Original Article
Mammographic Density and the Risk and Detection of Breast Cancer
N Engl J Med 2007; 356:227-236January 18, 2007
- Abstract
Background
Extensive mammographic density is associated with an increased risk of breast cancer and makes the detection of cancer by mammography difficult, but the influence of density on risk according to method of cancer detection is unknown.
Methods
We carried out three nested case–control studies in screened populations with 1112 matched case–control pairs. We examined the association of the measured percentage of density in the baseline mammogram with risk of breast cancer, according to method of cancer detection, time since the initiation of screening, and age.
Results
As compared with women with density in less than 10% of the mammogram, women with density in 75% or more had an increased risk of breast cancer (odds ratio, 4.7; 95% confidence interval [CI], 3.0 to 7.4), whether detected by screening (odds ratio, 3.5; 95% CI, 2.0 to 6.2) or less than 12 months after a negative screening examination (odds ratio, 17.8; 95% CI, 4.8 to 65.9). Increased risk of breast cancer, whether detected by screening or other means, persisted for at least 8 years after study entry and was greater in younger than in older women. For women younger than the median age of 56 years, 26% of all breast cancers and 50% of cancers detected less than 12 months after a negative screening test were attributable to density in 50% or more of the mammogram.
Conclusions
Extensive mammographic density is strongly associated with the risk of breast cancer detected by screening or between screening tests. A substantial fraction of breast cancers can be attributed to this risk factor.
Media in This Article
Figure 1
Box Plots Showing Percent Density in the Baseline Mammograms of Matched Pairs of Case Patients and Control Subjects.Table 1
Selected Characteristics of Mammographic-Screening Programs.Article Activity
- Article
The radiographic appearance of the breast varies among women because of differences in tissue composition and differences in the radiographic attenuation properties of fat, stroma, and epithelium.1 Fat is radiographically lucent and appears dark on a mammogram. In contrast, epithelium and stroma are radiographically dense and look light, an appearance we refer to as mammographic density. In 1976, Wolfe described an association between a qualitative classification of mammographic densities and the risk of breast cancer,2,3 and now substantial literature shows that more extensive density is associated with an increased risk of breast cancer. Women with dense tissue in 75% or more of the breast have a risk of breast cancer four to six times as great as the risk among women with little or no dense tissue.4-11
Extensive mammographic density may also make breast cancer more difficult to detect by mammography and thus increases the risk of the development of cancer between mammographic screening tests.12-14 Because density influences the detection of cancer, estimates of the risk of breast cancer associated with mammographic density may be distorted. Risk may be underestimated if it is based solely on cancers found at screening, because cancers masked by dense tissue will be omitted. However, risk may be overestimated if it is based only on cancers found by means other than screening, because cancers not detected by screening will be overrepresented.
Whitehead et al., using data from the 1970s,12 showed that a masking effect of density did exist but that it operated in addition to differences in the risk of breast cancer related to the classification of breast patterns described by Wolfe.2 Other studies have reached similar conclusions but have had short periods of follow-up13 or have not distinguished between breast cancers detected by screening and those detected by methods other than screening.14 There are, therefore, few data that allow an examination of the extent to which mammographic density, assessed quantitatively and using modern mammography, influences the risk of breast cancer at screening, between screening examinations, or over time.
The purpose of this study was to describe the association between mammographic density in the baseline mammogram and the subsequent risk of breast cancer. We studied the association according to the method of cancer detection and over time.
Methods
Screened Populations
We used data from three nested case–control studies carried out in populations that were screened with the use of mammography. The National Breast Screening Study (NBSS) was a randomized trial of screening with mammography and physical examination.15,16 The Screening Mammography Program of British Columbia (SMPBC) uses mammography as the only method of screening at its screening centers, and the Ontario Breast Screening Program (OBSP) uses mammography and physical examination as its methods of screening. Selected characteristics of the three screening programs included in this study are shown in Table 1Table 1
Selected Characteristics of Mammographic-Screening Programs.. The study was approved by the ethics committees at the University of Toronto, the University Health Network (Toronto), the OBSP, and the University of British Columbia.Selection of Subjects
For the OBSP and the SMPBC, lists were prepared of subjects with histologically verified invasive breast cancer that was diagnosed from 1993 through 1998 for the OBSP and from 1993 through 1999 for the SMPBC. Subjects who had a diagnosis of breast cancer less than 12 months after their first screening examination were excluded. For each case of breast cancer, the method of detection (screening or other means) was determined by each program, independent of this study, and was based on the active follow-up of women in whom abnormalities had been found. In addition, each program periodically carried out linkage with provincial and national cancer registries to identify breast cancers diagnosed in subjects in whom breast cancer had not been detected at screening.
Eligible case patients in the OBSP and the SMPBC were sent a letter, followed by a telephone call, and were asked to provide informed consent for the release of their mammogram and to complete a self-administered questionnaire. For each case patient who provided consent, we selected up to 10 control subjects, individually matched by age (within 1 year), by year of entry to the screening program, and by screening center, and who had a duration of follow-up that was at least as long as the time the corresponding case subject had been in the program before the diagnosis of breast cancer. Potential control subjects were approached in random order, and we selected the first to provide consent who had an available mammogram. Fifty percent of case patients and 54% of control subjects selected from the OBSP and the SMPBC agreed to take part.
Written informed consent for research applications using the data collected had been obtained at entry to the NBSS. All 354 patients in whom invasive breast cancer was diagnosed between 1981 and 1990 and their matched controls were included.6
Data Collection
In the NBSS, information about risk factors for breast cancer was obtained by self-administered questionnaire at the time of study entry. For the other two programs, information was collected by self-administered questionnaire at the time of recruitment into the present study. Information about demographic characteristics, use (including the date started and duration of use) or nonuse of hormone therapy, and menstrual and reproductive risk factors was collected with reference to the time of the first screening mammogram.
Assessment of Mammographic Density
Mammographic density was assessed independently by radiologists and by a computer-assisted method. Two radiologists who had previously classified density17 each read approximately half the mammograms. The craniocaudal view of the unaffected breast of case patients and the corresponding image of matched control subjects were read in sets of 100 images on a multiviewer, in random order, without knowledge of case or control status. Each image was placed into one of six categories of density (0%, <10%, 10 to <25%, 25 to <50%, 50 to <75%, and ≥75%) that have been used in previous work.6,17 Ten percent of each set was reread by each radiologist, and both radiologists read a further 10%. The reliability of each reader was 0.73 to 0.89, and reliability between readers was 0.68.
The same craniocaudal images that were read by the radiologists were digitized with the use of a Lumisys 85 digitizer (Lumisys) and measured by one observer using a computer-assisted technique described elsewhere.18 The mammograms were read in sets of approximately 120, including equal numbers of randomly ordered case patients and control subjects, by the same observer, who was unaware of case or control status or of the classifications made by the radiologists. A random sample of 10% of the images was reread, within and between each set, and reproducibility was 0.94 both within sets and between sets.
Statistical Analysis
Of the 1209 case–control pairs we recruited, 95 were excluded because of missing data (NBSS, 24; OBSP, 34; SMPBC, 37), leaving a total of 1114 matched case–control pairs for analysis. The radiologists did not classify 2 case patients, so their results have 1112 case–control pairs.
We compared selected characteristics of the case and control subjects, using paired t-tests for symmetrically distributed continuous variables, Wilcoxon rank-sum tests for continuous variables with skewed distributions, and Mantel–Haenszel chi-square tests for categorical variables. All P values were calculated from two-tailed tests of statistical significance.
We examined the association of mammographic density with the risk of breast cancer, using logistic regression. We used logistic regression to analyze unmatched data and conditional logistic regression to analyze matched data.19 The categories of density of 0% and less than 10% were combined because of small numbers in some categories after the data were divided according to method of cancer detection. An increase in risk associated with greater density was tested by the Cochran–Armitage test for trend. For the computer-assisted method, the percentage of mammographic density was modeled as a continuous variable. All analyses were adjusted for other risk factors for breast cancer. Attributable risk was calculated with the use of the following formula: attributable risk=(RR−1)Pc÷RR, where RR denotes relative risk of greater than 50%, and Pc prevalence of density of greater than 50% in case patients.20
Results
The results shown are for the classifications by the radiologists. Matched and unmatched results for the two readers were very similar to the unmatched results, and most results shown are unmatched, since these are easier to display. Matched results for both radiologists and the computer-assisted measure are shown in the tables in the Supplementary Appendix (available with the full text of this article at www.nejm.org).
Characteristics of the Subjects
Table 2Table 2
Selected Characteristics of the Subjects. shows selected characteristics of case patients and control subjects for the three screening programs. Earlier age at menarche, later age at first birth, nulliparity, a smaller number of live births, later age at menopause, a family history of breast cancer, and use of hormone therapy were all more frequent among patients with breast cancer than among control subjects. The average percentage of mammographic density in the baseline mammogram was 5.8 percentage points greater in case patients than in controls.Percentage of Mammographic Density and the Risk and Detection of Breast Cancer
Table 3Table 3
Mammographic Density and Risk of Breast Cancer According to Method of Detection. shows the distribution of case patients and control subjects in the combined studies according to the percentage of mammographic density and the method of detection. Odds ratios from unmatched analyses were adjusted for age, body-mass index, age at menarche, parity, number of live births, age at first birth, menopausal status, age at menopause, hormone-replacement therapy (ever or never), breast cancer in first-degree relatives (0, 1, or 2 or more), study (NBSS, OBSP, or SMPBC), and observation time (1 to ≤2 years, >2 to ≤4 years, or >4 years). When those who had less than 10% mammographic density were compared with those who had 75% or more, the odds ratio was 4.7 (95% confidence interval [CI], 3.0 to 7.4) for all cancers. In the 717 cases of breast cancer detected at screening, the odds ratio was 3.5 (95% CI, 2.0 to 6.2). In the 124 cases of breast cancer detected less than 12 months after the last screening examination, the odds ratio for the risk of breast cancer in those with density of 75% or more was 17.8 (95% CI, 4.8 to 65.9). For cancers detected 12 months or more after the last screening examination, the odds ratio for those with density of 75% or more was 5.7 (95% CI, 2.1 to 15.5). Within each category of detection, there was a monotonic increase in risk with each category of density, and the tests for trend were all significant (P<0.001).Similar results were seen in each of the three screening programs. The odds ratios for 75% or more density as compared with 10% or less for all cancers were 5.7 (95% CI, 2.8 to 11.3) for the NBSS, 3.4 (95% CI, 1.1 to 10.3) for the OBSP, and 4.5 (95% CI, 1.9 to 11.0) for the SMPBC (data not shown). Matched analyses for both the radiologists and the computer-assisted measure of density gave similar results (see Tables 1 and 2 in the Supplementary Appendix).
Risk According to Method of Detection and Years since Entry
Table 4Table 4
Risk of Breast Cancer Associated with the Percentage of Mammographic Density According to Time since Study Entry. shows the risk of breast cancer in the combined data according to mammographic density (as classified by radiologists), method of detection of breast cancer, and number of years after entry into the screening programs, grouped into three time periods. Percentage of density was associated with an increased risk of breast cancer in all categories of detection and at all time periods, up to 8 years after entry. However, for breast cancers detected by methods other than screening, risk was notably higher in the first 2 years after the first screening examination. The continuous computer-assisted measure showed a higher percentage of density in the baseline mammograms of women in whom breast cancer later developed, as compared with women in whom no breast cancer developed, regardless of whether the cancer was detected by screening or by methods other than screening, up to 8 years after entry (Figure 1Figure 1Box Plots Showing Percent Density in the Baseline Mammograms of Matched Pairs of Case Patients and Control Subjects.).Mammographic Density and Attributable Risks of Breast Cancer
Table 5Table 5
Mammographic Density and Attributable Risks of Breast Cancer. shows the prevalence of a mammographic density of 50% or more and the associated relative and attributable risks of breast cancer for each category of cancer detection. The attributable risks of breast cancer, which assume causality, for a mammographic density of 50% or more were 16% for all cancers, 12% for cancers detected by screening, 40% for cancers detected less than 12 months after a negative screening test, and 16% for cancers detected 12 months or more after a screening examination.For women below the median age of 56 years, the prevalence of mammographic density of 50% or more was about three times as great as the prevalence in older women in each category of detection, and the attributable risks of breast cancer were 26% for all cancers, 21% for cancers detected by screening, 50% for cancers detected less than 12 months after a negative screening examination, and 28% for cancers detected 12 months or more after a screening examination.
Discussion
Our results showed that after adjustment for other risk factors, extensive mammographic density was strongly and reproducibly associated with an increased risk of breast cancer, regardless of whether the cancer was detected by screening or other means. We also found that this increased risk persisted for an extended period of time. Calculations of attributable risk showed that mammographic density accounted for a substantial proportion of cases of breast cancer, particularly in younger women, in whom 26% of all breast cancers and 50% of cancers detected less than 12 months after a negative screening examination were associated with density in 50% or more of the mammogram.
The marked increase in the risk of breast cancer associated with extensive mammographic density up to 12 months after screening is probably due to cancers that were present at the time of screening but were not detected because of masking by dense breast tissue. Calculation of the risk of breast cancer associated with mammographic density that includes only screen-detected cancers will thus underestimate the true risk, because cancers that are masked by density are omitted. However, risk estimates based on cancers detected up to 12 months after screening will overestimate risk, because cancers that were present but not detected at screening (because of masking by density) will be overrepresented. The annual incidence of breast cancer associated with mammographic density is thus best estimated with these data by combining cancers that were detected by screening with those that were diagnosed up to 12 months after a screening examination. The risk of breast cancer associated with mammographic density 12 months or more after a screening examination was similar to the overall risk.
It is unlikely that bias, confounding, or chance can explain these results. Measurement of mammographic density was made by two independent methods, without knowledge of the status of case patients or control subjects, and similar results were obtained in each of three separate populations. In the NBSS, all eligible case patients had mammograms and other data available, but not all eligible case patients in the OBSP and the SMPBC participated. However, differences in the percentage of density between case patients and controls, and the associated risks of breast cancer, were similar in each of the three populations and similar to risk estimates found by others who used quantitative methods to classify density.4,5,7,21,22 Bias in selection affecting percentage of density is thus unlikely.
Recall bias might influence information about nonmammographic risk factors obtained after the diagnosis of breast cancer in the OBSP and the SMPBC. However, in the NBSS, data collection occurred before the diagnosis of breast cancer. The distribution of nonmammographic risk factors was similar in each of the three populations. We also observed the expected effects on risk of breast cancer of most known risk factors. Recall bias affecting risk factors in the OBSP and the SMPBC is thus unlikely.
Other studies have shown that mammographic density is associated with an increased risk of breast cancer at screening and in the intervals after a negative mammographic examination.23,24 However, some of these studies have been based on older methods of mammography than those we used, have used qualitative classifications of density, or have not adjusted risk estimates for covariates.12-14
Among women with extensive mammographic density, the extent to which the markedly increased risk of breast cancer up to 12 months after a negative screening examination is due to masking or to the rapid growth of tumors in dense breasts is unknown.23-28 Density may mask nonpalpable cancers presenting on mammography as a mass or architectural distortion but is less likely to mask calcification, which is present in about 40% of cancers.29,30 Mammography was the only screening method in the SMPBC and the method by which 88% of cancers were detected at screening in the OBSP.31 In the NBSS, 75% of cancers were detected by mammography alone or in combination with physical examination.15,16
Because the increase, by a factor of 17, in the risk of breast cancer associated with extensive mammographic density is apparently limited to the 12 months after a screening examination, masking — rather than rapid growth — seems likely to be the principal mechanism at work. These results further suggest that annual screening examinations in women with extensive mammographic density are not likely to increase the rate of detection of cancers; attention should be directed to the development and evaluation of alternative imaging techniques for such women. Digital mammography,32 ultrasonography,33 and magnetic resonance imaging34 may increase the detection of cancer in women who have extensive mammographic density and in whom the risk of breast cancer, detected at screening and between screening examinations, is greatest.
Supported by grants from the National Cancer Institute of Canada and the Canadian Breast Cancer Research Alliance. Dr. Boyd is supported by the Lee K. and Margaret Lau Chair in Breast Cancer Research.
No potential conflict of interest relevant to this article was reported.
Source Information
From the Campbell Family Institute for Breast Cancer Research (N.F.B., H.G., L.J.M., L.S.); the Ontario Cancer Institute (N.F.B, H.G., L.J.M., L.S., J.S., S.M.); the Departments of Radiology and Imaging Research, Women's College Hospital (E.F.) and Sunnybrook Health Sciences Centre (R.A.J., M.J.Y.); and the Ontario Breast Screening Program, Cancer Care Ontario (A.C.) — all in Toronto; and the British Columbia Cancer Agency, Vancouver (G.H.) — all in Canada.
Address reprint requests to Dr. Boyd at Ontario Cancer Institute, 610 University Ave., Room 10-415, Toronto, ON M5G 2M9, Canada, or at boyd@uhnres.utoronto.ca.
- References
References
1
Johns PC ,Yaffe MJ . X-ray characterisation of normal and neoplastic breast tissues. Phys Med Biol 1987;32:675-695
CrossRef | Web of Science | Medline2
Wolfe JN . Breast patterns as an index of risk for developing breast cancer. AJR Am J Roentgenol 1976;126:1130-1137
Web of Science | Medline3
Wolfe JN . Risk for breast cancer development determined by mammographic parenchymal pattern. Cancer 1976;37:2486-2492
CrossRef | Web of Science | Medline4
Ursin G ,Ma H ,Wu AH , et al. Mammographic density and breast cancer in three ethnic groups. Cancer Epidemiol Biomarkers Prev 2003;12:332-338
Web of Science | Medline5
Byrne C ,Schairer C ,Wolfe J , et al. Mammographic features and breast cancer risk: effects with time, age, and menopause status. J Natl Cancer Inst 1995;87:1622-1629
CrossRef | Web of Science | Medline6
Boyd NF ,Byng JW ,Jong RA , et al. Quantitative classification of mammographic densities and breast cancer risk: results from the Canadian National Breast Screening Study. J Natl Cancer Inst 1995;87:670-675
CrossRef | Web of Science | Medline7
Wolfe JN ,Saftlas AF ,Salane M . Mammographic parenchymal patterns and quantitative evaluation of mammographic densities: a case-control study. AJR Am J Roentgenol 1987;148:1087-1092
Web of Science | Medline8
Byrne C ,Schairer C ,Brinton LA , et al. Effects of mammographic density and benign breast disease on breast cancer risk (United States). Cancer Causes Control 2001;12:103-110
CrossRef | Web of Science | Medline9
Harvey JA ,Bovbjerg VE . Quantitative assessment of mammographic breast density: relationship with breast cancer risk. Radiology 2004;230:29-41
CrossRef | Web of Science | Medline10
Boyd NF ,Rommens JM ,Vogt K , et al. Mammographic breast density as an intermediate phenotype for breast cancer. Lancet Oncol 2005;6:798-808
CrossRef | Web of Science | Medline11
McCormack VA ,dos Santos Silva I . Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. Cancer Epidemiol Biomarkers Prev 2006;15:1159-1169
CrossRef | Web of Science | Medline12
Whitehead J ,Carlile T ,Kopecky KJ , et al. Wolfe mammographic parenchymal patterns: a study of the masking hypothesis of Egan and Mosteller. Cancer 1985;56:1280-1286
CrossRef | Web of Science | Medline13
Sala E ,Warren R ,McCann J ,Duffy S ,Day N ,Luben R . Mammographic parenchymal patterns and mode of detection: implications for the breast screening programme. J Med Screen 1998;5:207-212
Web of Science | Medline14
van Gils CH ,Otten JD ,Verbeek AL ,Hendriks JH . Mammographic breast density and risk of breast cancer: masking bias or causality? Eur J Epidemiol 1998;14:315-320
CrossRef | Web of Science | Medline15
Miller AB ,Baines CJ ,To T ,Wall C . Canadian National Breast Screening Study: 1. Breast cancer detection and death rates among women aged 40 to 49 years. CMAJ 1992;147:1459-1476[Erratum, CMAJ 1993;148:718.]
Web of Science | Medline16
Miller AB ,Baines CJ ,To T ,Wall C . Canadian National Breast Screening Study: 2. Breast cancer detection and death rates among women aged 50 to 59 years. CMAJ 1992;147:1477-1488[Erratum, CMAJ 1993;148:718.]
Web of Science | Medline17
Jong R ,Fishell E ,Little L ,Lockwood G ,Boyd NF . Mammographic signs of potential relevance to breast cancer risk: the agreement of radiologists' classification. Eur J Cancer Prev 1996;5:281-286
CrossRef | Web of Science | Medline18
Byng JW ,Boyd NF ,Fishell E ,Jong RA ,Yaffe MJ . The quantitative analysis of mammographic densities. Phys Med Biol 1994;39:1629-1638
CrossRef | Web of Science | Medline19
Breslow NE, Day NE. Statistical methods in cancer research. Vol. 1. The analysis of case-control studies. Lyon, France: International Agency for Research on Cancer, 1980. (IARC scientific publications no. 32.)
20
Rothman KJ, Greenland S. Modern epidemiology. 2nd ed. Philadelphia: Lippincott-Raven, 1998.
21
Boyd NF ,O'Sullivan B ,Campbell JE , et al. Mammographic signs as risk factors for breast cancer. Br J Cancer 1982;45:185-193
CrossRef | Web of Science | Medline22
Saftlas AF ,Hoover RN ,Brinton LA , et al. Mammographic densities and risk of breast cancer. Cancer 1991;67:2833-2838
CrossRef | Web of Science | Medline23
Ma L ,Fishell E ,Wright B ,Hanna W ,Allan S ,Boyd NF . Case-control study of factors associated with failure to detect breast cancer by mammography. J Natl Cancer Inst 1992;84:781-785
CrossRef | Web of Science | Medline24
Mandelson MT ,Oestreicher N ,Porter PL , et al. Breast density as a predictor of mammographic detection: comparison of interval- and screen-detected cancers. J Natl Cancer Inst 2000;92:1081-1087
CrossRef | Web of Science | Medline25
Buist DS ,Porter PL ,Lehman C ,Taplin SH ,White E . Factors contributing to mammography failure in women aged 40-49 years. J Natl Cancer Inst 2004;96:1432-1440
CrossRef | Web of Science | Medline26
Porter PL ,El-Bastawissi AY ,Mandelson MT , et al. Breast tumor characteristics as predictors of mammographic detection: comparison of interval- and screen-detected cancers. J Natl Cancer Inst 1999;91:2020-2028
CrossRef | Web of Science | Medline27
Roubidoux MA ,Bailey JE ,Wray LA ,Helvie MA . Invasive cancers detected after breast cancer screening yielded a negative result: relationship of mammographic density to tumor prognostic factors. Radiology 2004;230:42-48
CrossRef | Web of Science | Medline28
Gilliland FD ,Joste N ,Stauber P , et al. Biologic characteristics of interval and screen-detected breast cancers. J Natl Cancer Inst 2000;92:743-749
CrossRef | Web of Science | Medline29
Sickles EA . Mammographic features of 300 consecutive nonpalpable breast cancers. AJR Am J Roentgenol 1986;146:661-663
Web of Science | Medline30
Meyer JE ,Kopans DB ,Stomper PC ,Lindfors KK . Occult breast abnormalities: percutaneous preoperative needle localization. Radiology 1984;150:335-337
Web of Science | Medline31
Knight JA ,Libstug AR ,Moravan V ,Boyd NF . An assessment of the influence of clinical breast examination reports on the interpretation of mammograms in a breast screening program. Breast Cancer Res Treat 1998;48:65-71
CrossRef | Web of Science | Medline32
Pisano ED ,Gatsonis C ,Hendrick E , et al. Diagnostic performance of digital versus film mammography for breast-cancer screening. N Engl J Med 2005;353:1773-1783
Full Text | Web of Science | Medline33
Crystal P ,Strano SD ,Shcharynski S ,Koretz MJ . Using sonography to screen women with mammographically dense breasts. AJR Am J Roentgenol 2003;181:177-182
Web of Science | Medline34
Wright H ,Listinsky J ,Rim A , et al. Magnetic resonance imaging as a diagnostic tool for breast cancer in premenopausal women. Am J Surg 2005;190:572-575
CrossRef | Web of Science | Medline
- Citing Articles (162)
Citing Articles
1
Hui Li, Maryellen L. Giger, Li Lan, Jeremy Bancroft Brown, Aoife MacMahon, Mary Mussman, Olufunmilayo I. Olopade, Charlene Sennett. (2012) Computerized Analysis of Mammographic Parenchymal Patterns on a Large Clinical Dataset of Full-Field Digital Mammograms: Robustness Study with Two High-Risk Datasets. Journal of Digital Imaging
CrossRef2
, Virginia Lope, Beatriz Pérez-Gómez, Carmen Sánchez-Contador, María Carmen Santamariña, Pilar Moreo, Carmen Vidal, Maria Soledad Laso, Maria Ederra, Carmen Pedraz-Pingarrón, Isabel González-Román, Milagros García-López, Dolores Salas-Trejo, Mercé Peris, María Pilar Moreno, Jose Antonio Vázquez-Carrete, Francisca Collado, Nuria Aragonés, Marina Pollán. (2012) Obstetric history and mammographic density: a population-based cross-sectional study in Spain (DDM-Spain). Breast Cancer Research and Treatment
CrossRef3
Joanne Kotsopoulos, Steven A. Narod. (2012) Androgens and breast cancer. Steroids 77:1-2, 1-9
CrossRef4
Vivian van Breest Smallenburg, Lucien E.M. Duijm, Adri C. Voogd, Johanna H. Groenewoud, Frits H. Jansen, Mike van Beek, Marieke W.J. Louwman. (2012) Lower sensitivity of screening mammography after previous benign breast surgery. International Journal of Cancer 130:1, 122-128
CrossRef5
Michael K. Wendt, Maozhen Tian, William P. Schiemann. (2012) Deconstructing the mechanisms and consequences of TGF-β-induced EMT during cancer progression. Cell and Tissue Research 347:1, 85-101
CrossRef6
Ingrid H. R. Hauge, Peter Hogg, Katy Szczepura, Paul Connolly, George McGill, Claire Mercer. (2012) The readout thickness versus the measured thickness for a range of screen film mammography and full-field digital mammography units. Medical Physics 39:1, 263
CrossRef7
Lusine Yaghjyan, Graham A. Colditz, Bettina Drake. (2012) Vitamin D and mammographic breast density: a systematic review. Cancer Causes & Control 23:1, 1-13
CrossRef8
Mark S. Pearce, Peter W. G. Tennant, Kay D. Mann, Tessa M. Pollard, Lesley McLean, Brenda Kaye, Louise Parker. (2012) Lifecourse predictors of mammographic density: the Newcastle Thousand Families cohort Study. Breast Cancer Research and Treatment 131:1, 187-195
CrossRef9
John A Shepherd, Karla Kerlikowske. (2012) Do fatty breasts increase or decrease breast cancer risk?. Breast Cancer Research 14:1, 102
CrossRef10
Annemieke W. J. Opstal-van Winden, Roel C. H. Vermeulen, Petra H. M. Peeters, Jos H. Beijnen, Carla H. Gils. (2011) Early diagnostic protein biomarkers for breast cancer: how far have we come?. Breast Cancer Research and Treatment
CrossRef11
Irene Ma, Amylou Dueck, Richard Gray, Nabil Wasif, Marina Giurescu, Roxanne Lorans, Victor Pizzitola, Barbara Pockaj. (2011) Clinical and Self Breast Examination Remain Important in the Era of Modern Screening. Annals of Surgical Oncology
CrossRef12
Valentina Assi, Jane Warwick, Jack Cuzick, Stephen W. Duffy. (2011) Clinical and epidemiological issues in mammographic density. Nature Reviews Clinical Oncology 9:1, 33-40
CrossRef13
J. A. A. M. van Dijck, J. D. M. Otten, N. Karssemeijer, P. Kenemans, A. L. M. Verbeek, M. J. van der Mooren. (2011) Less mammographic density after nasal versus oral administration of postmenopausal hormone therapy. Climacteric 14:6, 683-688
CrossRef14
E. Lundström, A.L. Hirschberg, G. Söderqvist. (2011) Digitized assessment of mammographic breast density – Effects of continuous combined hormone therapy, tibolone and black cohosh compared to placebo. Maturitas 70:4, 361-364
CrossRef15
M. B. Terry, C. A. Schaefer, J. D. Flom, Y. Wei, P. Tehranifar, Y. Liao, S. Buka, K. B. Michels. (2011) Prenatal smoke exposure and mammographic density in mid-life. Journal of Developmental Origins of Health and Disease 2:06, 340-352
CrossRef16
, Virginia Lope, Beatriz Pérez-Gómez, María Pilar Moreno, Carmen Vidal, Dolores Salas-Trejo, Nieves Ascunce, Isabel González Román, Carmen Sánchez-Contador, María Carmen Santamariña, Jose Antonio Vázquez Carrete, Francisca Collado-García, Carmen Pedraz-Pingarrón, María Ederra, Francisco Ruiz-Perales, Mercé Peris, Soledad Abad, Anna Cabanes, Marina Pollán. (2011) Childhood factors associated with mammographic density in adult women. Breast Cancer Research and Treatment 130:3, 965-974
CrossRef17
M. B. I. Lobbes, J. P. M. Cleutjens, V. Lima Passos, C. Frotscher, M. J. Lahaye, K. B. M. I. Keymeulen, R. G. Beets-Tan, J. Wildberger, C. Boetes. (2011) Density is in the eye of the beholder: visual versus semi-automated assessment of breast density on standard mammograms. Insights into Imaging
CrossRef18
Beatriz Pérez-Gómez, Franciso Ruiz, Inmaculada Martínez, María Casals, Josefa Miranda, Carmen Sánchez-Contador, Carmen Vidal, Rafael Llobet, Marina Pollán, Dolores Salas. (2011) Women’s features and inter-/intra-rater agreement on mammographic density assessment in full-field digital mammograms (DDM-SPAIN). Breast Cancer Research and Treatment
CrossRef19
Marla R. Lander, László Tabár. (2011) Automated 3-D Breast Ultrasound as a Promising Adjunctive Screening Tool for Examining Dense Breast Tissue. Seminars in Roentgenology 46:4, 302-308
CrossRef20
Min Sun Bae, Wonshik Han, Hye Ryoung Koo, Nariya Cho, Jung Min Chang, Ann Yi, In-Ae Park, Dong-Young Noh, Woo Suk Choi, Woo Kyung Moon. (2011) Characteristics of breast cancers detected by ultrasound screening in women with negative mammograms. Cancer Science 102:10, 1862-1867
CrossRef21
Selin Carkaci, Lumarie Santiago, Beatriz E. Adrada, Gary J. Whitman. (2011) Screening for Breast Cancer with Sonography. Seminars in Roentgenology 46:4, 285-291
CrossRef22
C. Desmetz, A. Mange, T. Maudelonde, J. Solassol. (2011) Autoantibody signatures: progress and perspectives for early cancer detection. Journal of Cellular and Molecular Medicine 15:10, 2013-2024
CrossRef23
Beverly E. Hashimoto. (2011) New Sonographic Breast Technologies. Seminars in Roentgenology 46:4, 292-301
CrossRef24
Vassilios Papantoniou, Evangelia Sotiropoulou, Pipitsa Valsamaki, Angeliki Tsaroucha, Maria Sotiropoulou, Nikolaos Ptohis, Aikaterini Stipsanelli, Konstantinos Dimitrakakis, Spyridon Marinopoulos, Spyridon Tsiouris, Aris Antsaklis. (2011) Breast density, scintimammographic 99mTc(V)DMSA uptake, and calcitonin gene related peptide (CGRP) expression in mixed invasive ductal associated with extensive in situ ductal carcinoma (IDC + DCIS) and pure invasive ductal carcinoma (IDC): correlation with estrogen receptor (ER) status, proliferation index Ki-67, and histological grade. Breast Cancer 18:4, 286-291
CrossRef25
Yidong Zhou, Bo Pan, Feng Mao, Qingli Zhu, Zhen Huo, Hongyan Wang, Feng Cai, Zhiyong Liang, Changjun Wang, Yanna Zhang, Qiang Sun. (2011) A Hidden Breast Lump Covered by Nipple Appendices in a Patient with von Recklinghausen Disease: A Case Report and Review of the Literature. Clinical Breast Cancer
CrossRef26
Steven A. Narod. (2011) Screening of women at high risk for breast cancer. Preventive Medicine 53:3, 127-130
CrossRef27
Brandy M. Heckman-Stoddard, Kathleen A. Foster, Barbara K. Dunn. (2011) Update on Phase I/II Breast Cancer Prevention Trials. Current Breast Cancer Reports 3:3, 131-141
CrossRef28
K. Kerlikowske, A. I. Phipps. (2011) Breast Density Influences Tumor Subtypes and Tumor Aggressiveness. JNCI Journal of the National Cancer Institute 103:15, 1143-1145
CrossRef29
Huong T. Le-Petross, Mahesh K. Shetty. (2011) Magnetic Resonance Imaging and Breast Ultrasonography as an Adjunct to Mammographic Screening in High-Risk Patients. Seminars in Ultrasound, CT, and MRI 32:4, 266-272
CrossRef30
M. Nielsen, G. Karemore, M. Loog, J. Raundahl, N. Karssemeijer, J.D.M. Otten, M.A. Karsdal, C.M. Vachon, C. Christiansen. (2011) A novel and automatic mammographic texture resemblance marker is an independent risk factor for breast cancer. Cancer Epidemiology 35:4, 381-387
CrossRef31
Guido Schoor, Ellen Paap, Mireille J. M. Broeders, André L. M. Verbeek. (2011) Residual confounding after adjustment for age: a minor issue in breast cancer screening effectiveness. European Journal of Epidemiology 26:8, 585-588
CrossRef32
Cindy Snyder, Patsy E. Crihfield. (2011) Performing Breast Cancer Risk Assessments in a Community Setting. Clinical Journal of Oncology Nursing 15:4, 361-364
CrossRef33
L. Aibar, A. Santalla, M.S. López- Criado, I. González–Pérez, M.A. Calderón, J.L. Gallo, J. Fernández -Parra. (2011) Clasificación radiológica y manejo de las lesiones mamarias. Clínica e Investigación en Ginecología y Obstetricia 38:4, 141-149
CrossRef34
Sagar Ghosh, Tao Kang, Howard Wang, Yanfen Hu, Rong Li. (2011) Mechanical phenotype is important for stromal aromatase expression. Steroids 76:8, 797-801
CrossRef35
Hsiao-Wen Tsai, Nae-Fang Twu, Chin-Chu Ko, Ming-Shyen Yen, Ming Jie Yang, Kuan-Chong Chao, Lily Wen, Chih-Yao Chen, Yi Hong Chou, Yi-Jen Chen. (2011) Compliance with screening mammography and breast sonography of young Asian women. European Journal of Obstetrics & Gynecology and Reproductive Biology 157:1, 89-93
CrossRef36
Zsolt Nagy, Mónika Csanád, Katalin Tóth, Szabolcs Máté, József Gábor Joó. (2011) A BRCA-génmutációt hordozó nők klinikogenetikai ellátása: szűrés, diagnosztika, terápia. Orvosi Hetilap 152:23, 913-918
CrossRef37
Michiel G J Kallenberg, Mariëtte Lokate, Carla H van Gils, Nico Karssemeijer. (2011) Automatic breast density segmentation: an integration of different approaches. Physics in Medicine and Biology 56:9, 2715-2729
CrossRef38
J. Cuzick, J. Warwick, E. Pinney, S. W. Duffy, S. Cawthorn, A. Howell, J. F. Forbes, R. M. L. Warren. (2011) Tamoxifen-Induced Reduction in Mammographic Density and Breast Cancer Risk Reduction: A Nested Case-Control Study. JNCI Journal of the National Cancer Institute 103:9, 744-752
CrossRef39
Rachel Novotny, Yihe Daida, Yukiko Morimoto, John Shepherd, Gertraud Maskarinec. (2011) Puberty, body fat, and breast density in girls of several ethnic groups. American Journal of Human Biology 23:3, 359-365
CrossRef40
John J. Heine, Ke Cao, Dana E. Rollison, Gail Tiffenberg, Jerry A. Thomas. (2011) A Quantitative Description of the Percentage of Breast Density Measurement Using Full-field Digital Mammography. Academic Radiology 18:5, 556-564
CrossRef41
Vittorio Corsetti, Nehmat Houssami, Marco Ghirardi, Aurora Ferrari, Michela Speziani, Sergio Bellarosa, Giuseppe Remida, Cristina Gasparotti, Enzo Galligioni, Stefano Ciatto. (2011) Evidence of the effect of adjunct ultrasound screening in women with mammography-negative dense breasts: Interval breast cancers at 1year follow-up. European Journal of Cancer 47:7, 1021-1026
CrossRef42
Jack Cuzick, Andrea DeCensi, Banu Arun, Powel H Brown, Monica Castiglione, Barbara Dunn, John F Forbes, Agnes Glaus, Anthony Howell, Gunter von Minckwitz, Victor Vogel, Heinz Zwierzina. (2011) Preventive therapy for breast cancer: a consensus statement. The Lancet Oncology 12:5, 496-503
CrossRef43
John J. Heine, Ke Cao, Dana E. Rollison. (2011) Calibrated Measures for Breast Density Estimation. Academic Radiology 18:5, 547-555
CrossRef44
T. Cigler, H. Richardson, M. J. Yaffe, C. J. Fabian, D. Johnston, J. N. Ingle, E. Nassif, R. L. Brunner, M. E. Wood, J. L. Pater, H. Hu, S. Qi, D. Tu, P. E. Goss. (2011) A randomized, placebo-controlled trial (NCIC CTG MAP.2) examining the effects of exemestane on mammographic breast density, bone density, markers of bone metabolism and serum lipid levels in postmenopausal women. Breast Cancer Research and Treatment 126:2, 453-461
CrossRef45
Stephanie M. W. Y. Ven, Niculae Mincu, Jean Brunette, Guobin Ma, Mario Khayat, Debra M. Ikeda, Sanjiv S. Gambhir. (2011) Molecular Imaging Using Light-Absorbing Imaging Agents and a Clinical Optical Breast Imaging System—a Phantom Study. Molecular Imaging and Biology 13:2, 232-238
CrossRef46
Gertraud Maskarinec, Yukiko Morimoto, Yihe Daida, Aurelie Laidevant, Serghei Malkov, John A. Shepherd, Rachel Novotny. (2011) Comparison of breast density measured by dual energy X-ray absorptiometry with mammographic density among adult women in Hawaii. Cancer Epidemiology 35:2, 188-193
CrossRef47
G van Schoor, S M Moss, J D M Otten, R Donders, E Paap, G J den Heeten, R Holland, M J M Broeders, A L M Verbeek. (2011) Increasingly strong reduction in breast cancer mortality due to screening. British Journal of Cancer 104:6, 910-914
CrossRef48
Mina J Bissell, William C Hines. (2011) Why don't we get more cancer? A proposed role of the microenvironment in restraining cancer progression. Nature Medicine 17:3, 320-329
CrossRef49
C S Wong, G H Lim, F Gao, R W Jakes, J Offman, K S Chia, S W Duffy. (2011) Mammographic density and its interaction with other breast cancer risk factors in an Asian population. British Journal of Cancer 104:5, 871-874
CrossRef50
Stephen Feig. (2011) Comparison of Costs and Benefits of Breast Cancer Screening with Mammography, Ultrasonography, and MRI. Obstetrics and Gynecology Clinics of North America 38:1, 179-196
CrossRef51
Brian L. Sprague, Amy Trentham-Dietz, Ronald E. Gangnon, Diana S. M. Buist, Elizabeth S. Burnside, Erin J. Aiello Bowles, Frank Z. Stanczyk, Gale S. Sisney. (2011) Circulating Sex Hormones and Mammographic Breast Density among Postmenopausal Women. Hormones and Cancer 2:1, 62-72
CrossRef52
N. F. Boyd, L. J. Martin, M. J. Yaffe, M. Bronskill, N. Duric, S. Minkin. (2011) Response: Re: Breast Tissue Composition and Susceptibility to Breast Cancer. JNCI Journal of the National Cancer Institute 103:1, 77-78
CrossRef53
Xinming Liu, Chao-Jen Lai, Gary J. Whitman, William R. Geiser, Youtao Shen, Ying Yi, Chris C. Shaw. (2011) Effects of exposure equalization on image signal-to-noise ratios in digital mammography: A simulation study with an anthropomorphic breast phantom. Medical Physics 38:12, 6489
CrossRef54
Spyros S Skandalis, Vassiliki T Labropoulou, Panagiota Ravazoula, Eleni Likaki-Karatza, Katalin Dobra, Haralabos P Kalofonos, Nikos K Karamanos, Achilleas D Theocharis. (2011) Versican but not decorin accumulation is related to malignancy in mammographically detected high density and malignant-appearing microcalcifications in non-palpable breast carcinomas. BMC Cancer 11:1, 314
CrossRef55
D Tzias, S George, L Wilkinson, R Mehta, C Lobo, A Hainsworth, A Sharma. (2011) Correlation of ethnicity with breast density as assessed by Quantra™. Breast Cancer Research 13:Suppl 1, O5
CrossRef56
Jei-Hun Jeon, Jung-Hyun Kang, Yeonju Kim, Hoo-Yeon Lee, Kui Son Choi, Jae Kwan Jun, Dong-Kwan Oh, Chang Yoon Lee, Kyungran Ko, Eun-Cheol Park. (2011) Reproductive and Hormonal Factors Associated with Fatty or Dense Breast Patterns among Korean Women. Cancer Research and Treatment 43:1, 42
CrossRef57
Justin L. Ducote, Michael J. Klopfer, S. Molloi. (2011) Volumetric lean percentage measurement using dual energy mammography. Medical Physics 38:8, 4498
CrossRef58
Christine Lasset, Valérie Bonadona. 2011. Épidémiologie du cancer du sein. , 21-28.
CrossRef59
Charlotte Robert, Guillaume Montémont, Véronique Rebuffel, Loïck Verger, Irène Buvat. (2011) Optimization of a parallel hole collimator/CdZnTe gamma-camera architecture for scintimammography. Medical Physics 38:4, 1806
CrossRef60
Jeon-Hor Chen, Yeun-Chung Chang, Daniel Chang, Yi-Ting Wang, Ke Nie, Ruey-Feng Chang, Orhan Nalcioglu, Chiun-Sheng Huang, Min-Ying Su. (2011) Reduction of breast density following tamoxifen treatment evaluated by 3-D MRI: preliminary study. Magnetic Resonance Imaging 29:1, 91-98
CrossRef61
Daniel H.-E. Chang, Jeon-Hor Chen, Muqing Lin, Shadfar Bahri, Hon J. Yu, Rita S. Mehta, Ke Nie, David J. B. Hsiang, Orhan Nalcioglu, Min-Ying Su. (2011) Comparison of breast density measured on MR images acquired using fat-suppressed versus nonfat-suppressed sequences. Medical Physics 38:11, 5961
CrossRef62
R. James Brenner. (2011) Breast Density and Risk of Breast Cancer: New Clothes for the Emperor. Breast Diseases: A Year Book Quarterly 22:4, 349-352
CrossRef63
Woo Kyung Moon, Yi-Wei Shen, Chiun-Sheng Huang, Sheng-Chy Luo, Aida Kuzucan, Jeon-Hor Chen, Ruey-Feng Chang. (2011) Comparative study of density analysis using automated whole breast ultrasound and MRI. Medical Physics 38:1, 382
CrossRef64
Guido van Schoor, Sue M. Moss, Johannes D.M. Otten, Rogier Donders, Ellen Paap, Gerard J. den Heeten, Roland Holland, Mireille J.M. Broeders, André L.M. Verbeek. (2010) Effective biennial mammographic screening in women aged 40–49. European Journal of Cancer 46:18, 3137-3140
CrossRef65
Danielle J. Haakinson, Chee-Chee H. Stucky, Amylou C. Dueck, Richard J. Gray, Nabil Wasif, Heidi A. Apsey, Barbara Pockaj. (2010) A significant number of women present with palpable breast cancer even with a normal mammogram within 1 year. The American Journal of Surgery 200:6, 712-718
CrossRef66
Christian R. Loehberg, Katharina Heusinger, Sebastian M. Jud, Lothar Haeberle, Alexander Hein, Claudia Rauh, Mayada R. Bani, Michael P. Lux, Michael G. Schrauder, Christian M. Bayer, Cosima Helbig, Ronald Grolik, Boris Adamietz, Ruediger Schulz-Wendtland, Matthias W. Beckmann, Peter A. Fasching. (2010) Assessment of mammographic density before and after first full-term pregnancy. European Journal of Cancer Prevention 19:6, 405-412
CrossRef67
Kevin M. Kelly, Judy Dean, Sung-Jae Lee, W. Scott Comulada. (2010) Breast cancer detection: radiologists’ performance using mammography with and without automated whole-breast ultrasound. European Radiology 20:11, 2557-2564
CrossRef68
Xingwei Wang, Dror Lederman, Jun Tan, Xiao Hui Wang, Bin Zheng. (2010) Computerized Detection of Breast Tissue Asymmetry Depicted on Bilateral Mammograms. Academic Radiology 17:10, 1234-1241
CrossRef69
Arturo Prado, Patricio Andrades, Francisco Parada. (2010) Recent developments in the ability to predict and modify breast cancer risk. Journal of Plastic, Reconstructive & Aesthetic Surgery 63:10, 1581-1587
CrossRef70
Edward A. Sickles. (2010) The Use of Breast Imaging to Screen Women at High Risk for Cancer. Radiologic Clinics of North America 48:5, 859-878
CrossRef71
Stephen Feig. (2010) Cost-Effectiveness of Mammography, MRI, and Ultrasonography for Breast Cancer Screening. Radiologic Clinics of North America 48:5, 879-891
CrossRef72
N. F. Boyd, L. J. Martin, M. Bronskill, M. J. Yaffe, N. Duric, S. Minkin. (2010) Breast Tissue Composition and Susceptibility to Breast Cancer. JNCI Journal of the National Cancer Institute 102:16, 1224-1237
CrossRef73
Erin J. Aiello Bowles, Melissa L. Anderson, Susan D. Reed, Katherine M. Newton, E. Dawn Fitzgibbons, Deborah Seger, Diana S.M. Buist. (2010) Mammographic Breast Density and Tolerance for Short-Term Postmenopausal Hormone Therapy Suspension. Journal of Women's Health 19:8, 1467-1474
CrossRef74
Gretchen L. Gierach, Jennifer T. Loud, Catherine K. Chow, Sheila A. Prindiville, Jennifer Eng-Wong, Peter W. Soballe, Claudia Giambartolomei, Phuong L. Mai, Claudia E. Galbo, Kathryn Nichols, Kathleen A. Calzone, Celine Vachon, Mitchell H. Gail, Mark H. Greene. (2010) Mammographic density does not differ between unaffected BRCA1/2 mutation carriers and women at low-to-average risk of breast cancer. Breast Cancer Research and Treatment 123:1, 245-255
CrossRef75
Tzu-Ching Shih, Jeon-Hor Chen, Dongxu Liu, Ke Nie, Lizhi Sun, Muqing Lin, Daniel Chang, Orhan Nalcioglu, Min-Ying Su. (2010) Computational simulation of breast compression based on segmented breast and fibroglandular tissues on magnetic resonance images. Physics in Medicine and Biology 55:14, 4153-4168
CrossRef76
O Alonzo-Proulx, N Packard, J M Boone, A Al-Mayah, K K Brock, S Z Shen, M J Yaffe. (2010) Validation of a method for measuring the volumetric breast density from digital mammograms. Physics in Medicine and Biology 55:11, 3027-3044
CrossRef77
Luis G Carvajal-Carmona. (2010) Genetic dissection of intermediate phenotypes as a way to discover novel cancer susceptibility alleles. Current Opinion in Genetics & Development 20:3, 308-314
CrossRef78
E. Amir, O. C. Freedman, B. Seruga, D. G. Evans. (2010) Assessing Women at High Risk of Breast Cancer: A Review of Risk Assessment Models. JNCI Journal of the National Cancer Institute 102:10, 680-691
CrossRef79
Fritz K. W. Schaefer, A. Waldmann, A. Katalinic, C. Wefelnberg, M. Heller, W. Jonat, I. Schreer. (2010) Influence of additional breast ultrasound on cancer detection in a cohort study for quality assurance in breast diagnosis—analysis of 102,577 diagnostic procedures. European Radiology 20:5, 1085-1092
CrossRef80
Christian R. Loehberg, Sebastian M. Jud, Lothar Haeberle, Katharina Heusinger, Gerhard Dilbat, Alexander Hein, Claudia Rauh, Peter Dall, Nadine Rix, Sabrina Heinrich, Stefan Buchholz, Benno Lex, Barbara Reichler, Boris Adamietz, Ruediger Schulz-Wendtland, Matthias W. Beckmann, Peter A. Fasching. (2010) Breast cancer risk assessment in a mammography screening program and participation in the IBIS-II chemoprevention trial. Breast Cancer Research and Treatment 121:1, 101-110
CrossRef81
Icro Meattini, Lorenzo Livi, Calogero Saieva, Livia Marrazzo, Andrea Rampini, Carmine Iermano, Maria Grazia Papi, Beatrice Detti, Silvia Scoccianti, Giampaolo Biti. (2010) Breast Cancer Following Hodgkin’s Disease: The Experience of the University of Florence. The Breast Journal 16:3, 290-296
CrossRef82
Marina E. Giurescu, Tilina Hu, Olufolajimi Obembe. (2010) Role of Imaging in Breast Cancer Detection. AAOHN Journal 58:4, 131-134
CrossRef83
A. D. A. Maidment. (2010) The future of medical imaging. Radiation Protection Dosimetry 139:1-3, 3-7
CrossRef84
T. Cigler, D. Tu, M. J. Yaffe, B. Findlay, S. Verma, D. Johnston, H. Richardson, H. Hu, S. Qi, P. E. Goss. (2010) A randomized, placebo-controlled trial (NCIC CTG MAP1) examining the effects of letrozole on mammographic breast density and other end organs in postmenopausal women. Breast Cancer Research and Treatment 120:2, 427-435
CrossRef85
H. Madjar. (2010) Mammasonographie. Der Gynäkologe 43:3, 241-249
CrossRef86
Kevin M. Kelly, Judy Dean, W. Scott Comulada, Sung-Jae Lee. (2010) Breast cancer detection using automated whole breast ultrasound and mammography in radiographically dense breasts. European Radiology 20:3, 734-742
CrossRef87
C. Colin, V. Prince, P.J. Valette. (2010) Can mammographic assessments lead to consider density as a risk factor for breast cancer?. European Journal of Radiology
CrossRef88
Lisa M. Arendt, Jenny A. Rudnick, Patricia J. Keller, Charlotte Kuperwasser. (2010) Stroma in breast development and disease. Seminars in Cell & Developmental Biology 21:1, 11-18
CrossRef89
Justin L. Ducote, Sabee Molloi. (2010) Quantification of breast density with dual energy mammography: An experimental feasibility study. Medical Physics 37:2, 793
CrossRef90
Jacob D. Shea, Panagiotis Kosmas, Susan C. Hagness, Barry D. Van Veen. (2010) Three-dimensional microwave imaging of realistic numerical breast phantoms via a multiple-frequency inverse scattering technique. Medical Physics 37:8, 4210
CrossRef91
Carol H. Lee, D. David Dershaw, Daniel Kopans, Phil Evans, Barbara Monsees, Debra Monticciolo, R. James Brenner, Lawrence Bassett, Wendie Berg, Stephen Feig, Edward Hendrick, Ellen Mendelson, Carl D'Orsi, Edward Sickles, Linda Warren Burhenne. (2010) Breast Cancer Screening With Imaging: Recommendations From the Society of Breast Imaging and the ACR on the Use of Mammography, Breast MRI, Breast Ultrasound, and Other Technologies for the Detection of Clinically Occult Breast Cancer. Journal of the American College of Radiology 7:1, 18-27
CrossRef92
Nikolce Gjorevski, Celeste M. Nelson. (2010) Endogenous patterns of mechanical stress are required for branching morphogenesis. Integrative Biology 2:9, 424
CrossRef93
Ke Nie, Daniel Chang, Jeon-Hor Chen, Tzu-Ching Shih, Chieh-Chih Hsu, Orhan Nalcioglu, Min-Ying Su. (2010) Impact of skin removal on quantitative measurement of breast density using MRI. Medical Physics 37:1, 227
CrossRef94
Wei Tse Yang, Michael T. Lewis, Kenneth Hess, Helen Wong, Anna Tsimelzon, Nese Karadag, Michelina Cairo, Caimaio Wei, Funda Meric-Bernstam, Powel Brown, Banu Arun, Gabriel N. Hortobagyi, Aysegul Sahin, Jenny C. Chang. (2010) Decreased TGFβ signaling and increased COX2 expression in high risk women with increased mammographic breast density. Breast Cancer Research and Treatment 119:2, 305-314
CrossRef95
Tulin Cil, Eve Fishell, Wedad Hanna, Ping Sun, Ellen Rawlinson, Steven A. Narod, David R. McCready. (2009) Mammographic density and the risk of breast cancer recurrence after breast-conserving surgery. Cancer 115:24, 5780-5787
CrossRef96
Hans Junkermann. (2009) Mammadiagnostik zur Brustkrebsfrüherkennung. Onkopipeline 2:4, 146-152
CrossRef97
Leny Pearman, Risa Kagan, Jody Arsenault, David Muram. (2009) The effects of raloxifene on mammographic breast density. Menopause1
CrossRef98
Raja A. Sayegh, Priscilla J. Slanetz. (2009) Breast density, hormones, and screening mammography. Menopause 16:6, 1085-1086
CrossRef99
P.E. Lønning, H. Helle, N.K. Duong, D. Ekse, T. Aas, J. Geisler. (2009) Tissue estradiol is selectively elevated in receptor positive breast cancers while tumour estrone is reduced independent of receptor status. The Journal of Steroid Biochemistry and Molecular Biology 117:1-3, 31-41
CrossRef100
Lisa J. Martin, Salomon Minkin, Norman F. Boyd. (2009) Hormone therapy, mammographic density, and breast cancer risk. Maturitas 64:1, 20-26
CrossRef101
Mohamed A. Bedaiwy, Noha A. Mousa, Robert F. Casper. (2009) Aromatase Inhibitors: Potential Reproductive Implications. Journal of Minimally Invasive Gynecology 16:5, 533-539
CrossRef102
Jeffrey A. Tice. (2009) Mammographic density as a marker of breast cancer risk?. Current Breast Cancer Reports 1:3, 175-180
CrossRef103
J.-H. Chen, F.-T. Hsu, H.-N. Shih, C.-C. Hsu, D. Chang, K. Nie, O. Nalcioglu, M.-Y. Su. (2009) Does breast density show difference in patients with estrogen receptor-positive and estrogen receptor-negative breast cancer measured on MRI?. Annals of Oncology 20:8, 1447-1449
CrossRef104
J.-H. Chen, D. Chang, K. Nie, F.-T. Hsu, H.-N. Shih, C.-C. Hsu, O. Nalcioglu, M.-Y. Su. (2009) Comparison of breast density in the contralateral normal breast of patients with invasive and in situ breast cancer measured on MRI. Annals of Oncology 20:8, 1449-1450
CrossRef105
Mads Nielsen, Jakob Raundahl, Paola C. Pettersen, Marco Loog, Gopal Karemore, Morten A. Karsdal, Claus Christiansen. (2009) Low-dose transdermal estradiol induces breast density and heterogeneity changes comparable to those of raloxifene. Menopause 16:4, 785-791
CrossRef106
Norman Boyd, Lisa Martin, Sofia Chavez, Anoma Gunasekara, Ayesha Salleh, Olga Melnichouk, Martin Yaffe, Christine Friedenreich, Salomon Minkin, Michael Bronskill. (2009) Breast-tissue composition and other risk factors for breast cancer in young women: a cross-sectional study. The Lancet Oncology 10:6, 569-580
CrossRef107
Gulisa Turashvili, Steven McKinney, Lisa Martin, Karen A. Gelmon, Peter Watson, Norman Boyd, Samuel Aparicio. (2009) Columnar cell lesions, mammographic density and breast cancer risk. Breast Cancer Research and Treatment 115:3, 561-571
CrossRef108
A H Olsen, K Bihrmann, M-B Jensen, I Vejborg, E J Hoffman. (2009) Breast density and outcome of mammography screening: a cohort study. British Journal of Cancer 100:7, 1205-1208
CrossRef109
S. R. Cummings, J. A. Tice, S. Bauer, W. S. Browner, J. Cuzick, E. Ziv, V. Vogel, J. Shepherd, C. Vachon, R. Smith-Bindman, K. Kerlikowske. (2009) Prevention of Breast Cancer in Postmenopausal Women: Approaches to Estimating and Reducing Risk. JNCI Journal of the National Cancer Institute 101:6, 384-398
CrossRef110
Despina Kontos, Predrag R. Bakic, Ann-Katherine Carton, Andrea B. Troxel, Emily F. Conant, Andrew D.A. Maidment. (2009) Parenchymal Texture Analysis in Digital Breast Tomosynthesis for Breast Cancer Risk Estimation. Academic Radiology 16:3, 283-298
CrossRef111
Stephanie Ven, Sjoerd Elias, Andrea Wiethoff, Marjolein Voort, Anais Leproux, Tim Nielsen, Bernhard Brendel, Leon Bakker, Martin Mark, Willem Mali, Peter Luijten. (2009) Diffuse Optical Tomography of the Breast: Initial Validation in Benign Cysts. Molecular Imaging and Biology 11:2, 64-70
CrossRef112
Alberto Tagliafico, Giulio Tagliafico, Simona Tosto, Fabio Chiesa, Carlo Martinoli, Lorenzo E. Derchi, Massimo Calabrese. (2009) Mammographic density estimation: Comparison among BI-RADS categories, a semi-automated software and a fully automated one. The Breast 18:1, 35-40
CrossRef113
Darci T. Butcher, Tamara Alliston, Valerie M. Weaver. (2009) A tense situation: forcing tumour progression. Nature Reviews Cancer 9:2, 108-122
CrossRef114
J Price, SW Chen. (2009) Screening for breast cancer with MRI: recent experience from the Australian Capital Territory. Journal of Medical Imaging and Radiation Oncology 53:1, 69-80
CrossRef115
Jeon-Hor Chen, Chiun-Sheng Huang, Kuang-Che Chang Chien, Etsuo Takada, Woo Kyung Moon, Jeffery H. K. Wu, Nariya Cho, Yi-Fa Wang, Ruey-Feng Chang. (2009) Breast density analysis for whole breast ultrasound images. Medical Physics 36:11, 4933
CrossRef116
Paul Hansma, Hongmei Yu, David Schultz, Azucena Rodriguez, Eugene A. Yurtsev, Jessica Orr, Simon Tang, Jon Miller, Joseph Wallace, Frank Zok, Cheng Li, Richard Souza, Alexander Proctor, Davis Brimer, Xavier Nogues-Solan, Leonardo Mellbovsky, M. Jesus Peña, Oriol Diez-Ferrer, Phillip Mathews, Connor Randall, Alfred Kuo, Carol Chen, Mathilde Peters, David Kohn, Jenni Buckley, Xiaojuan Li, Lisa Pruitt, Adolfo Diez-Perez, Tamara Alliston, Valerie Weaver, Jeffrey Lotz. (2009) The tissue diagnostic instrument. Review of Scientific Instruments 80:5, 054303
CrossRef117
Lone Rønnov-Jessen, Mina J. Bissell. (2009) Breast cancer by proxy: can the microenvironment be both the cause and consequence?. Trends in Molecular Medicine 15:1, 5-13
CrossRef118
Jennifer C. Carter, Frank C. Church. (2009) Obesity and Breast Cancer: The Roles of Peroxisome Proliferator-Activated Receptor-γ and Plasminogen Activator Inhibitor-1. PPAR Research 2009, 1-13
CrossRef119
Amanda L. Weinmann, Carrie B. Hruska, Michael K. O’Connor. (2009) Design of optimal collimation for dedicated molecular breast imaging systems. Medical Physics 36:3, 845
CrossRef120
S.A. Feig. (2009) Cost Effectiveness of Breast Cancer Screening With Contrast-Enhanced MRI in High-Risk Women. Breast Diseases: A Year Book Quarterly 20:4, 383-385
CrossRef121
Albert H. Tyson, Gordon E. Mawdsley, Martin J. Yaffe. (2009) Measurement of compressed breast thickness by optical stereoscopic photogrammetry. Medical Physics 36:2, 569
CrossRef122
John J. Heine, Ke Cao, Craig Beam. (2009) Cumulative sum quality control for calibrated breast density measurements. Medical Physics 36:12, 5380
CrossRef123
M. J. Yaffe, J. M. Boone, N. Packard, O. Alonzo-Proulx, S.-Y. Huang, C. L. Peressotti, A. Al-Mayah, K. Brock. (2009) The myth of the 50-50 breast. Medical Physics 36:12, 5437
CrossRef124
2009. BIBLIOGRAPHIE. , 176-189.
CrossRef125
Gerco Haars, Carla H. van Gils, Sjoerd G. Elias, Mariëtte Lokate, Paul A.H. van Noord, Petra HM Peeters. (2009) The influence of a period of caloric restriction due to the Dutch famine on breast density. International Journal of CancerNA-NA
CrossRef126
Serghei Malkov, Jeff Wang, Karla Kerlikowske, Steven R. Cummings, John A. Shepherd. (2009) Single x-ray absorptiometry method for the quantitative mammographic measure of fibroglandular tissue volume. Medical Physics 36:12, 5525
CrossRef127
Rulla M. Tamimi, Louise Eriksson, Pagona Lagiou, Kamila Czene, Anders Ekbom, Chung-Cheng Hsieh, Hans-Olov Adami, Dimitrios Trichopoulos, Per Hall. (2009) Birth weight and mammographic density among postmenopausal women in Sweden. International Journal of CancerNA-NA
CrossRef128
M.R. Bani, M.P. Lux, K. Heusinger, E. Wenkel, A. Magener, R. Schulz-Wendtland, M.W. Beckmann, P.A. Fasching. (2009) Factors correlating with reexcision after breast-conserving therapy. European Journal of Surgical Oncology (EJSO) 35:1, 32-37
CrossRef129
Kate Grower-Thomas. 2009. Imaging of the breast. , 71-80.
CrossRef130
O M Ginsburg, L J Martin, N F Boyd. (2008) Mammographic density, lobular involution, and risk of breast cancer. British Journal of Cancer 99:9, 1369-1374
CrossRef131
Frances C. Wright, Cagla Eskicioglu, Joan Glazier, Roberta Jong, Petrina Causer, May Lynn Quan. (2008) Women with Locally Advanced Breast Cancer are Not at Higher Risk for Contralateral Synchronous Breast Cancer. The Breast Journal 14:6, 556-561
CrossRef132
Y. Shen, J. P. Costantino, J. Qin. (2008) Tamoxifen Chemoprevention Treatment and Time to First Diagnosis of Estrogen Receptor-Negative Breast Cancer. JNCI Journal of the National Cancer Institute 100:20, 1448-1453
CrossRef133
Seema A Khan, Robert T Chatterton Jr. (2008) Cellular and hormonal content of breast nipple aspirate fluid in relation to the risk of breast cancer. Biomarkers in Medicine 2:5, 479-493
CrossRef134
Jennifer R. Zebrack, Keith W. Brown. (2008) Preventive Health for Women: Screening and Immunizations. Medical Clinics of North America 92:5, 1011-1035
CrossRef135
Anna M. Kucharska-Newton, Wayne D. Rosamond, Pamela J. Mink, Anthony J. Alberg, Eyal Shahar, Aaron R. Folsom. (2008) HDL-Cholesterol and Incidence of Breast Cancer in the ARIC Cohort Study. Annals of Epidemiology 18:9, 671-677
CrossRef136
Noha A. Mousa, Pavel Crystal, Wendy L. Wolfman, Mohamed A. Bedaiwy, Robert F. Casper. (2008) Aromatase inhibitors and mammographic breast density in postmenopausal women receiving hormone therapy. Menopause 15:5, 875-884
CrossRef137
E. Paap, M.J.M. Broeders, G. van Schoor, J.D.M. Otten, A.L.M. Verbeek. (2008) Large increase in a Dutch woman’s lifetime risk of developing breast cancer. European Journal of Cancer 44:11, 1485-1487
CrossRef138
Victor G. Vogel. (2008) Epidemiology, genetics, and risk evaluation of postmenopausal women at risk of breast cancer. Menopause 15:Supplement, 782-789
CrossRef139
Emily C. Siegal, Elizabeth J. Angelakis, Audrey Hartman. (2008) Can Peer Review Contribute to Earlier Detection of Breast Cancer? A Quality Initiative to Learn from False-Negative Mammograms. The Breast Journal 14:4, 330-334
CrossRef140
Gulisa Turashvili, Malcolm Hayes, Blake Gilks, Peter Watson, Samuel Aparicio. (2008) Are columnar cell lesions the earliest histologically detectable non-obligate precursor of breast cancer?. Virchows Archiv 452:6, 589-598
CrossRef141
Goli Samimi, Graham A. Colditz, Heather J. Baer, Rulla M. Tamimi. (2008) Measures of energy balance and mammographic density in the Nurses’ Health Study. Breast Cancer Research and Treatment 109:1, 113-122
CrossRef142
N. M. Perry, P. C. Allgood, S. W. Duffy, K. Mokbel. (2008) Exposure to traffic emissions throughout life and risk of breast cancer. Cancer Causes & Control 19:4, 435-435
CrossRef143
Dimitrios Trichopoulos, Hans-Olov Adami, Anders Ekbom, Chung-Cheng Hsieh, Pagona Lagiou. (2008) Early life events and conditions and breast cancer risk: From epidemiology to etiology. International Journal of Cancer 122:3, 481-485
CrossRef144
N. M. Perry, P. C. Allgood, S. E. Milner, K. Mokbel, S. W. Duffy. (2008) Mammographic breast density by area of residence: possible evidence of higher density in urban areas. Current Medical Research and Opinion 24:2, 365-368
CrossRef145
Jack Cuzick. (2008) Chemoprevention of breast cancer. Breast Cancer 15:1, 10-16
CrossRef146
Carri K. Glide-Hurst, Neb Duric, Peter Littrup. (2008) Volumetric breast density evaluation from ultrasound tomography images. Medical Physics 35:9, 3988
CrossRef147
Kristina M. Blackmore, Samantha Dick, Julia Knight, Lothar Lilge. (2008) Estimation of mammographic density on an interval scale by transillumination breast spectroscopy. Journal of Biomedical Optics 13:6, 064030
CrossRef148
Justin L. Ducote, Sabee Molloi. (2008) Quantification of breast density with dual energy mammography: A simulation study. Medical Physics 35:12, 5411
CrossRef149
Ke Nie, Jeon-Hor Chen, Siwa Chan, Man-Kwun I. Chau, Hon J. Yu, Shadfar Bahri, Tiffany Tseng, Orhan Nalcioglu, Min-Ying Su. (2008) Development of a quantitative method for analysis of breast density based on three-dimensional breast MRI. Medical Physics 35:12, 5253
CrossRef150
Y Faridah. (2008) Digital versus screen film mammography: a clinical comparison. Biomedical Imaging and Intervention Journal 4:4,
CrossRef151
Yngve Bremnes, Giske Ursin, Nils Bjurstam, Sabina Rinaldi, Rudolf Kaaks, Inger T. Gram. (2007) Endogenous sex hormones, prolactin and mammographic density in postmenopausal Norwegian women. International Journal of Cancer 121:11, 2506-2511
CrossRef152
R. T. Chlebowski, G. L. Anderson, D. S. Lane, A. K. Aragaki, T. Rohan, S. Yasmeen, G. Sarto, C. A. Rosenberg, F. A. Hubbell, . (2007) Predicting Risk of Breast Cancer in Postmenopausal Women by Hormone Receptor Status. JNCI Journal of the National Cancer Institute 99:22, 1695-1705
CrossRef153
Johannes C Huber, Johannes Ott, Clemens B Tempfer. (2007) Preventive oncology in the postmenopausal woman. Women's Health 3:6, 689-697
CrossRef154
Wendie A. Berg. (2007) Beyond Standard Mammographic Screening: Mammography at Age Extremes, Ultrasound, and MR Imaging. Radiologic Clinics of North America 45:5, 895-906
CrossRef155
Catherine Ruhl. (2007) Breast Health Screening: What All Women Should Know. Nursing for Women's Health 11:3, 326-330
CrossRef156
(2007) Mammographic Breast Density. New England Journal of Medicine 356:18, 1885-1887
Full Text157
Andrew Karellas. (2007) Mammographic Pattern Analysis: An Emerging Risk Assessment Tool. Academic Radiology 14:5, 511-512
CrossRef158
Lila E. Nachtigall. (2007) Breast density as a clinical entity. Menopause 14:3, 345-346
CrossRef159
Hall, Ferris M., . (2007) Breast Imaging and Computer-Aided Detection. New England Journal of Medicine 356:14, 1464-1466
Full Text160
Kerlikowske, Karla, . (2007) The Mammogram That Cried Wolfe. New England Journal of Medicine 356:3, 297-300
Full Text161
Sara M. Tolaney, Eric P. Winer. (2007) Follow-up care of patients with breast cancer. The Breast 16, 45-50
CrossRef162
Carri K. Glide-Hurst, Neb Duric, Peter Littrup. (2007) A new method for quantitative analysis of mammographic density. Medical Physics 34:11, 4491
CrossRef
- Letters
