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We evaluated the association between short-term change in body mass index (BMI) and breast density during a 1 year weight-loss intervention (Manchester, UK). We included 65 premenopausal women (35–45 years, ≥7 kg adult weight gain, family history of breast cancer). BMI and breast density (semi-automated area-based, automated volume-based) were measured at baseline, 1 year, and 2 years after study entry (1 year post intervention). Cross-sectional (between-women) and short-term change (within-women) associations between BMI and breast density were measured using repeated-measures correlation coefficients and multivariable linear mixed models. BMI was positively correlated with dense volume between-women (r = 0.41, 95%CI: 0.17, 0.61), but less so within-women (r = 0.08, 95%CI: −0.16, 0.28). There was little association with dense area (between-women r = −0.12, 95%CI: −0.38, 0.16, within-women r = 0.01, 95%CI: −0.24, 0.25). BMI and breast fat were positively correlated (volume: between r = 0.77, 95%CI: 0.69, 0.84, within r = 0.58, 95%CI: 0.36, 0.75, area: between r = 0.74, 95%CI: 0.63, 0.82, within r = 0.45, 95%CI: 0.23, 0.63). Multivariable models reported similar associations. Exploratory analysis suggested associations between BMI gain from 20 years and density measures (standard deviation change per +5 kg/m2 BMI: dense area: +0.61 (95%CI: 0.12, 1.09), fat volume: −0.31 (95%CI: −0.62, 0.00)). Short-term BMI change is likely to be positively associated with breast fat, but we found little association with dense tissue, although power was limited by small sample size.

The importance of care of infants and children in palaeoanthropological and human behavioural ecological research on the evolution of our species is evident in the diversity of research on human development, alloparental care, and learning and social interaction. There has been a recent surge of interest in modelling the social implications of care provision for people with serious disabilities in bioarchaeology. However, there is a lack of acknowledgement of infant and child care in bioarchaeology, despite the significant labour and resources that are required, and the implications this has for health outcomes within societies. Drawing on the recent proliferation of studies on infancy and childhood in evolutionary anthropology and bioarchaeology, this paper presents ways the subdisciplines may draw on research developments from each field to advance a more holistic understanding of the evolutionary, social and health significance of infant and children care in the past.

Purpose Precision oncology develops and implements evidence-based personalized therapies that are based on specific genetic targets within each tumor. However, a major challenge that remains is the provision of a standardized, up-to-date, and evidenced-based precision medicine initiative across a geographic region. Materials and Methods We developed a statewide molecular tumor board that integrates academic and community oncology practices. The Precision Medicine Molecular Tumor Board (PMMTB) has three components: a biweekly Web-based teleconference tumor board meeting provided as a free clinical service, an observational research registry, and a monthly journal club to establish and revise evidence-based guidelines for off-label therapies. The PMMTB allows for flexible and rapid implementation of treatment, uniformity in practice, and the ability to track outcomes. Results We describe the implementation of the PMMTB and its first year of activity. Seventy-seven patient cases were presented, 48 were enrolled in a registry, and 38 had recommendations and clinical follow-up. The 38 subjects had diverse solid tumors (lung, 45%; GI, 21%; breast, 13%; other, 21%). Of these subjects, targeted therapy was recommended for 32 (84%). Clinical trials were identified for 24 subjects (63%), and nontrial targeted medicines for 16 (42%). Nine subjects (28%) received recommended therapy with a response rate of 17% (one of six) and a clinical benefit rate (partial response + stable disease) of 38% (three of eight). Although clinical trials often were identified, patients rarely enrolled. Conclusion The PMMTB provides a model for a regional molecular tumor board with clinical utility. This work highlights the need for outcome registries and improved access to clinical trials to pragmatically implement precision oncology.

Background High mammographic density is associated with both risk of cancers being missed at mammography, and increased risk of developing breast cancer. Stratification of breast cancer prevention and screening requires mammographic density measures predictive of cancer. This study compares five mammographic density measures to determine the association with subsequent diagnosis of breast cancer and the presence of breast cancer at screening. Methods Women participating in the “Predicting Risk Of Cancer At Screening” (PROCAS) study, a study of cancer risk, completed questionnaires to provide personal information to enable computation of the Tyrer-Cuzick risk score. Mammographic density was assessed by visual analogue scale (VAS), thresholding (Cumulus) and fully-automated methods (Densitas, Quantra, Volpara) in contralateral breasts of 366 women with unilateral breast cancer (cases) detected at screening on entry to the study (Cumulus 311/366) and in 338 women with cancer detected subsequently. Three controls per case were matched using age, body mass index category, hormone replacement therapy use and menopausal status. Odds ratios (OR) between the highest and lowest quintile, based on the density distribution in controls, for each density measure were estimated by conditional logistic regression, adjusting for classic risk factors. Results The strongest predictor of screen-detected cancer at study entry was VAS, OR 4.37 (95% CI 2.72–7.03) in the highest vs lowest quintile of percent density after adjustment for classical risk factors. Volpara, Densitas and Cumulus gave ORs for the highest vs lowest quintile of 2.42 (95% CI 1.56–3.78), 2.17 (95% CI 1.41–3.33) and 2.12 (95% CI 1.30–3.45), respectively. Quantra was not significantly associated with breast cancer (OR 1.02, 95% CI 0.67–1.54). Similar results were found for subsequent cancers, with ORs of 4.48 (95% CI 2.79–7.18), 2.87 (95% CI 1.77–4.64) and 2.34 (95% CI 1.50–3.68) in highest vs lowest quintiles of VAS, Volpara and Densitas, respectively. Quantra gave an OR in the highest vs lowest quintile of 1.32 (95% CI 0.85–2.05). Conclusions Visual density assessment demonstrated a strong relationship with cancer, despite known inter-observer variability; however, it is impractical for population-based screening. Percentage density measured by Volpara and Densitas also had a strong association with breast cancer risk, amongst the automated measures evaluated, providing practical automated methods for risk stratification. Electronic supplementary material The online version of this article (10.1186/s13058-018-0932-z) contains supplementary material, which is available to authorized users.

Body: Introduction In the IBIS I Prevention Trial we demonstrated that tamoxifen prevented breast cancer in women with greater than 9 % absolute reduction in visually assessed mammographic density over a 12-18 month period as assessed by an expert radiologist, RW (1). In this study we investigated: whether RW obtained similar results in a different group of women treated with tamoxifen; how other expert mammographic film readers with experience of density assessment (radiologists, advanced practitioner radiographers and a breast physician) estimated mammographic change; how visual change relates to change in automated measures of volumetric density; and whether we can predict change by serum markers or SNPs. Methods 105 women aged 33 to 46 at greater than 1 in 6 lifetime breast cancer risk completed one year’s treatment with tamoxifen. RW assessed mammographic percentage density in increments of 5% for baseline and one year mammograms. Two or three of a pool of eight readers estimated % density using a visual analogue scale (VAS). Percent change was also estimated using a computer-assisted thresholding technique (Cumulus). Change in volume of dense tissue (Quantra™ & Volpara™) was measured. Changes in lipids, IGF1, insulin and relevant SNPs were measured to determine whether they predicted density change. Results. Estimates of change obtained by RW were broadly consistent with those from our previous study, as were those from Cumulus, but could not be replicated using estimates from the pooled results of VAS readers. Tamoxifen was associated with marked reductions of dense volume of the breast (Table 1) However the different methods were at best only moderately correlated with RW (r less than 0.6). Change in serum triglycerides significantly predicted density change as measured by RW but none of the other serum measures or SNPs did. Table 1 Numbers of women and percentage change in density measures after one year of tamoxifen% Density changeRW %changeOther radiologists %changeCumulus %change_____% Dense volume change^Quantra %changeVolpara %change40+001 40+15930+503 30+141020+12013 20+202010+35630 10+17260+498143 0+16190-4188 0-1615Number10510598 9899RW = Ruth Warren. CUMULUS was measured by JS, a trained operator of the software. * Percentage point change eg if density changed from 40% to 30% this was regarded as a 10% change.^ Reduction in dense volume expressed as a percentage of baseline dense volume. We used Quantra version 2.0 and Volpara version 1.4.5 Conclusions Whilst RW remained consistent with previous density estimation it was not possible to use a pool of other expert readers to predict change. Cumulus gave similar results to RW but is difficult to use in practice. There was good agreement between the two objective volumetric measures used (r=0.5) and since these are automated they may be suitable for clinical practice. However their relationship to the long term breast cancer preventative effect of tamoxifen needs to be established. Reference 1 Tamoxifen-induced reduction in mammographic density and breast cancer risk reduction: a nested case-control study. Cuzick J, Warwick J, Pinney E, Duffy JW, Cawthorn S, Howell A, Forbes JF, Warren RM. J Natl Cancer Inst. 2011 May 4; 103 (9): 744-52. Citation Format: Anthony Howell, Sue Astley, Elaine Harkness, Julia Wiseman, Jill Fox, Paula Stavrinos, Mary Wilson, Yit Lim, Valerie Reece, Ursula Beetles, Anil Jain, Jamie Sergeant, Jack Cuzick, Ruth Warren, Gareth Evans. Predicting the effect of tamoxifen on the breast: Change in measures of breast density, serum markers and SNPs [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P5-12-01.

Mammographic density is a strong risk factor for breast cancer, but its potential application in risk management is not clear, partly due to uncertainties about its interaction with other breast cancer risk factors. We aimed to quantify the impact of mammographic density on breast cancer risk in women aged 40-49 at intermediate familial risk of breast cancer (average lifetime risk of 23%), in particular in premenopausal women, and to investigate its relationship with other breast cancer risk factors in this population. We present the results from a case-control study nested with the FH01 cohort study of 6,710 women mostly aged 40-49 at intermediate familial risk of breast cancer. One hundred and three cases of breast cancer were age-matched to one or two controls. Density was measured by semiautomated interactive thresholding. Absolute density, but not percent density, was a significant risk factor for breast cancer in this population after adjusting for area of nondense tissue (OR per 10 cm(2) = 1.07, 95% CI 1.00-1.15, p = 0.04). The effect was stronger in premenopausal women, who made up the majority of the study population. Absolute density remained a significant predictor of breast cancer risk after adjusting for age at menarche, age at first live birth, parity, past or present hormone replacement therapy, and the Tyrer-Cuzick 10-year relative risk estimate of breast cancer. Absolute density can improve breast cancer risk stratification and delineation of high-risk groups alongside the Tyrer-Cuzick 10-year relative risk estimate.

Background Observational studies indicate that weight gain or loss alters breast cancer risk. Hormonal prevention with tamoxifen or ovarian suppression reduces mammographic breast density, but has no impact on breast adipose tissue.1 The aim of this study was to assess whether change in weight is associated with change in breast density, breast fat or both. Methods 74 premenopausal women aged between 35 and 45 years, with a family history of breast cancer, were recruited from our Family History Clinic. 36 were allocated to a 25% calorie-restricted Mediterranean diet and exercise intervention; a further 38 women were separately recruited into a control group and given written diet and exercise advice only. At baseline and 12 months breast dense and non-dense (largely adipose) components of the breast were measured: area using Cumulus2 and volume using the Manchester ‘stepwedge’ method.3 Visual assessment of percentage density was reported to the nearest 5%.4 We used correlations to relate percentage change in absolute dense and non-dense (area and volume) to percentage change in: weight, total body fat (DXA), intra-abdominal and subcutaneous abdominal fat (MRI), as well as serum total IGF-I. Results At 12 months, 40 (54%) women lost >1.5% body weight, 14 (19%) gained >1.5% and 21 (28%) remained weight stable, Conclusions These data indicate that dense area and volume remain stable irrespective of change in weight. Non-dense area changes significantly in response to weight change in parallel with total and abdominal fat stores. These observations were performed on relatively small numbers of women and require confirmation in larger series. 1. Cuzick et al J Natl Cancer Inst. 103(9): 744–52, 2011. 2. Boyd NF et al J Natl Cancer Inst. 87(9) 670–675 1995. 3. Diffy et al IWIDM 2006, LNCS 4046 p1-9. In Astley et al (Eds) Springer-Verlag Berlin Heidelberg 2006 4. Brisson J et al. Cancer Epidemiol Biomarkers Prev 2003;12:7288–32. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P4-13-09.

Background: Mammographic breast density and endogenous sex-hormone levels are both strong risk factors for breast cancer. This study investigated whether there is evidence for a shared genetic basis between these risk factors. Methods: Using data on 1,286 women from 617 families, we estimated the heritabilities of serum estradiol, testosterone, and sex-hormone binding globulin (SHBG) levels and of three measures of breast density (dense area, nondense area, and percentage density). We tested for associations between hormone levels and density measures and estimated the genetic and environmental correlations between pairs of traits using variance and covariance components models and pedigree-based maximum likelihood methods. Results: We found no significant associations between estradiol, testosterone, or SHBG levels and any of the three density measures, after adjusting for body mass index (BMI). The estimated heritabilities were 63%, 66%, and 65% for square root–transformed adjusted percentage density, dense area, and nondense area, respectively, and 40%, 25%, and 58% for log-transformed–adjusted estradiol, testosterone, and SHBG. We found no evidence of a shared genetic basis between any hormone levels and any measure of density, after adjusting for BMI. The negative genetic correlation between dense and nondense areas remained significant even after adjustment for BMI and other covariates (ρ = −0.34; SE = 0.08; P = 0.0005). Conclusions: Breast density and sex hormones can be considered as independent sets of traits. Impact: Breast density and sex hormones can be used as intermediate phenotypes in the search for breast cancer susceptibility loci. Cancer Epidemiol Biomarkers Prev; 21(12); 2167–75. ©2012 AACR.

Breast density is a well-known breast cancer risk factor. Most current methods of measuring breast density are area based and subjective. Standard mammogram form (SMF) is a computer program using a volumetric approach to estimate the percent density in the breast. The aim of this study is to evaluate the current implementation of SMF as a predictor of breast cancer risk by comparing it with other widely used density measurement methods. The case-control study comprised 634 cancers with 1,880 age-matched controls combined from the Cambridge and Norwich Breast Screening Programs. Data collection involved assessing the films based both on Wolfe's parenchymal patterns and on visual estimation of percent density and then digitizing the films for computer analysis (interactive threshold technique and SMF). Logistic regression was used to produce odds ratios associated with increasing categories of breast density. Density measures from all four methods were strongly associated with breast cancer risk in the overall population. The stepwise rises in risk associated with increasing density as measured by the threshold method were 1.37 [95% confidence interval (95% CI), 1.03-1.82], 1.80 (95% CI, 1.36-2.37), and 2.45 (95% CI, 1.86-3.23). For each increasing quartile of SMF density measures, the risks were 1.11 (95% CI, 0.85-1.46), 1.31 (95% CI, 1.00-1.71), and 1.92 (95% CI, 1.47-2.51). After the model was adjusted for SMF results, the threshold readings maintained the same strong stepwise increase in density-risk relationship. On the contrary, once the model was adjusted for threshold readings, SMF outcome was no longer related to cancer risk. The available implementation of SMF is not a better cancer risk predictor compared with the thresholding method. (Cancer Epidemiol Biomarkers Prev 2008;17(5):1074–81)

Introduction. Currently, there is a lack of data on the role of combined positron emission tomography–computed tomography (PET–CT) in the staging of early invasive primary breast cancer. We therefore evaluated the role of 18F-fluorodeoxyglucose (18F-FDG)-PET–CT in this patient population. Methods. We prospectively recruited 70 consecutive patients (69 women, one man; mean age, 61.9 ± 8.1 years) with early primary breast cancer for staging with 18F-FDG-PET–CT. All PET–CT images were interpreted by two readers (independently of each other). A third reader adjudicated any discrepancies. All readers had ≥5 years of specific experience. Ethics board approval and informed consent were obtained. Results. The mean clinical follow-up was 22.7 ± 12.6 months. The primary tumor was identified with PET–CT in 64 of 70 patients. Of the unidentified lesions, surgical pathology revealed two intraductal carcinomas, one invasive tubular carcinoma, and three invasive lobular carcinomas. Undiagnosed multifocal breast disease was shown in seven of 70 patients. PET–CT identified avid axillary lymph nodes in 19 of 70 patients, compared with 24 of 70 confirmed during surgery. There were four patients who were axillary node positive on PET but had no axillary disease at surgery. Five patients were reported with avid metastases. Two of those patients were treated for metastatic disease (nodal, lung, and liver in one and bone metastases in the other) following further imaging and clinical assessment. In the other three patients, lesions (lung, n = 1; pleural, n = 1; paratrachael node, n = 1) were subsequently diagnosed as benign lesions. Conclusion. Integrated 18F-FDG-PET–CT may have a role in staging patients presenting with early breast cancer.

Percent mammographic breast density (PMD) is a strong heritable risk factor for breast cancer. However, the pathways through which this risk is mediated are still unclear. To explore whether PMD and breast cancer have a shared genetic basis, we identified genetic variants most strongly associated with PMD in a published meta-analysis of five genome-wide association studies (GWAS) and used these to construct risk scores for 3,628 breast cancer cases and 5,190 controls from the UK2 GWAS of breast cancer. The signed per-allele effect estimates of single-nucleotide polymorphisms (SNP) were multiplied with the respective allele counts in the individual and summed over all SNPs to derive the risk score for an individual. These scores were included as the exposure variable in a logistic regression model with breast cancer case–control status as the outcome. This analysis was repeated using 10 different cutoff points for the most significant density SNPs (1%–10% representing 5,222–50,899 SNPs). Permutation analysis was also conducted across all 10 cutoff points. The association between risk score and breast cancer was significant for all cutoff points from 3% to 10% of top density SNPs, being most significant for the 6% (2-sided P = 0.002) to 10% (P = 0.001) cutoff points (overall permutation P = 0.003). Women in the top 10% of the risk score distribution had a 31% increased risk of breast cancer [OR = 1.31; 95% confidence interval (CI), 1.08–1.59] compared with women in the bottom 10%. Together, our results show that PMD and breast cancer have a shared genetic basis that is mediated through a large number of common variants. Cancer Res; 72(6); 1478–84. ©2012 AACR.

Mammographic breast density is a strong risk factor for breast cancer. Tamoxifen, which reduces the risk of breast cancer in women at high risk, also reduces mammographic breast density. However, it is not known if tamoxifen-induced reductions in breast density can be used to identify women who will benefit the most from prophylactic treatment with this drug.We conducted a nested case-control study within the first International Breast Cancer Intervention Study, a randomized prevention trial of tamoxifen vs placebo. Mammographic breast density was assessed visually and expressed as a percentage of the total breast area in 5% increments. Case subjects were 123 women diagnosed with breast cancer at or after their first follow-up mammogram, which took place 12-18 months after trial entry, and control subjects were 942 women without breast cancer. Multivariable logistic regression was used to adjust for other risk factors. All statistical tests were two-sided.In the tamoxifen arm, 46% of women had a 10% or greater reduction in breast density at their 12- to 18-month mammogram. Compared with all women in the placebo group, women in the tamoxifen group who experienced a 10% or greater reduction in breast density had 63% reduction in breast cancer risk (odds ratio = 0.37, 95% confidence interval = 0.20 to 0.69, P = .002), whereas those who took tamoxifen but experienced less than a 10% reduction in breast density had no risk reduction (odds ratio = 1.13, 95% confidence interval = 0.72 to 1.77, P = .60). In the placebo arm, there was no statistically significant difference in breast cancer risk between subjects who experienced less than a 10% reduction in mammographic density and subjects who experienced a greater reduction.The 12- to 18-month change in mammographic breast density is an excellent predictor of response to tamoxifen in the preventive setting.

Mammographic density is a strong risk factor for breast cancer. Which and how many x-rays are used for research, and how mammographic density is measured varies across studies. In this article, we compared three different measurements (absolute dense area, percent dense area and percent dense volume) from each of four mammograms [left, right, medio-lateral oblique (MLO) and cranio-caudal (CC) views] using three different methods of measurement [computer-assisted thresholding, visual assessment and standard mammogram form (SMF)] to investigate whether additional measurements and/or different methods of measurement provide more information in the prediction of breast cancer risk. Mammographic density was measured in all four mammograms from 318 cases and 899 age-matched controls combined from the Cambridge and Norwich Breast Screening Programmes. Measurements were averaged across various combinations of mammogram type and/or view. Conditional logistic regression was used to estimate odds ratios associated with increasing quintiles of each mammographic measure. Overall, there appeared to be no difference in the fit of the models using two or four mammograms compared to the models using just the contralateral MLO or CC mammogram (all P > 0.07) for all methods of measurement. Common practice of measuring just the contralateral MLO or CC mammogram for analysis in case-control studies investigating the association between mammographic density and breast cancer risk appears to be sufficient.

n Abstract: The aim of this study was to examine the relationship between mammographic density and histological characteristics of breast tumors within a case–control study population. This study was an expansion of a large size case– control study examining the relationship between breast density and breast cancer risk. Percent and area of breast density was assessed in 370 invasive breast cancer cases and 1904 age-matched controls, using a computer-assisted method. Associations between breast density and estrogen receptor (ER) status, histological grade, histological size, lymph node status, vascular invasion, disease extent, and Nottingham Prognostic Index were evaluated, using logistic regression. Women with 50% or greater mammographic density have a 2.63-fold risk (95% confidence interval [95% CI] = 1.78–3.87; p < 0.001) of developing breast cancer compared to women with less than 10% density. Increase in every category of percentage of breast density is also associated with a 1.45-fold risk in developing ER positive tumors relative to ER negative tumors (odds ratio [OR] = 1.02; 95% CI = 1.00–1.04; p = 0.048), and increase in every quartile of absolute area of density is associated with a 1.48-fold ER positive breast cancer risk [95% CI = 1.06–2.07; p = 0.020]. Furthermore, breast density was found to be associated with specifically ER positivity, invasion as well as invasion with in situ, histological grades 1 and 2, tumor size larger than 1.1 cm, lack of vascular invasion, lymph node positivity and negativity, and NPI less than 4.0. After stratifying the data according to mode of diagnosis, the relationship became slightly stronger in the interval cancer group. Similar results were in observed using percent density and absolute density readings. Mammographic density was a stronger risk factor for ER positive [OR = 2.94; 95% CI = 1.94–4.43; p < 0.001] than ER negative cancers when comparing breasts with greater than 50% dense region to those with less than 10% density. No other tumor characteristic had a significant correlation with breast density. These results suggest that mammographic percent density may be more strongly related to ER positive than ER negative breast cancer, but otherwise is a risk factor for breast cancer independent of other tumor characteristics. n

Introduction: A UK multicenter study compared the performance of contrast enhanced-magnetic resonance imaging with X-Ray Mammography in women at high-risk of breast cancer commencing in 1997. Selection criteria were used to identify women with at least 0.9% annual risk of breast cancer. Methods: Women at high breast cancer risk, with a strong family history and/or high probability of a BRCA1/BRCA2/TP53 mutation, were recruited from 22 centers. Those not known as gene carriers were asked to give a blood sample, which was tested anonymously for mutations. Women ages 35 to 49 years were offered annual screening for 2 to 7 years. Study eligibility at entry was assessed retrospectively by detailed examination of pedigrees and overall eligibility accounting for computer risk assessment and mutation results. Results: Seventy-eight of 837 (9%) women entered for screening were ineligible using the strict entry criteria. Thirty-nine cancers were detected in 1,869 women-years in study (incidence 21 per 1,000). Including 3,561 further years follow-up, 28 more breast cancers were identified (12 of 1,000). Incidence rates for 759 eligible women were 22 of 1,000 in study and 13 of 1,000 in total follow-up, compared with 9 of 1,000 and 4 of 1,000, respectively, in 78 ineligible women. Breast cancer rates were higher for BRCA2 than BRCA1 after testing anonymized samples in this selected population at 65 of 1,000 in study and 36 of 1,000 in total follow-up for BRCA2 compared with 44 of 1,000 and 27 of 1,000 for BRCA1. Conclusions: Strict enforcement of study criteria would have minimally improved the power of the study, whereas testing for BRCA1/2 in advance would have substantially increased the detection rates. (Cancer Epidemiol Biomarkers Prev 2009;18(7):2123–31)

Background: Mammographic breast density (MBD) has a strong genetic component. Investigating the genetic models for mammographic density may provide further insights into the genetic factors affecting breast cancer risk. Purpose: To evaluate the familial aggregation of MBD and investigate the genetic models of susceptibility. Methods: We used data on 746 women from 305 families participating in the Sisters in Breast Screening study. Retrieved mammograms were digitized, and percent mammographic density was determined using the Cumulus software. Linear regression analysis was done to identify the factors that are associated with mammographic density and a multivariate regression model was constructed. Familial correlations between relative pairs were calculated using the residuals from these models. Genetic models of susceptibility were investigated using segregation analysis. Results: After adjusting for covariates, the intraclass correlation coefficient among the residuals was 0.26 (95% confidence interval, 0.16-0.36) in sister-sister pairs and 0.67 (0.27-1.00) among the monozygotic twin pairs. The most parsimonious model was a Mendelian single major gene model in which an allele with population frequency 0.39 (95% confidence interval, 0.33-0.46) influenced mammographic density in an additive fashion. This model explained 66% of the residual variance. Conclusion: These results confirm that MBD has a strong heritable basis, and suggest that major genes may explain some of the familial aggregation. These results may have implications for the search of genes that control mammographic density. (Cancer Epidemiol Biomarkers Prev 2009;18(4):1277–84)

In a systematic review of breast MRI for assessing ipsilateral breast cancer to detect additional lesions, technical details were extracted from publications to assess their effect on diagnostic performance. Where technical parameters were complete, we examined their effect on summary ROC models, and the TP:FP ratio and PPV, using random-effects logistic regression. A total of 2,801 breasts in 19 publications underwent statistical analysis for year of study, slice thickness, and repetitions after contrast-medium injection. None were associated with TP/FP ratio. Summary ROC analysis provided weak evidence (P = 0.09) of an association between diagnostic performance and time period, however no trend over time. Tesla strength was reported in 2,801 cases. Other key information was omitted including whether both breasts were examined for 1683 (60%), position of the patient in 1,375 (49%), and imaging planes used in 688 (25%). Contrast agent and dose were reported for 2,646 (95%) breasts. Reporting technique was inconsistently reported. Single radiology reports were found in 1,637 (58%) cases, double in 347 (12.4%), and in 960 (34%) knowledge of mammography or ultrasound findings was not stated. Slice thickness, number of sequences after contrast medium, and year of study did not show significant performance differences. Other technical information was deficient. There is an urgent need to improve the quality of reporting of breast MRI studies.

Overexpression of the endothelin A (ET(A)) receptor has been found in a number of human cancer cell lines. Activation of the ET(A) receptor by endothelin-1 (ET-1) promotes cell proliferation and survival in these tumors, whereas activation of the endothelin B (ET(B)) receptor results in an opposing effect. Therefore, blockade of ET(A) may have antitumor effects, while sparing ET(B)-mediated effects such as induction of apoptosis and clearance of ET-1.ZD4054 is an orally bioavailable, specific ET(A) antagonist currently being investigated in prostate cancer. In receptor-binding studies, ZD4054 only bound to ET(A), with no binding detected towards ET(B). Prostate cancer cell lines are known to produce ET-1 and there is a relative increase in expression of ET(A) to ET(B) in these cancers. There is also an association of greater ET(A) expression in higher grade versus lower grade tumors, suggesting that ET(A) may be involved in the malignant transformation process. As ET-1 may also mediate nociceptive effects and osteoblastic effects, there is much interest in clinically assessing ZD4054 in prostate cancer.The data describing the endothelin axis, the role of ET(A) and ET(B) in malignancy, and the effects of ET(A) antagonist ZD4054 in prostate cancer, as demonstrated in preclinical and clinical studies, are reviewed.Further investigation of ZD4054 in prostate cancer is warranted, and Phase III trials are already planned in patients with non-metastatic castrate-resistant prostate cancer (CRPC) with rising prostate specific antigen values, metastatic (asymptomatic) CRPC, and in metastatic CRPC in combination with docetaxel, assessing either differences in progression-free survival and overall survival or overall survival alone.

Purpose We review the evidence on magnetic resonance imaging (MRI) in staging the affected breast to determine its accuracy and impact on treatment. Methods Systematic review and meta-analysis of the accuracy of MRI in detection of multifocal (MF) and/or multicentric (MC) cancer not identified on conventional imaging. We estimated summary receiver operating characteristic curves, positive predictive value (PPV), true-positive (TP) to false positive (FP) ratio, and examined their variability according to quality criteria. Pooled estimates of the proportion of women whose surgery was altered were calculated. Results Data from 19 studies showed MRI detects additional disease in 16% of women with breast cancer (N = 2,610). MRI incremental accuracy differed according to the reference standard (RS; P = .016) decreasing from 99% to 86% as the quality of the RS increased. Summary PPV was 66% (95% CI, 52% to 77%) and TP:FP ratio was 1.91 (95% CI, 1.09 to 3.34). Conversion from wide local excision (WLE) to mastectomy was 8.1% (95% CI, 5.9 to 11.3), from WLE to more extensive surgery was 11.3% in MF/MC disease (95% CI, 6.8 to 18.3). Due to MRI-detected lesions (in women who did not have additional malignancy on histology) conversion from WLE to mastectomy was 1.1% (95% CI, 0.3 to 3.6) and from WLE to more extensive surgery was 5.5% (95% CI, 3.1 to 9.5). Conclusion MRI staging causes more extensive breast surgery in an important proportion of women by identifying additional cancer, however there is a need to reduce FP MRI detection. Randomized trials are needed to determine the clinical value of detecting additional disease which changes surgical treatment in women with apparently localized breast cancer.

Background: Hormone replacement therapy (HRT) is known to increase breast density, thus decreasing the sensitivity of cancer screening by mammography. Some authors recommend short cessation of HRT before mammography, but evidence showing the effect of such short cessation is limited. The purpose of this study is to examine whether a short cessation of HRT changes mammographic density. Methods: Forty-eight women taking HRT agreed to have mammograms taken before and after stopping HRT for 4 weeks. Mammographic density was measured by Wolfe’s four-point classification, six-categorical visual scale and two different computer methods (interactive-thresholding and SMF). Density values of mammography before and after the cessation of HRT were compared using Wilcoxon signed-rank test for categorical variables and paired t-test for continuous variables. Changes in breast pain and tenderness during mammography, radiation dose, compression force, and breast thickness were also recorded. Results: No significant changes in mammographic density were observed by either visual or computer methods. There were no significant changes in breast pain or in tenderness on mammograms before and after the month’s cessation of HRT. Radiographic measurements were not significantly altered by the 4-week cessation of HRT. Conclusion: In this screening population, a 4-week cessation of HRT before mammograms did not significantly alter mammographic density. © 2008 Elsevier Ireland Ltd. All rights reserved.

We conducted a cross-sectional study nested within a prospective cohort of breast cancer risk factors and two novel measures of breast density volume among 590 women who had attended Glasgow University (1948-1968), replied to a postal questionnaire (2001) and attended breast screening in Scotland (1989-2002). Volumetric breast density was estimated using a fully automated computer programme applied to digitised film-screen mammograms, from medio-lateral oblique mammograms at the first-screening visit. This measured the proportion of the breast volume composed of dense (non-fatty) tissue (Standard Mammogram Form (SMF)%) and the absolute volume of this tissue (SMF volume, cm3). Median age at first screening was 54.1 years (range: 40.0-71.5), median SMF volume 70.25 cm3 (interquartile range: 51.0-103.0) and mean SMF% 26.3%, s.d.=8.0% (range: 12.7-58.8%). Age-adjusted logistic regression models showed a positive relationship between age at last menstrual period and SMF%, odds ratio (OR) per year later: 1.05 (95% confidence interval: 1.01-1.08, P=0.004). Number of pregnancies was inversely related to SMF volume, OR per extra pregnancy: 0.78 (0.70-0.86, P0.001). There was a suggestion of a quadratic relationship between birthweight and SMF%, with lowest risks in women born under 2.5 and over 4 kg. Body mass index (BMI) at university (median age 19) and in 2001 (median age 62) were positively related to SMF volume, OR per extra kg m(-2) 1.21 (1.15-1.28) and 1.17 (1.09-1.26), respectively, and inversely related to SMF%, OR per extra kg m(-2) 0.83 (0.79-0.88) and 0.82 (0.76-0.88), respectively, P0.001. Standard Mammogram Form% and absolute SMF volume are related to several, but not all, breast cancer risk factors. In particular, the positive relationship between BMI and SMF volume suggests that volume of dense breast tissue will be a useful marker in breast cancer studies.

Purpose: Magnetic resonance imaging (MRI) screening enables early detection of breast cancers in women with an inherited predisposition. Interval cancers occurred in women with a BRCA1 mutation, possibly due to fast tumor growth. We investigated the effect of a BRCA1 or BRCA2 mutation and age on the growth rate of breast cancers, as this may influence the optimal screening frequency. Experimental Design: We reviewed the invasive cancers from the United Kingdom, Dutch, and Canadian MRI screening trials for women at hereditary risk, measuring tumor size at diagnosis and on preceding MRI and/or mammography. We could assess tumor volume doubling time (DT) in 100 cancers. Results: Tumor DT was estimated for 43 women with a BRCA1 mutation, 16 women with a BRCA2 mutation, and 41 women at high risk without an identified mutation. Growth rate slowed continuously with increasing age (P = 0.004). Growth was twice as fast in BRCA1 (P = 0.003) or BRCA2 (P = 0.03) patients as in high-risk patients of the same age. The mean DT for women with BRCA1/2 mutations diagnosed at ages ≤40, 41 to 50, and >50 years was 28, 68, and 81 days, respectively, and 83, 121, and 173 days, respectively, in the high-risk group. Pathologic tumor size decreased with increasing age (P = 0.001). Median size was 15 mm for patients ages ≤40 years compared with 9 mm in older patients (P = 0.003); tumors were largest in young women with BRCA1 mutations. Conclusion: Tumors grow quickly in women with BRCA1 mutations and in young women. Age and risk group should be taken into account in screening protocols.

Although breast cancer screening has been shown to work in randomised trials, there is a need to evaluate service screening programmes to ensure that they are delivering the benefit indicated by the trials. We carried out a case–control study to investigate the effect of mammography service screening, in the NHS breast screening programme, on breast cancer mortality in the East Anglian region of the UK. Cases were deaths from breast cancer in women diagnosed between the ages of 50 and 70 years, following the instigation of the East Anglia Breast Screening Programme in 1989. The controls were women (two per case) who had not died of breast cancer, from the same area, matched by date of birth to the cases. Each control was known to be alive at the time of death of her matched case. All women were known to the breast screening programme and were invited, at least once, to be screened. There were 284 cases and 568 controls. The odds ratio (OR) for risk of death from breast cancer in women who attended at least one routine screen compared to those who did not attend was 0.35 (CI: 0.24, 0.50). Adjusting for self-selection bias gave an estimate of the breast cancer mortality reduction associated with invitation to screening of 35% (OR=0.65, 95% CI: 0.48, 0.88). The effect of actually being screened was a 48% breast cancer mortality reduction (OR=0.52, 95% CI: 0.32, 0.84). The results suggest that the National Breast Screening Programme in East Anglia is achieving a reduction in breast cancer deaths, which is at least consistent with the results from the randomised controlled trials of mammographic screening.

Breast cancer risk is grouped into high risk, moderate risk and woman at or near population risk. Who are moderate-risk women? How is their risk assessed? What is the evidence and best practice for screening moderate-risk women?

Breast density measurements can be made from mammograms using either area-based methods, such as the six category classification (SCC), or volumetric based methods, such as the standard mammogram form (SMF). Previously, we have shown how both types of methods generate breast density estimates which are generally close. In this paper, we switch our attention to the question of why, for certain cases, they provide widely differing estimates. First, we show how the underlying physical models of the breast employed in the methods need to be consistent, and how area-based methods are susceptible to projection effects. We then analyse a set of patients whose mammograms show large differences between their SCC and SMF assessments. More precisely, 12% of 657 patients were found to fall into this category. Of these, 2.7% were attributable to errors either in the SMF segmentation algorithms, human error in SCC categorization or poor image exposure. More importantly, 9.3% of the cases appear to be due to fundamental differences between the area- and volume-based techniques. We conclude by suggesting how we might remove half of those discrepancies by introducing a new categorization of the SMF estimates based on the breast thickness. We note however, that this still leaves 6% of patients with large differences between SMF and SCC estimates. We discuss why it might not be appropriate to assume SMF (or any volume measure) has a similar breast cancer risk prediction capability to SCC.

Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10−5). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk. Cancer Res; 75(12); 2457–67. ©2015 AACR.

Contrast enhanced magnetic resonance imaging (CE MRI) is the most sensitive tool for screening women who are at high familial risk of breast cancer. Our aim in this study was to assess the cost-effectiveness of X-ray mammography (XRM), CE MRI or both strategies combined. In total, 649 women were enrolled in the MARIBS study and screened with both CE MRI and mammography resulting in 1881 screens and 1-7 individual annual screening events. Women aged 35-49 years at high risk of breast cancer, either because they have a strong family history of breast cancer or are tested carriers of a BRCA1, BRCA2 or TP53 mutation or are at a 50% risk of having inherited such a mutation, were recruited from 22 centres and offered annual MRI and XRM for between 2 and 7 years. Information on the number and type of further investigations was collected and specifically calculated unit costs were used to calculate the incremental cost per cancer detected. The numbers of cancer detected was 13 for mammography, 27 for CE MRI and 33 for mammography and CE MRI combined. In the subgroup of BRCA1 (BRCA2) mutation carriers or of women having a first degree relative with a mutation in BRCA1 (BRCA2) corresponding numbers were 3 (6), 12 (7) and 12 (11), respectively. For all women, the incremental cost per cancer detected with CE MRI and mammography combined was pound28 284 compared to mammography. When only BRCA1 or the BRCA2 groups were considered, this cost would be reduced to pound11 731 (CE MRI vs mammography) and pound15 302 (CE MRI and mammography vs mammography). Results were most sensitive to the unit cost estimate for a CE MRI screening test. Contrast-enhanced MRI might be a cost-effective screening modality for women at high risk, particularly for the BRCA1 and BRCA2 subgroups. Further work is needed to assess the impact of screening on mortality and health-related quality of life.

The purpose of this study was to examine the relationship between breast arterial calcification (BAC), commonly found on mammography, and cardiovascular disease and its risk factors.The study population, nested within the European Prospective Investigation of Cancer-Norfolk (EPIC-Norfolk) cohort study, consisted of 1,590 women older than 55 years, not taking hormone replacement therapy, and with available screening mammograms. Mammograms were coded by three radiologists for presence or absence of BAC. History of coronary heart disease (CHD), stroke, and diabetes and risk factors for cardiovascular disease (including smoking status, body mass index [BMI], blood pressure, diabetes, and glycosylated hemoglobin [HbA1c]) were independently measured from health examinations in the EPIC study.The prevalence of BAC was 16.0%. Women with BAC were significantly older than those without it. BAC was associated with prevalent CHD, but not stroke. The odds ratio of having CHD was 2.54 (95% confidence interval, 1.03-6.30). The sensitivity and specificity were 32.4% and 85.5%, respectively. Except for smoking, which showed an inverse association, there was no consistent significant association of BAC with cardiovascular disease risk factors including BMI, diabetes, HbA1c, or lipids.BAC found on mammograms was associated with prevalent CHD after adjustment for age, but with low sensitivity. BAC may provide additional information toward identifying cardiovascular disease risk among otherwise healthy women.

Limitations of area based measures of breast density have led several research groups to develop volumetric measures of breast density, for use in predicting risk and in epidemiological research. In this paper, we describe our initial experiences using an automated algorithm (standard mammogram form, SMF) to estimate the volume of the breast that is dense from digitized film mammograms. We performed analyses on 3816 mammograms of 626 women, who were part of the Glasgow Alumni Cohort and had mammograms taken within the Scottish Breast Screening Programme between 1989 and 2002. Absolute volume of dense breast tissue (SMF volume) and the percentage of the volume of the breast that is dense (SMF%) were calculated. The median (interquartile range) of SMF volume was 66 cm 3 (48 to 98), and of SMF% was 23.4% (18.6 to 29.7). SMF%, but not SMF volume, was positively related to a six category classification (SCC) of visually assigned area-based breast density (increase in ln(SMF%) per category increase in SCC: 0.04% (95%CI: 0.03-0.05). The SMF algorithm produced lower SMF volume for craniocaudal (CC) compared with mediolateral oblique (MLO) views, but CC/MLO differences for SMF% were small. The mean right/left difference for ln(SMF volume) was 20.027 cm 3 (95% confidence interval (CI) 20.044 to 20.009) and of ln(SMF%) was 0.005% (95% CI 20.008% to 0.019%). We present these initial data as a background for future analytical work using SMF.

High breast density as measured on mammograms is a strong risk factor for breast cancer in the general population, but its effect in carriers of germline BRCA1 and BRCA2 mutations is unclear. We obtained mammograms from 206 female carriers of BRCA1 or BRCA2 mutations, 96 of whom were subsequently diagnosed with breast cancer and 136 relatives of carriers who were themselves noncarriers. We compared the mammographic densities of affected carriers (cases) and unaffected carriers (controls), and of mutation carriers and noncarriers, using a computer-assisted method of measurement and visual assessment by two observers. Analyses were adjusted for age, parity, body mass index, menopausal status, and hormone replacement therapy use. There was no difference in the mean percent density between noncarriers and carriers. Among carriers, increasing mammographic density was associated with an increased risk of breast cancer (Ptrend = 0.024). The odds ratio (OR; 95% confidence interval) for breast cancer associated with a density of ≥50% was 2.29 (1.23-4.26; P = 0.009). The OR did not differ between BRCA1 and BRCA2 carriers or between premenopausal and postmenopausal carriers. The results suggest that the distribution of breast density in BRCA1 and BRCA2 carriers is similar to that in non-carriers. High breast density in carriers is associated with an increased risk of breast cancer, with the relative risk being similar to that observed in the general population. Use of mammographic density could improve individual risk prediction in carriers. (Cancer Res 2006; 66(3): 1866-72)

Background Women genetically predisposed to breast cancer often develop the disease at a young age when dense breast tissue reduces the sensitivity of X-ray mammography. Our aim was, therefore, to compare contrast enhanced magnetic resonance imaging (CE MRI) with mammography for screening. Methods We did a prospective multicentre cohort study in 649 women aged 35-49 years with a strong family history of breast cancer or a high probability of a BRCA1, BRCA2, or TP53 mutation. We recruited participants from 22 centres in the UK, and offered the women annual screening with CE MRI and mammography for 2-7 years. Findings We diagnosed 35 cancers in the 649 women screened with both mammography and CE MRI (1881 screens): 19 by CE MRI only, six by mammography only, and eight by both, with two interval cases. Sensitivity was significantly higher for CE MRI (77%, 95% CI 60-90) than for mammography (40%, 24-58; p=0.01), and was 94% (81-99) when both methods were used. Specificity was 93% (92-95) for mammography, 81% (80-83) for CE MRI (p

Contrast-enhanced (CE) MRI was used to monitor breast cancer response to neoadjuvant chemotherapy. Patients underwent CE MRI before and after therapy, together with conventional assessment methods (CAM). CE MRI was carried out at 1.5 T in the coronal plain with 3D sequences before and after bolus injection. An expert panel determined chemotherapy response using both CE MRI and CAM. Histopathological response in the surgical specimen was then used to determine the sensitivity and specificity of CE MRI and CAM. In total, 67 patients with 69 breast cancers were studied (mean age of 46 years). Tumour characteristics showed a high-risk tumour population: median size 49 mm: histopathological grade 3 (55%): oestrogen receptor (ER) negative (48%). Histopathological response was as follows: – complete pathological response (pCR) 17%; partial response (pPR) 68%; no response (NR) 15%. Sensitivity of CAM for pCR or pPR was 98% (CI 91–100%) and specificity was 50% (CI 19–81%). CE MRI sensitivity was 100% (CI 94–100%), and specificity was 80% (CI 44–97%). The absolute agreement between assessment methods and histopathology was marginally higher for CE MRI than CAM (81 vs 68%; P=0.09). In 71%, CE MRI increased diagnostic knowledge, although in 20% it was judged confusing or incorrect. The 2nd MRI study significantly increased diagnostic confidence, and in 19% could have changed the treatment plan. CE MRI persistently underestimated minimal residual disease. In conclusion, CE MRI of breast cancer proved more reliable for predicting histopathological response to neoadjuvant chemotherapy than conventional assessment methods.

OBJECTIVE: To establish the diagnostic impact of breast magnetic resonance imaging (MRI), on the management of cases in our mammographic screening programme. METHODS AND MATERIALS: We analysed the cases examined from July 1997 to December 2000 during which time 44,000 population screening mammograms and 85 MRI studies were undertaken on women identified by computer overlap. The studies were reviewed to find the reason for the MRI study and its diagnostic impact. RESULTS: Of 83 studies analysed, 31 were for recurrence of tumour, 33 in newly diagnosed cancer, 22 to assess extent, 11 to monitor primary chemotherapy. In a small diagnostic subset of 19 cases MRI was used to find or characterize a lesion. The 11 cases in which MRI results caused a measurable beneficial change in management were from the query recurrence and diagnostic groups. In 52 cases from all groups, MR increased diagnostic confidence. In 11 cases MRI results were indeterminate, and in six of these stimulated more studies. CONCLUSION: MRI is an expensive investigation and its use must be justified. There is a limited, but valuable role for breast MRI in selected cases from screening assessment. Misinterpretation of enhancing lesions may generate additional procedures. Diagnostic impact was greatest for the detection of tumour recurrence. Warren R. M. L. and Crawley A. (2002). Clinical Radiology, 57, 1090–1097.

Dense mammographic patterns are a risk factor for breast cancer. In a recent case–control study, dense patterns were observed to be associated with a higher relative risk estimate for the more aggressive grade 3 tumors than for grade 1 or 2 tumors. The present study was designed to ascertain, by reference to odds ratio estimates of relative risk by tumor size and histologic grade, whether this was more likely to be due to increased innate predisposition of dense parenchymal patterns to grade 3 tumors, or to dedifferentiation of cases missed at screening due to dense patterns. If the observation were due entirely to dedifferentiation, then for a given size the relative risk of grade 3 tumors would be the same as for grades 1–2. Size-specific relative risks of grade 3 tumors were higher than those of grade 1–2 tumors. It is concluded that the majority of the enhanced risk of grade 3 tumors is due to enhanced innate predisposition to grade 3 tumors in dense breasts.

Mammographic density is a strong risk factor for breast cancer, but its potential application in risk management is not clear, partly due to uncertainties about its interaction with other breast cancer risk factors. We aimed to quantify the impact of mammographic density on breast cancer risk in women aged 40-49 at intermediate familial risk of breast cancer (average lifetime risk of 23%), in particular in premenopausal women, and to investigate its relationship with other breast cancer risk factors in this population. We present the results from a case-control study nested with the FH01 cohort study of 6,710 women mostly aged 40-49 at intermediate familial risk of breast cancer. One hundred and three cases of breast cancer were age-matched to one or two controls. Density was measured by semiautomated interactive thresholding. Absolute density, but not percent density, was a significant risk factor for breast cancer in this population after adjusting for area of nondense tissue (OR per 10 cm(2) = 1.07, 95% CI 1.00-1.15, p = 0.04). The effect was stronger in premenopausal women, who made up the majority of the study population. Absolute density remained a significant predictor of breast cancer risk after adjusting for age at menarche, age at first live birth, parity, past or present hormone replacement therapy, and the Tyrer-Cuzick 10-year relative risk estimate of breast cancer. Absolute density can improve breast cancer risk stratification and delineation of high-risk groups alongside the Tyrer-Cuzick 10-year relative risk estimate.

Geneticists are able to identify the risk of breast cancer. Strategies on offer include prevention, early diagnosis by screening, and prophylactic surgery. This paper analyses the evidence for offering screening. The radiation dose of mammography has been measured, but the risk is not fully known. Mammography screening of women of 40-50 years in the normal population has known effect. Little evidence is available for women under 40 years or for women with genetic susceptibility to breast cancer. Dense parenchymal pattern is associated with high grade cancers, and is both a risk factor and a reason for impaired screening sensitivity. Whether this applies to younger women or women at high risk is speculative. The pathological features of the cancers in gene carriers show differences from those occurring in normal women. This work should be correlated with imaging features. There is no literature to support the use of newer imaging methods in these women. Ultrasound and MRI avoid radiation and may be useful in dense breasts. SestaMIBI and PET scanning are not yet mature enough for screening, and may never have such a role. Any newer modality must be subjected to a formal randomised trial before being offered to screen women at high risk.