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Similarity of fibroglandular breast tissue content measured from magnetic resonance and mammographic images and by a mathematical algorithm.

ABSTRACT: Women with high breast density (BD) have a 4- to 6-fold greater risk for breast cancer than women with low BD. We found that BD can be easily computed from a mathematical algorithm using routine mammographic imaging data or by a curve-fitting algorithm using fat and nonfat suppression magnetic resonance imaging (MRI) data. These BD measures in a strictly defined group of premenopausal women providing both mammographic and breast MRI images were predicted as well by the same set of strong predictor variables as were measures from a published laborious histogram segmentation method and a full field digital mammographic unit in multivariate regression models. We also found that the number of completed pregnancies, C-reactive protein, aspartate aminotransferase, and progesterone were more strongly associated with amounts of glandular tissue than adipose tissue, while fat body mass, alanine aminotransferase, and insulin like growth factor-II appear to be more associated with the amount of breast adipose tissue. Our results show that methods of breast imaging and modalities for estimating the amount of glandular tissue have no effects on the strength of these predictors of BD. Thus, the more convenient mathematical algorithm and the safer MRI protocols may facilitate prospective measurements of BD.

SUBMITTER: Nayeem F

PROVIDER: S-EPMC4123610 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Similarity of fibroglandular breast tissue content measured from magnetic resonance and mammographic images and by a mathematical algorithm.

Nayeem Fatima F Ju Hyunsu H Brunder Donald G DG Nagamani Manubai M Anderson Karl E KE Khamapirad Tuenchit T Lu Lee-Jane W LJ

International journal of breast cancer 20140715

Women with high breast density (BD) have a 4- to 6-fold greater risk for breast cancer than women with low BD. We found that BD can be easily computed from a mathematical algorithm using routine mammographic imaging data or by a curve-fitting algorithm using fat and nonfat suppression magnetic resonance imaging (MRI) data. These BD measures in a strictly defined group of premenopausal women providing both mammographic and breast MRI images were predicted as well by the same set of strong predict ...[more]

PMID: 25132995

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Project description:Background & aimsPopulations consuming soy have reduced risk for breast cancer, but the mechanisms are unclear. We tested the hypothesis that soy isoflavones, which have ovarian hormone-like effects, can reduce fibroglandular breast tissue (FGBT, 'breast density'), a strong risk marker for breast cancer.MethodsPremenopausal women (age 30-42 years) were randomized to consume isoflavones (136.6 mg as aglycone equivalents, n = 99) or placebo (n = 98) for 5 days per week up to 2 years, and changes in breast composition measured by magnetic resonance imaging at baseline and yearly intervals were compared after square root transformation using linear mixed effects regression models.ResultsBy intention-to-treat analyses (n = 194), regression coefficients (β estimates) of the interaction of time and isoflavone treatment were -0.238 (P = 0.06) and -0.258 (P < 0.05) before and after BMI adjustment, respectively for FGBT, 0.620 (P < 0.05) and 0.248 (P = 0.160), respectively for fatty breast tissue (FBT), and -0.155 (P < 0.05) and -0.107 (P < 0.05), respectively for FGBT as percent of total breast (FGBT%). β Estimates for interaction of treatment with serum calcium were -2.705 for FBT, and 0.588 for FGBT% (P < 0.05, before but not after BMI adjustment). BMI (not transformed) was related to the interaction of treatment with time (β = 0.298) or with calcium (β = -1.248) (P < 0.05). Urinary excretion of isoflavones in adherent subjects (n = 135) significantly predicted these changes in breast composition. Based on the modeling results, after an average of 1.2, 2.2 and 3.3 years of supplementation, a mean decrease of FGBT by 5.3, 12.1, and 19.3 cc, respectively, and a mean decrease of FGBT% by 1.37, 2.43, and 3.50%, respectively, were estimated for isoflavone exposure compared to placebo treatment. Subjects with maximum isoflavone excretion were estimated to have 38 cc less FGBT (or ∼3.13% less FGBT%) than subjects without isoflavone excretion. Decrease in FGBT and FGBT% was more precise with daidzein than genistein.ConclusionsSoy isoflavones can induce a time- and concentration-dependent decrease in FGBT, a biomarker for breast cancer risk, in premenopausal women, and moderate effects of calcium on BMI and breast fat, suggesting a beneficial effect of soy consumption.Trial registrationwww.Clinicaltrialsgov identifier: NCT00204490.Trial registrationwww.Clinicaltrialsgov identifier: NCT00204490.

Project description:Quantitative analysis of craniofacial morphology is of interest to scholars working in a wide variety of disciplines, such as anthropology, developmental biology, and medicine. T1-weighted (anatomical) magnetic resonance images (MRI) provide excellent contrast between soft tissues. Given its three-dimensional nature, MRI represents an ideal imaging modality for the analysis of craniofacial structure in living individuals. Here we describe how T1-weighted MR images, acquired to examine brain anatomy, can also be used to analyze facial features. Using a sample of typically developing adolescents from the Saguenay Youth Study (N?=?597; 292 male, 305 female, ages: 12 to 18 years), we quantified inter-individual variations in craniofacial structure in two ways. First, we adapted existing nonlinear registration-based morphological techniques to generate iteratively a group-wise population average of craniofacial features. The nonlinear transformations were used to map the craniofacial structure of each individual to the population average. Using voxel-wise measures of expansion and contraction, we then examined the effects of sex and age on inter-individual variations in facial features. Second, we employed a landmark-based approach to quantify variations in face surfaces. This approach involves: (a) placing 56 landmarks (forehead, nose, lips, jaw-line, cheekbones, and eyes) on a surface representation of the MRI-based group average; (b) warping the landmarks to the individual faces using the inverse nonlinear transformation estimated for each person; and (3) using a principal components analysis (PCA) of the warped landmarks to identify facial features (i.e. clusters of landmarks) that vary in our sample in a correlated fashion. As with the voxel-wise analysis of the deformation fields, we examined the effects of sex and age on the PCA-derived spatial relationships between facial features. Both methods demonstrated significant sexual dimorphism in craniofacial structure in areas such as the chin, mandible, lips, and nose.

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Similarity of fibroglandular breast tissue content measured from magnetic resonance and mammographic images and by a mathematical algorithm.

Publications

Similarity of fibroglandular breast tissue content measured from magnetic resonance and mammographic images and by a mathematical algorithm.

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