Kathy R. Brandt

Texture Features from Mammographic Images and Risk of Breast Cancer

Mammographic percent density (PD) is a strong risk factor for breast cancer, but there has been relatively little systematic evaluation of other features in mammographic images that might additionally predict breast cancer risk. We evaluated the association of a large number of image texture features with risk of breast cancer using a clinic-based case-control study of digitized film mammograms, all with screening mammograms before breast cancer diagnosis. The sample was split into training (123 cases and 258 controls) and validation (123 cases and 264 controls) data sets. Age-adjusted and body mass index (BMI)–adjusted odds ratios (OR) per SD change in the feature, 95% confidence intervals, and the area under the receiver operator characteristic curve (AUC) were obtained using logistic regression. A bootstrap approach was used to identify the strongest features in the training data set, and results for features that validated in the second half of the sample were reported using the full data set. The mean age at mammography was 64.0 ± 10.2 years, and the mean time from mammography to breast cancer was 3.7 ± 1.0 (range, 2.0-5.9 years). PD was associated with breast cancer risk (OR, 1.49; 95% confidence interval, 1.25-1.78). The strongest features that validated from each of several classes (Markovian, run length, Laws, wavelet, and Fourier) showed similar ORs as PD and predicted breast cancer at a similar magnitude (AUC = 0.58-0.60) as PD (AUC = 0.58). All of these features were automatically calculated (unlike PD) and measure texture at a coarse scale. These features were moderately correlated with PD (r = 0.39-0.76), and after adjustment for PD, each of the features attenuated only slightly and retained statistical significance. However, simultaneous inclusion of these features in a model with PD did not significantly improve the ability to predict breast cancer. (Cancer Epidemiol Biomarkers Prev 2009;18(3):837–45)

Age-specific Trends in Mammographic Density The Minnesota Breast Cancer Family Study

Mammographic density is a strong risk factor for breast cancer, yet few studies have evaluated density trends, and associated factors, over time. The authors retrieved and digitized mammograms (> or =1 per woman) imaged in 1990-2003 to evaluate percent density (PD) in the Minnesota Breast Cancer Family cohort. Multivariable-adjusted, mixed-effects, repeated-measures models incorporating a natural cubic spline provided estimates of nonlinear trends in PD with age and were used to examine association with covariates. Overall, 5,698 mammograms from 1,689 women with covariate information were digitized. In descriptive analyses, the highest median PD was 33.1% (interquartile range, 21.8%; n = 230) among premenopausal women, 31.0% (interquartile range, 23.2%; n = 175) among women who transitioned from pre- to postmenopause, and 18.7% (interquartile range, 22.2%; n = 1,284) among postmenopausal women. On average, premenopausal compared with postmenopausal women had 1.9% (p = 0.001) higher PD. In repeated-measures analyses, greater declines in PD occurred with menopause and among women with higher baseline PD; current postmenopausal hormone use and higher body mass index modified these declines (p interaction < 0.001). No significant modification of the density change with age was seen with parity/age at first birth, age at menarche, oral contraceptive use, family history of breast or ovarian cancer in a first- or second-degree relative, educational level, smoking status, or alcohol intake were observed. These data suggest that menopause, baseline PD, postmenopausal hormone use, and body mass index predict changes in mammographic density trends during adult life.

Interactive fast spin-echo imaging.

It is shown that a spin‐echo sequence may be used to acquire T2‐weighted, high‐resolution, high‐SNR sections at quasi‐real‐time frame rates for interactive, diagnostic imaging. A single‐shot fast spin‐echo sequence was designed which employs driven equilibrium to realign transverse magnetization remaining at the final spin echo. Driven equilibrium is shown to improve T2 contrast at a given TR, or conversely to reduce TR by approximately 1000 msec and thus increase temporal resolution while maintaining a given level of contrast. Wiener demodulation of k‐space data prior to reconstruction is shown to reduce blurring caused by T2‐decay while constraining noise often associated with other inverse filters. Images are continuously acquired, reconstructed, and displayed at rates of one image every one to two seconds, while section position and contrast may be altered interactively. The clinical utility of this method is demonstrated with applications to dynamic pelvic floor imaging and interactive obstetric imaging. Magn Reson Med 44:339–348, 2000.

Prenatal and Perinatal Correlates of Adult Mammographic Breast Density

Background: Adult mammographic percent density is one of the strongest known risk factors for breast cancer. In utero exposure to high levels of endogenous estrogens (or other pregnancy hormones) has been hypothesized to increase breast cancer risk in later life. We examined the hypothesis that those factors associated with higher levels of estrogen during pregnancy or shortly after birth are associated with higher mammographic breast density in adulthood. Methods: We analyzed data on 1,893 women from 360 families in the Minnesota Breast Cancer Family Study who had screening mammograms, risk factor data, over age 40, and no history of breast cancer. Prenatal and perinatal risk factor data were ascertained using a mailed questionnaire. Mammographic percent density and dense area were estimated from the mediolateral oblique view using Cumulus, a computer-assisted thresholding program. Linear mixed effects models incorporating familial correlation were used to assess the association of risk factors with percent density, adjusting for age, weight, and other breast cancer risk factors, all at time of mammography. Results: The mean age at mammography was 60.4 years (range, 40-91 years), and 76% were postmenopausal. Among postmenopausal women, there was a positive association of birthweight with percent density (P trend <0.01), with an adjusted mean percent density of 17.1% for <2.95 kg versus 21.0% for ≥3.75 kg. There were suggestive positive associations with gestational age (mean percent density of 16.7% for preterm birth, 20.2% for term birth, and 23.0% for late birth; P trend = 0.07), maternal eclampsia/preeclampsia (mean percent density of 19.9% for no and 14.6% for yes; P = 0.16), and being breast-fed as an infant (mean percent density of 18.2% for never and 20.0% for ever; P = 0.08). There was no association of percent density with maternal age, birth order, maternal use of alcohol or cigarettes, or neonatal jaundice. Except for being breast-fed, these associations showed similar but attenuated trends among premenopausal women, although none were statistically significant. The results for dense area paralleled the percent density results. The associations of gestational age and being breast-fed as an infant with percent density attenuated when included in the same model as birthweight. Conclusions: Birthweight was positively associated with mammographic breast density and dense area among postmenopausal women and more weakly among premenopausal women, suggesting that it may be a marker of this early life exposure. These results offer some support to the hypothesis that pregnancy estrogens or other pregnancy changes may play a role in breast cancer etiology, and suggest that these factors may act in part through long-term effects on breast density.

Evaluation of aromatase expression in mammographically dense and non-dense regions of the breast in healthy women.

Abstract #4033 Background : Aromatase activity within the breast is a source of estrogen that may cause breast cancer. Mammographic density (MD) is a risk factor for breast cancer whose biologic basis is unknown. Our study compared aromatase expression in tissue from dense and non-dense areas of the breasts of healthy volunteers.
 Methods : Participants were 40+ yrs, had a screening mammogram with visible MD, no history of cancer and were not on endocrine therapy. Ultrasound-guided core biopsies were done within 6 months of mammography to obtain three paired cores from mammographically dense and non-dense regions of the breast. Immunostaining for aromatase expression employed the streptavidin-biotin amplification method using the recently developed 677 mouse monoclonal antibody. Immunoreactivity (IR) was scored in terms of proportion of cells staining positive for aromatase (PPC) (0= Results : 18 (37%) of the 49 participants were premenopausal (median age 46 yrs). Summing across cell types, the global composite score showed increased aromatase IR on sections sampled from dense vs. non-dense regions (β=5.3,p 1% stromal cells on each section, there was evidence for increased IR on dense sections as indicated by the greater PPCs (β=0.9), relative intensity (β=0.7) and composite score (β=2.7)(p9s 1% normal ductal epithelium in both dense and non-dense sections, there was a greater composite score (β=1.4,p=0.004) for cells on dense sections although differences for PPC (β=0.3,p=0.11) and relative intensity (β=0.3,p=0.09) did not reach statistical significance. No differences were seen in IR for adipocytes from the two density regions (46 women). Findings were unchanged with adjustment for covariates, including proportions of each cell type per section.
 Conclusions : There is strong evidence for increased aromatase expression in the stromal and normal ductal epithelium of dense vs. non-dense tissue. These results support ongoing research into mammographic density as a biomarker of effect of aromatase inhibitors. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 4033.

Human sulfotransferase (SULT) 1A1 pharmacogenetics: Intragene haplotype, breast cancer and mammographic breast density

SULT1A1 catalyzes the sulfate conjugation of estrogens and many drugs. A common ORF SNP (Arg213His, SULT1A1*2) is associated with low SULT1A1 activity, and 2 additional SNPs, C(‐624)G and G(‐396)A, are associated with decreased transcription.