Computerized Analysis of Mammographic Parenchymal Patterns on a Large Clinical Dataset of Full-Field Digital Mammograms: Robustness Study with Two High-Risk Datasets

The purpose of this study was to demonstrate the robustness of our prior computerized texture analysis method for breast cancer risk assessment, which was developed initially on a limited dataset of screen-film mammograms. This current study investigated the robustness by (1) evaluating on a large clinical dataset, (2) using full-field digital mammograms (FFDM) as opposed to screen-film mammography, and (3) incorporating analyses over two types of high-risk patient sets, as well as patients at low risk for breast cancer. The evaluation included the analyses on the parenchymal patterns of women at high risk of developing of breast cancer, including both BRCA1/2 gene mutation carriers and unilateral cancer patients, and of women at low risk of developing breast cancer. A total of 456 cases, including 53 women with BRCA1/2 gene mutations, 75 women with unilateral cancer, and 328 low-risk women, were retrospectively collected under an institutional review board approved protocol. Regions-of-interest (ROIs), were manually selected from the central breast region immediately behind the nipple. These ROIs were subsequently used in computerized feature extraction to characterize the mammographic parenchymal patterns in the images. Receiver operating characteristic analysis was used to assess the performance of the computerized texture features in the task of distinguishing between high-risk and low-risk subjects. In a round robin evaluation on the FFDM dataset with Bayesian artificial neural network analysis, AUC values of 0.82 (95% confidence interval [0.75, 0.88]) and 0.73 (95% confidence interval [0.67, 0.78]) were obtained between BRCA1/2 gene mutation carriers and low-risk women, and between unilateral cancer and low-risk women, respectively. These results from computerized texture analysis on digital mammograms demonstrated that high-risk and low-risk women have different mammographic parenchymal patterns. On this large clinical dataset, we validated our methods for quantitative analyses of mammographic patterns on FFDM, statistically demonstrating again that women at high risk tend to have dense breasts with coarse and low-contrast texture patterns.     

Power Spectral Analysis of Mammographic Parenchymal Patterns for Breast Cancer Risk Assessment

PURPOSE: The purpose of the study was to evaluate the usefulness of power law spectral analysis on mammographic parenchymal patterns in breast cancer risk assessment. MATERIALS AND METHODS: Mammograms from 172 subjects (30 women with the BRCA1/BRCA2 gene mutation and 142 low-risk women) were retrospectively collected and digitized. Because age is a very important risk factor, 60 low-risk women were randomly selected from the 142 low-risk subjects and were age matched to the 30 gene mutation carriers. Regions of interest were manually selected from the central breast region behind the nipple of these digitized mammograms and subsequently used in power spectral analysis. The power law spectrum of the form P(f) = B/f(beta) was evaluated for the mammographic patterns. The performance of exponent beta as a decision variable for differentiating between gene mutation carriers and low-risk women was assessed using receiver operating characteristic analysis for both the entire database and the age-matched subset. RESULTS: Power spectral analysis of mammograms demonstrated a statistically significant difference between the 30 BRCA1/BRCA2 gene mutation carriers and the 142 low risk women with an average beta values of 2.92 (+/-0.28) and 2.47(+/-0.20), respectively. An A (z) value of 0.90 was achieved in distinguishing between gene mutation carriers and low-risk women in the entire database, with an A (z) value of 0.89 being achieved on the age-matched subset. CONCLUSIONS: The BRCA1/BRCA2 gene mutation carriers and low-risk women have different mammographic parenchymal patterns. It is expected that women identified as high risk by computerized feature analyses might potentially be more aggressively screened for breast cancer.     

Computerized analysis of mammographic parenchymal patterns for breast cancer risk assessment: feature selection

Our purpose in this study was to identify computer-extracted, mammographic parenchymal patterns that are associated with breast cancer risk. We extracted 14 features from the central breast region on digitized mammograms to characterize the mammographic parenchymal patterns of women at different risk levels. Two different approaches were employed to relate these mammographic features to breast cancer risk. In one approach, the features were used to distinguish mammographic patterns seen in low-risk women from those who inherited a mutated form of the BRCA1/BRCA2 gene, which confers a very high risk of developing breast cancer. In another approach, the features were related to risk as determined from existing clinical models (Gail and Claus models), which use well-known epidemiological factors such as a woman's age, her family history of breast cancer, reproductive history, etc. Stepwise linear discriminant analysis was employed to identify features that were useful in differentiating between "low-risk" women and BRCA1/BRCA2-mutation carriers. Stepwise linear regression analysis was employed to identify useful features in predicting the risk, as estimated from the Gail and Claus models. Similar computer-extracted mammographic features were identified in the two approaches. Results show that women at high risk tend to have dense breasts and their mammographic patterns tend to be coarse and low in contrast.     

Computerized detection of masses in digital mammograms: Investigation of feature-analysis techniques

Mammographic screening of asymptomatic women has shown effectiveness in the reduction of breast cancer mortality. We are developing a computerized scheme for the detection of mammographic masses as an aid to radiologists in mammographic screening programs. Possible masses on digitized screen/film mammograms are initially identified using a nonlinear bilateral-subtraction technique, which is based on asymmetric density patterns occurring in corresponding portions of right and left mammograms. In this study, we analyze the characteristics of actual masses and nonmass detections to develop feature-analysis techniques with which to reduce the number of non-mass (ie, false-positive) detections. These feature-analysis techniques involve (1) the extraction of various features (such as area, contrast, circularity and border-distance based on the density and geometric information of masses in both processed, and original breast images), and (2) tests of the extracted features to reduce nonmass detections. Cumulative histograms of both actual-mass detections and nonmass detections are used to characterize extracted features and to determine the cutoff values used in the feature tests. The effectiveness of the feature-analysis techniques is evaluated in combination with the computerized detection scheme that uses the nonlinear bilateral-subtraction technique using free-response receiver operating characteristic analysis and 77 patient cases (308 mammograms). Results show that the feature-analysis techniques effectively improve the performance of the computerized detection scheme: about 35% false-positive detections were eliminated without loss in sensitivity when the feature-analysis techniques were used.     

Computer-aided diagnosis in mammography: classification of mass and normal tissue by texture analysis

Computer-aided diagnosis schemes are being developed to assist radiologists in mammographic interpretation. In this study, we investigated whether texture features could be used to distinguish between mass and non-mass regions in clinical mammograms. Forty-five regions of interest (ROIs) containing true masses with various degrees of visibility and 135 ROIs containing normal breast parenchyma were extracted manually from digitized mammograms as case samples. Spatial-grey-level-dependence (SGLD) matrices of each ROI were calculated and eight texture features were calculated from the SGLD matrices. The correlation and class-distance properties of extracted texture features were analysed. Selected texture features were input into a modified decision-tree classification scheme. The performance of the classifier was evaluated for different feature combinations and orders of features on the tree. A classification accuracy of about 89% sensitivity and 76% specificity was obtained for ordered features, sum average, correlation, and energy, during the training procedure. With a leave-one-out method, the test result was about 76% sensitivity and 64% specificity. The results of this preliminary study demonstrate the feasibility of using texture information for classification of mass and normal breast tissue, which will be likely to be useful for classifying true and false detections in computer-aided diagnosis programmes.     

Androgen receptor CAG repeat length in Jewish Israeli women who are BRCA1/2 mutation carriers: association with breast/ovarian cancer phenotype

BRCA1/2 mutation carriers are at an increased risk for developing breast and/or ovarian cancer. Yet, the genetic and environmental factors that govern the phenotypic expression of mutant BRCA1/2 alleles remain elusive. The CAG repeat within exon 1 of the androgen receptor (AR) gene is reportedly associated with breast cancer phenotype in BRCA1 mutation carriers. Two hundred and twenty seven BRCA1/2 mutation carriers were genotyped for the polymorphic AR CAG repeat, and allele size was correlated with breast/ovarian cancer morbidity parameters. Of 227 BRCA1/2 carriers, 169 were BRCA1 mutation carriers and 58 carried a BRCA2 mutation, 149 had breast and/or ovarian cancer and 78 were asymptomatic mutation carriers. The mean age at diagnosis in women with either or both neoplasms was 46.7+/-11.2 years, and that of the asymptomatic group - 45.8+/-9.4 years, a statistically insignificant difference. The AR CAG repeat ranged from eight to 28 in all tested women, and the mean number of the repeats were not statistically different between affected (18.3+/-2.4) and asymptomatic mutation carriers (18.6+/-2.1). The AR CAG repeat among patients with early onset (<42 years) breast cancer was significantly shorter (17.5+/-2.3) compared with asymptomatic individuals (18.6+/-2.1) (P<0.01), and the shorter allele - the younger the age at diagnosis. There is no conclusive evidence of association between AR CAG repeat size and breast or ovarian cancer risk in Jewish BRCA1/2 mutation carriers. A small effect of a short AR CAG allele size on breast cancer at early age (<42 years) cannot be excluded.     

Breast and ovarian cancer risk perception after prophylactic salpingo-oophorectomy due to an inherited mutation in the BRCA1 or BRCA2 gene

It is often recommended that women who carry a mutation in the BRCA1 or BRCA2 gene have their ovaries and fallopian tubes removed to reduce their risk of gynecologic cancer. The aim of this study was to evaluate women's perception of their risk of breast and ovarian cancer before and after prophylactic salpingo-oophorectomy. We surveyed 127 women who carry a BRCA1 or BRCA2 mutation and who underwent prophylactic salpingo-oophorectomy at the University Health Network, Toronto. Subjects were asked to estimate their risks of breast and ovarian cancer before and after surgery. Their perceived risks of cancers were then compared with published risks, based on their mutation status. BRCA1 carriers estimated their risk of breast cancer risk to be, on average, 69% before surgery and 41% after surgery. They estimated their risk of ovarian cancer to be 55% before surgery and 11% after surgery. BRCA2 carriers estimated their risk of breast cancer to be 69% prior to surgery and 45% after surgery and their perceived risk of ovarian cancer to be 43% before surgery and 8% after surgery. Compared with published risk figures, the perceived risk of ovarian cancer before prophylactic salpingo-oophorectomy was overestimated by 47% of BRCA1 mutation carriers and by 61% of BRCA2 mutation carriers. Most women who have undergone genetic counseling and subsequently choose prophylactic salpingo-oophorectomy accurately perceive their risk of breast cancer. However, in this study, many women overestimated their risk of ovarian cancer, particularly women who carry a BRCA2 mutation.     

Computerized prediction of risk for developing breast cancer based on bilateral mammographic breast tissue asymmetry

This study developed and assessed a computerized scheme to detect breast abnormalities and predict the risk of developing cancer based on bilateral mammographic tissue asymmetry. A digital mammography database of 100 randomly selected negative cases and 100 positive cases for having high-risk of developing breast cancer was established. Each case includes four images of cranio-caudal (CC) and medio-lateral oblique (MLO) views of the left and right breast. To detect bilateral mammographic tissue asymmetry, a pool of 20 computed features was assembled. A genetic algorithm was applied to select optimal features and build an artificial neural network based classifier to predict the likelihood of a test case being positive. The leave-one-case-out validation method was used to evaluate the classifier performance. Several approaches were investigated to improve the classification performance including extracting asymmetrical tissue features from either selected regions of interests or the entire segmented breast area depicted on bilateral images in one view, and the fusion of classification results from two views. The results showed that (1) using the features computed from the entire breast area, the classifier yielded the higher performance than using ROIs, and (2) using a weighted average fusion method, the classifier achieved the highest performance with the area under ROC curve of 0.781 ± 0.023. At 90% specificity, the scheme detected 58.3% of high-risk cases in which cancers developed and verified 6–18 months later. The study demonstrated the feasibility of applying a computerized scheme to detect cases with high risk of developing breast cancer based on computer-detected bilateral mammographic tissue asymmetry.     

Common alleles at 6q25.1 and 1p11.2 are associated with breast cancer risk for BRCA1 and BRCA2 mutation carriers

Two single nucleotide polymorphisms (SNPs) at 6q25.1, near the ESR1 gene, have been implicated in the susceptibility to breast cancer for Asian (rs2046210) and European women (rs9397435). A genome-wide association study in Europeans identified two further breast cancer susceptibility variants: rs11249433 at 1p11.2 and rs999737 in RAD51L1 at 14q24.1. Although previously identified breast cancer susceptibility variants have been shown to be associated with breast cancer risk for BRCA1 and BRCA2 mutation carriers, the involvement of these SNPs to breast cancer susceptibility in mutation carriers is currently unknown. To address this, we genotyped these SNPs in BRCA1 and BRCA2 mutation carriers from 42 studies from the Consortium of Investigators of Modifiers of BRCA1/2. In the analysis of 14 123 BRCA1 and 8053 BRCA2 mutation carriers of European ancestry, the 6q25.1 SNPs (r(2) = 0.14) were independently associated with the risk of breast cancer for BRCA1 mutation carriers [hazard ratio (HR) = 1.17, 95% confidence interval (CI): 1.11-1.23, P-trend = 4.5 × 10(-9) for rs2046210; HR = 1.28, 95% CI: 1.18-1.40, P-trend = 1.3 × 10(-8) for rs9397435], but only rs9397435 was associated with the risk for BRCA2 carriers (HR = 1.14, 95% CI: 1.01-1.28, P-trend = 0.031). SNP rs11249433 (1p11.2) was associated with the risk of breast cancer for BRCA2 mutation carriers (HR = 1.09, 95% CI: 1.02-1.17, P-trend = 0.015), but was not associated with breast cancer risk for BRCA1 mutation carriers (HR = 0.97, 95% CI: 0.92-1.02, P-trend = 0.20). SNP rs999737 (RAD51L1) was not associated with breast cancer risk for either BRCA1 or BRCA2 mutation carriers (P-trend = 0.27 and 0.30, respectively). The identification of SNPs at 6q25.1 associated with breast cancer risk for BRCA1 mutation carriers will lead to a better understanding of the biology of tumour development in these women.     

Correspondence in texture features between two mammographic views

It is well established that radiologists are better able to interpret mammograms when two mammographic views are available. Consequently, two mammographic projections are standard: mediolateral oblique (MLO) and craniocaudal (CC). Computer-aided diagnosis algorithms have been investigated for assisting in the detection and diagnosis of breast lesions in digitized/digital mammograms. A few previous studies suggest that computer-aided systems may also benefit from combining evidence from the two views. Intuitively, we expect that there would only be value in merging data from two views if they provide complementary information. A measure of the similarity of information is the correlation coefficient between corresponding features from the MLO and CC views. The purpose of this study was to investigate the correspondence in Haralick's texture features between the MLO and CC mammographic views of breast lesions. Features were ranked on the basis of correlation values and the two-view correlation of features for subgroups of data including masses versus calcification and benign versus malignant lesions were compared. All experiments were performed on a subset of mammography cases from the Digital Database for Screening Mammography (DDSM). It was observed that the texture features from the MLO and CC views were less strongly correlated for calcification lesions than for mass lesions. Similarly, texture features from the two views were less strongly correlated for benign lesions than for malignant lesions. These differences were statistically significant. The results suggest that the inclusion of texture features from multiple mammographic views in a CADx algorithm may impact the accuracy of diagnosis of calcification lesions and benign lesions.     

The quantitative analysis of mammographic densities

Quantitative classification of mammographic parenchyma based on radiological assessment has been shown to provide one of the strongest estimates of the risk of developing breast cancer. Existing classification schemes, however, are limited by coarse category scales. In addition, subjectivity can lead to sizeable interobserver and intraobserver variations. Here, we propose an interactive thresholding technique applied to digitized film-screen mammograms, which assesses the proportion of the mammographic image representing radiographically dense tissue. Observers viewed images on a CRT display and selected grey-level thresholds from which the breast and regions of dense tissue in the breast were identified. The proportion of radiographic density was then calculated from the image histogram. The technique was evaluated for the mammograms of 30 women and is well correlated (R > 0.91, Spearman coefficient) with a six-category subjective classification of radiographic density by radiologists. The technique was found to be very reliable with an intraclass correlation coefficient between observers typically R > 0.9. This technique may have a role in routine mammographic analysis for the purpose of assessing risk categories and as a tool in studies of the etiology of breast cancer, in particular for monitoring changes in breast parenchyma during potential preventive interventions.     

Histopathological features of breast cancer in carriers of ATM gene variants

AIMS: Germline variants in the ataxia telangiectasia mutated (ATM) gene have been implicated in increased breast cancer risk. The aim of this study was to determine whether the histopathology of breast cancers occurring in ATM variant carriers is distinctive or resembles the described BRCA1 mutation-associated phenotype. METHODS: The histopathological features of breast cancers occurring in ATM variant carriers from multiple-case breast cancer families were compared with matched controls. The test group included 21 cases of in situ and/or invasive cancer from carriers of either the IVS10-6T-->G, 2424V-->G or 1420L-->F ATM variants in the absence of BRCA1 or BRCA2 mutations. An additional four invasive cancers from carriers of a pathogenic BRCA1 mutation in the context of a familial ATM variant were also examined. RESULTS: The histopathology of breast cancers in ATM variant-only carriers was not significantly different from controls and known features of BRCA1 mutation-associated cancer were rarely seen. In contrast, these features were prominent in the small group of cases with a pathogenic BRCA1 mutation. CONCLUSIONS: Breast cancer occurring in carriers of ATM variants is not associated with distinctive histopathological features and does not resemble the tumour phenotype commonly observed in BRCA1 mutation carriers.     

Germ-line mutations in BRCA1 or BRCA2 in the normal breast are associated with altered expression of estrogen-responsive proteins and the predominance of progesterone receptor A

The breast cancer susceptibility genes BRCA1 and BRCA2 are responsible for a large proportion of familial breast and ovarian cancer, yet little is known of how disruptions in the functions of the proteins these genes encode increased cancer risk preferentially in hormone-dependent tissue. There is no information on whether a germ-line mutation in BRCA1 or BRCA2 causes disruptions in hormone-signaling pathways in the normal breast. In this study markers of hormone responsiveness were measured in prophylactically removed normal breast tissue (n = 31) in women bearing a germ-line pathogenic mutation in one of the BRCA genes. The estrogen receptor (ER) and proteins associated with ER action in hormone-sensitive tissues, namely, PS2 and the progesterone receptor (PR), were detected immunohistochemically. ER expression was not different in BRCA mutation carriers than in noncarriers, but there was a reduction in PS2 expression. PR expression was also reduced, and there was a striking lack of expression of the PRB isoform, which resulted in cases with PRA-only expression in BRCA1 and BRCA2 mutation carriers. The alterations in PS2 and PR expression were similar in the BRCA1 and BRCA2 carriers, demonstrating that although these proteins are structurally and functionally distinct, there is overlap in their interaction with hormone-signaling pathways. This study provides evidence for altered cell function arising from loss of function of one BRCA allele in the normal breast, leading to PS2 loss, preferential PRB loss, and expression of PRA alone. In breast cancer development, PRA overexpression becomes evident in premalignant lesions and is associated with features of poor prognosis in invasive disease and altered cell function in vitro. The results of this study suggest that heterozygosity for a germ-line mutation in BRCA1 or BRCA2 results in development of PRA predominance. This is likely to lead to changes in progesterone signaling in hormone-dependent tissues, which may be a factor in the increased risk of cancer in these tissues in women with germ-line BRCA1 or BRCA2 mutations.     

High follicular phase luteinizing hormone levels in young healthy BRCA1 mutation carriers: implications for breast and ovarian cancer risk

BRCA1 mutation carriers have up to 80% life-time risk of developing breast cancer and 20-40% risk of developing ovarian cancer. High LH levels have been linked to increased risks of both breast and ovarian cancers in some studies and it is unknown whether gonadotropin levels are associated with BRCA1 mutation status. The aim of the study was to explore whether gonadotropin levels were associated with BRCA1 mutation status among healthy 40-year-old-women from hereditary breast cancer families. All women completed a questionnaire including information on reproductive factors and OC use. We measured height, weight, breast volumes, and plasma levels of LH, FSH, and estradiol (E2) once during menstrual cycle days 5-10 and once again during cycle days 18-23 in 43 non-carriers from BRCA1 families, 20 BRCA1 mutation carriers, and 101 women from non-BRCA1/2 families. The strongest predictors of high LH levels among BRCA1 mutation carriers and non-carriers during cycle days 5-10 were being a BRCA1 mutation carrier (p=0.002), lack of current OC use (p=0.003), and being nulliparous (p=0.01), adjusted for age and menstrual cycle day when the samples were obtained. This association was seen both in non-OC users and current OC users but was only significant in the former group (p=0.005). Because of multiple analyses it is possible that our finding is a result of a Type 1 statistical error. After a permutation test the new adjusted p value in non-OC users was 0.05. FSH and E2 were similar in non-carriers, BRCA1 mutation carriers and women from non-BRCA1/2 families. We found significantly elevated LH levels in the follicular phase among young healthy BRCA1 mutation carriers compared with non-carriers from BRCA1 families. This is a small study and confirmatory studies are warranted to establish whether elevated LH levels are part of the BRCA1 phenotype and may be manipulated in order to reduce cancer risks in BRCA1 mutation carriers.     

Adjusting the estimated proportion of breast cancer cases associated with BRCA1 and BRCA2 mutations: public health implications.

PURPOSE: Mutations in BRCA1 or BRCA2 genes increase breast cancer risk. Assuring reliability of information about these mutations is increasingly important to the health care community; mutation testing is becoming more widespread. We describe a methodology for assessing such information. METHODS: Our approach integrates four interdependent epidemiologic parameters: (1) the probability of developing breast cancer, (2) the proportion of breast cancer cases with a BRCA1 or BRCA2 mutation, (3) the proportion of women that carries a mutation, and (4) the proportion of women with a mutation that develops cancer. We assess the plausibility of estimates of these parameters from published reports and commonly accessed information sources. RESULTS: Assuming a fixed probability of developing breast cancer, the following estimates for the other three epidemiologic parameters are derived for women by age 70: 1% to 2% of all breast cancer cases are associated with a BRCA1 or BRCA2 mutation; 1 in 300 to 1 in 465 women carry a mutation; and 35 to 65% of mutation carriers develop breast cancer. Within these ranges, however, only selected combinations are plausible. The proportion of mutation-related breast cancer is lower than listed in some common information sources (1 to 2% vs 6%). Also, penetrance is somewhat lower and the carrier rate somewhat higher. CONCLUSIONS: The four epidemiologic parameters can be integrated to test their plausibility. BRCA1 and BRCA2 mutations are associated with only one-third as many breast cancer cases in the general population as reported by commonly accessed information sources.     

Anticipation in hereditary breast cancer

To determine whether familial breast cancer occurs at a younger age in successive generations, we reviewed the clinical records of 435 Ashkenazi women with breast cancer referred to our cancer genetic clinic. Ninety-eight who reported a maternal history of breast cancer were selected for further investigation. All women were genotyped for founder BRCA1/2 mutations (185delAG, 5382insC and 6174delT). Mean age at dignosis was 55.35 +/- 14.21 years in the maternal generation and 48.17 +/- 9.32 years in the daughters (t = - 4.144; p < 0.001). Seventeen women carried a BRCA1 mutation and 12 the 6174delT mutation in BRCA2. Among carriers of the BRCA1 mutation, mean age at diagnosis in the mothers' generation (44 +/- 10.18 years) did not differ from that recorded in the daughters (40.76 +/- 76 years). Among BRCA2 mutation carriers and non-carriers, the mean age at diagnosis in the daughters' generation (41.4 +/- 7.2 and 50.7 +/- 8.8 years, respectively) was younger than in the mothers (61.75 +/- 14.1 and 57.08 +/- 13.7 years, respectively) (t = - 4.29; p < 0.001 for BRCA2 carriers and t = -3.76; p < 0.001 for non-BRCA1/2 carriers). Daughters who were carriers of BRCA1/2 mutations developed breast cancer at a significantly younger age than non-carriers, whilst in the mothers' generation, carriers of BRCA1 mutations developed breast cancer at a significantly younger age than carriers of BRCA2 mutations and non-carriers. BRCA1 mutations predispose to breast cancer at an early age in both mothers and daughters, whereas mutations in BRCA2 were associated with significantly younger age at diagnosis in the second generation. This observation could be related to gene-environmental interactions causing anticipation in BRCA2 mutation carriers.     

Novel approach to evaluating breast density utilizing ultrasound tomography

Women with high mammographic breast density have a four- to fivefold increased risk of developing breast cancer compared to women with fatty breasts. Many preventative strategies have attempted to correlate changes in breast density with response to interventions including drugs and diet. The purpose of this work is to investigate the feasibility of assessing breast density with acoustic velocity measurements with ultrasound tomography, and to compare the results with existing measures of mammographic breast density. An anthropomorphic breast tissue phantom was first imaged with our computed ultrasound tomography clinical prototype. Strong positive correlations were observed between sound speed and material density, and sound speed and computed tomography number (Pearson correlation coefficients= 0.87 and 0.91, respectively). A cohort of 48 women was then imaged. Whole breast acoustic velocity was determined by creating image stacks and evaluating the sound speed frequency distribution. The acoustic measures of breast density were evaluated by comparing these results to two mammographic density measures: (1) qualitative estimates determined by a certified radiologist using the BI-RADS Categorical Assessment based on a 1 (fatty) to 4 (dense) scale, and (2) quantitative measurements via digitization and computerized analysis of archival mammograms. A one-way analysis of variance showed that a significant difference existed between the mean values of sound speed according to BI-RADS category, while post hoc analyses using the Scheffé criterion for significance indicated that BI-RADS 4 (dense) patients had a significantly higher sound speed than BI-RADS 1, 2, and 3 at an alpha level of 0.05. Using quantitative measures of breast density, a direct correlation between the mean acoustic velocity and calculated mammographic percent breast density was demonstrated with correlation coefficients ranging from 0.75 to 0.89. The results presented here support the hypothesis that sound speed can be used as an indicator of breast tissue density. Noninvasive, nonionizing monitoring of dietary and chemoprevention interventions that affect breast density are now possible.     

The risk of breast cancer in BRCA1 and BRCA2 mutation carriers without a first‐degree relative with breast cancer

The objective of this study was to estimate the lifetime risk of breast cancer in women with a BRCA1 or BRCA2 mutation with and without at least 1 first‐degree relative with breast cancer. A total of 2835 women with a BRCA1 or BRCA2 mutation were followed. Age‐ and gene‐specific breast cancer rates were calculated. The relative risks of breast cancer for subjects with a family history of breast cancer, compared to no family history were calculated. The mean age at baseline was 41.1 years, and they were followed for a mean of 6.0 years. The estimated penetrance of breast cancer to age 80 years was 60.8% for BRCA1 and 63.1% for BRCA2. For all BRCA carriers, the penetrance of breast cancer to age 80 for those with no first‐degree relative with breast cancer was 60.4% and 63.3% for those with at least 1 first‐degree relative with breast cancer. The risk of breast cancer for BRCA carriers with no first‐degree relative with breast cancer is substantial, and as a result, clinical management for these women should be the same as those for women with an affected relative.     

Computerized analysis of radiographic bone patterns: effect of imaging conditions on performance

We are developing computerized methods for characterizing the bone texture pattern from digitized skeletal radiographs. For this method to be useful clinically, it must be able to distinguish between weak and strong bone under the range of exposure conditions potentially encountered in the clinical setting. In this study, we examined the effect of exposure conditions on Fourier-based texture features. Thirty-four femoral specimens from total hip arthroplasties were radiographed multiple times under different exposure conditions. The specimens underwent mechanical strength testing from which load to failure values were obtained. The performance of the texture features were investigated in the task of distinguishing between strong and weak bone as characterized by the load to failure values. The texture features showed no dependence upon focal spot size of the x-ray tube or magnification. The texture features did show a dependence with relative exposure, peak kilovoltage, and amount of scattering material.