹, Agnieszka Bukowska³⁹, Steve Allen⁴⁰, Sarah Vinnicombe⁴¹, Sue Moss⁴², Anna M Chiarelli⁴³, Linda Linton⁴⁴, Gertraud Maskarinec⁴⁵, Martin J Yaffe⁴⁶, Norman F Boyd⁴⁴, Isabel Dos-Santos-Silva⁴⁷, Valerie A McCormack²

Affiliations

¹ Section of Environment and Radiation, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon, Cedex 09, France. burtona@fellows.iarc.fr.
² Section of Environment and Radiation, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon, Cedex 09, France.
³ Centre for Genetic Origins of Health and Disease, Curtin University and the University of Western Australia, Perth, Australia.
⁴ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
⁵ Moffitt Cancer Center, Tampa, FL, USA.
⁶ Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
⁷ Department of Surgery, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey.
⁸ Institute of Nutrition and Food Technology, University of Chile, Santiago, Chile.
⁹ Centre for Medical Image Computing, University College London, London, UK.
¹⁰ Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
¹¹ Marmara University School of Medicine Department of Radiology, Istanbul, Turkey.
¹² Slone Epidemiology Center, Boston University, Boston, MA, USA.
¹³ Division of Breast Surgery, Department of Surgery, The University of Hong Kong, Hong Kong, People's Republic of China.
¹⁴ Department of Surgery, Hong Kong Sanatorium and Hospital, Hong Kong, People's Republic of China.
¹⁵ Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia.
¹⁶ Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia.
¹⁷ Cancer Epidemiology Unit, Instituto de Salud Carlos III and CIBERESP, Madrid, Spain.
¹⁸ Breast Cancer Research Group, University Malaya Medical Centre, University Malaya, Kuala Lumpur, Malaysia.
¹⁹ Cancer Research Malaysia, Subang Jaya, Malaysia.
²⁰ Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
²¹ Center for Research on Population Health, Instituto Nacional de Salud Pública, Mexico City, Mexico.
²² Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France.
²³ National Cancer Control Center, Haifa, Israel.
²⁴ Cancer Registry of Norway, Oslo, Norway.
²⁵ Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
²⁶ Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA.
²⁷ Norwegian Center for Minority and Migrant Health Research (NAKMI), Oslo, Norway.
²⁸ Department of Population Sciences, Beckman Research Institute, City of Hope, CA, USA.
²⁹ Isfahan University of Medical Sciences, Isfahan, Iran.
³⁰ Department of Surgery, Asan Medical Center, Seoul, Republic of Korea.
³¹ Cairo University, Cairo, Egypt.
³² Woman Imaging Unit, Radiodiagnosis Department, Kasr El Aini, Cairo University Hospitals, Cairo, Egypt.
³³ Department of Surgery, Yong Loo Lin School of Medicine, Singapore, Singapore.
³⁴ Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
³⁵ NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore.
³⁶ Gifu University, Gifu, Japan.
³⁷ Aga Khan University Hospital, Nairobi, Kenya.
³⁸ Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
³⁹ Nofer Institute of Occupational Medicine, Łódz, Poland.
⁴⁰ Department of Imaging, Royal Marsden NHS Foundation Trust, London, UK.
⁴¹ Division of Cancer Research, Ninewells Hospital & Medical School, Dundee, UK.
⁴² Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK.
⁴³ Ontario Breast Screening Program, Cancer Care Ontario, Toronto, Canada.
⁴⁴ Princess Margaret Cancer Centre, Toronto, Canada.
⁴⁵ University of Hawaii Cancer Center, Honolulu, HI, USA.
⁴⁶ Medical Biophysics, University of Toronto, Toronto, Canada.
⁴⁷ Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.

PMID: 27993168
PMCID: PMC5168805
DOI: 10.1186/s13058-016-0787-0

Mammographic density assessed on paired raw and processed digital images and on paired screen-film and digital images across three mammography systems

Anya Burton et al. Breast Cancer Res. 2016.

. 2016 Dec 19;18(1):130.

doi: 10.1186/s13058-016-0787-0.

Authors

Affiliations

¹ Section of Environment and Radiation, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon, Cedex 09, France. burtona@fellows.iarc.fr.
² Section of Environment and Radiation, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon, Cedex 09, France.
³ Centre for Genetic Origins of Health and Disease, Curtin University and the University of Western Australia, Perth, Australia.
⁴ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
⁵ Moffitt Cancer Center, Tampa, FL, USA.
⁶ Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
⁷ Department of Surgery, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey.
⁸ Institute of Nutrition and Food Technology, University of Chile, Santiago, Chile.
⁹ Centre for Medical Image Computing, University College London, London, UK.
¹⁰ Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
¹¹ Marmara University School of Medicine Department of Radiology, Istanbul, Turkey.
¹² Slone Epidemiology Center, Boston University, Boston, MA, USA.
¹³ Division of Breast Surgery, Department of Surgery, The University of Hong Kong, Hong Kong, People's Republic of China.
¹⁴ Department of Surgery, Hong Kong Sanatorium and Hospital, Hong Kong, People's Republic of China.
¹⁵ Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia.
¹⁶ Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia.
¹⁷ Cancer Epidemiology Unit, Instituto de Salud Carlos III and CIBERESP, Madrid, Spain.
¹⁸ Breast Cancer Research Group, University Malaya Medical Centre, University Malaya, Kuala Lumpur, Malaysia.
¹⁹ Cancer Research Malaysia, Subang Jaya, Malaysia.
²⁰ Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
²¹ Center for Research on Population Health, Instituto Nacional de Salud Pública, Mexico City, Mexico.
²² Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France.
²³ National Cancer Control Center, Haifa, Israel.
²⁴ Cancer Registry of Norway, Oslo, Norway.
²⁵ Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
²⁶ Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA.
²⁷ Norwegian Center for Minority and Migrant Health Research (NAKMI), Oslo, Norway.
²⁸ Department of Population Sciences, Beckman Research Institute, City of Hope, CA, USA.
²⁹ Isfahan University of Medical Sciences, Isfahan, Iran.
³⁰ Department of Surgery, Asan Medical Center, Seoul, Republic of Korea.
³¹ Cairo University, Cairo, Egypt.
³² Woman Imaging Unit, Radiodiagnosis Department, Kasr El Aini, Cairo University Hospitals, Cairo, Egypt.
³³ Department of Surgery, Yong Loo Lin School of Medicine, Singapore, Singapore.
³⁴ Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
³⁵ NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore.
³⁶ Gifu University, Gifu, Japan.
³⁷ Aga Khan University Hospital, Nairobi, Kenya.
³⁸ Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
³⁹ Nofer Institute of Occupational Medicine, Łódz, Poland.
⁴⁰ Department of Imaging, Royal Marsden NHS Foundation Trust, London, UK.
⁴¹ Division of Cancer Research, Ninewells Hospital & Medical School, Dundee, UK.
⁴² Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK.
⁴³ Ontario Breast Screening Program, Cancer Care Ontario, Toronto, Canada.
⁴⁴ Princess Margaret Cancer Centre, Toronto, Canada.
⁴⁵ University of Hawaii Cancer Center, Honolulu, HI, USA.
⁴⁶ Medical Biophysics, University of Toronto, Toronto, Canada.
⁴⁷ Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.

PMID: 27993168
PMCID: PMC5168805
DOI: 10.1186/s13058-016-0787-0

Abstract

Background: Inter-women and intra-women comparisons of mammographic density (MD) are needed in research, clinical and screening applications; however, MD measurements are influenced by mammography modality (screen film/digital) and digital image format (raw/processed). We aimed to examine differences in MD assessed on these image types.

Methods: We obtained 1294 pairs of images saved in both raw and processed formats from Hologic and General Electric (GE) direct digital systems and a Fuji computed radiography (CR) system, and 128 screen-film and processed CR-digital pairs from consecutive screening rounds. Four readers performed Cumulus-based MD measurements (n = 3441), with each image pair read by the same reader. Multi-level models of square-root percent MD were fitted, with a random intercept for woman, to estimate processed-raw MD differences.

Results: Breast area did not differ in processed images compared with that in raw images, but the percent MD was higher, due to a larger dense area (median 28.5 and 25.4 cm² respectively, mean √dense area difference 0.44 cm (95% CI: 0.36, 0.52)). This difference in √dense area was significant for direct digital systems (Hologic 0.50 cm (95% CI: 0.39, 0.61), GE 0.56 cm (95% CI: 0.42, 0.69)) but not for Fuji CR (0.06 cm (95% CI: -0.10, 0.23)). Additionally, within each system, reader-specific differences varied in magnitude and direction (p < 0.001). Conversion equations revealed differences converged to zero with increasing dense area. MD differences between screen-film and processed digital on the subsequent screening round were consistent with expected time-related MD declines.

Conclusions: MD was slightly higher when measured on processed than on raw direct digital mammograms. Comparisons of MD on these image formats should ideally control for this non-constant and reader-specific difference.

Keywords: Breast cancer; Breast density; Image processing; Mammographic density assessment; Methods.

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Figures

**Fig. 1**
Examples of raw and processed images from Hologic, GE and Fuji digital mammography systems. a Raw and e processed paired images captured on GE Senographe Essential (G2, UK). b Raw and f processed paired images captured on Hologic Lorad Selenia (H1, Chile). c Raw and g processed paired images captured on Fuji CR (F1). d Screen-film image and h its paired Fujifilm CR processed image (SFM/digital set F2, Australia). CC craniocaudal, L left, *MLO* mediolateral oblique, R right

**Fig. 2**
Scatter plot of paired √DA readings measured on processed (y axis) vs raw (x axis) digital images, by reader and system. *Dashed lines*, equality (if DA from processed images was read identically to raw images); *blue dots*, modelled linear conversion. Reader-specific and system-specific calibration equations for the conversion of raw √DA to processed √DA are supplied in (Additional file 7: Information 2). *√DA* square root of dense area, GE General Electric

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References

1. Boyd NF, Guo H, Martin LJ, Sun L, Stone J, Fishell E, et al. Mammographic density and the risk and detection of breast cancer. N Engl J Med. 2007;356:227–36. doi: 10.1056/NEJMoa062790. - DOI - PubMed
1. Warwick J, Birke H, Stone J, Warren RM, Pinney E, Brentnall AR, et al. Mammographic breast density refines Tyrer-Cuzick estimates of breast cancer risk in high-risk women: findings from the placebo arm of the International Breast Cancer Intervention Study I. Breast Cancer Res. 2014;16:451. doi: 10.1186/s13058-014-0451-5. - DOI - PMC - PubMed
1. Cuzick J, Warwick J, Pinney E, Duffy SW, Cawthorn S, Howell A, et al. Tamoxifen-induced reduction in mammographic density and breast cancer risk reduction: a nested case–control study. J Natl Cancer Inst. 2011;103:744–52. doi: 10.1093/jnci/djr079. - DOI - PubMed
1. Schousboe JT, Kerlikowske K, Loh A, Cummings SR. Personalizing mammography by breast density and other risk factors for breast cancer: analysis of health benefits and cost-effectiveness. Ann Intern Med. 2011;155:10–20. doi: 10.7326/0003-4819-155-1-201107050-00003. - DOI - PMC - PubMed
1. Nickson C, Arzhaeva Y, Aitken Z, Elgindy T, Buckley M, Li M, et al. AutoDensity: an automated method to measure mammographic breast density that predicts breast cancer risk and screening outcomes. Breast Cancer Res. 2013;15:R80. doi: 10.1186/bcr3474. - DOI - PMC - PubMed

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[1] Boyd NF, Guo H, Martin LJ, Sun L, Stone J, Fishell E, et al. Mammographic density and the risk and detection of breast cancer. N Engl J Med. 2007;356:227–36. doi: 10.1056/NEJMoa062790. - DOI - PubMed

[2] Boyd NF, Guo H, Martin LJ, Sun L, Stone J, Fishell E, et al. Mammographic density and the risk and detection of breast cancer. N Engl J Med. 2007;356:227–36. doi: 10.1056/NEJMoa062790. - DOI - PubMed

[3] Warwick J, Birke H, Stone J, Warren RM, Pinney E, Brentnall AR, et al. Mammographic breast density refines Tyrer-Cuzick estimates of breast cancer risk in high-risk women: findings from the placebo arm of the International Breast Cancer Intervention Study I. Breast Cancer Res. 2014;16:451. doi: 10.1186/s13058-014-0451-5. - DOI - PMC - PubMed

[4] Warwick J, Birke H, Stone J, Warren RM, Pinney E, Brentnall AR, et al. Mammographic breast density refines Tyrer-Cuzick estimates of breast cancer risk in high-risk women: findings from the placebo arm of the International Breast Cancer Intervention Study I. Breast Cancer Res. 2014;16:451. doi: 10.1186/s13058-014-0451-5. - DOI - PMC - PubMed

[5] Cuzick J, Warwick J, Pinney E, Duffy SW, Cawthorn S, Howell A, et al. Tamoxifen-induced reduction in mammographic density and breast cancer risk reduction: a nested case–control study. J Natl Cancer Inst. 2011;103:744–52. doi: 10.1093/jnci/djr079. - DOI - PubMed

[6] Cuzick J, Warwick J, Pinney E, Duffy SW, Cawthorn S, Howell A, et al. Tamoxifen-induced reduction in mammographic density and breast cancer risk reduction: a nested case–control study. J Natl Cancer Inst. 2011;103:744–52. doi: 10.1093/jnci/djr079. - DOI - PubMed

[7] Schousboe JT, Kerlikowske K, Loh A, Cummings SR. Personalizing mammography by breast density and other risk factors for breast cancer: analysis of health benefits and cost-effectiveness. Ann Intern Med. 2011;155:10–20. doi: 10.7326/0003-4819-155-1-201107050-00003. - DOI - PMC - PubMed

[8] Schousboe JT, Kerlikowske K, Loh A, Cummings SR. Personalizing mammography by breast density and other risk factors for breast cancer: analysis of health benefits and cost-effectiveness. Ann Intern Med. 2011;155:10–20. doi: 10.7326/0003-4819-155-1-201107050-00003. - DOI - PMC - PubMed

[9] Nickson C, Arzhaeva Y, Aitken Z, Elgindy T, Buckley M, Li M, et al. AutoDensity: an automated method to measure mammographic breast density that predicts breast cancer risk and screening outcomes. Breast Cancer Res. 2013;15:R80. doi: 10.1186/bcr3474. - DOI - PMC - PubMed

[10] Nickson C, Arzhaeva Y, Aitken Z, Elgindy T, Buckley M, Li M, et al. AutoDensity: an automated method to measure mammographic breast density that predicts breast cancer risk and screening outcomes. Breast Cancer Res. 2013;15:R80. doi: 10.1186/bcr3474. - DOI - PMC - PubMed

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Mammographic density assessed on paired raw and processed digital images and on paired screen-film and digital images across three mammography systems

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Mammographic density assessed on paired raw and processed digital images and on paired screen-film and digital images across three mammography systems

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