Serghei Malkov

Volume of Mammographic Density and Risk of Breast Cancer

Background: Assessing the volume of mammographic density might more accurately reflect the amount of breast volume at risk of malignant transformation and provide a stronger indication of risk of breast cancer than methods based on qualitative scores or dense breast area. Methods: We prospectively collected mammograms for women undergoing screening mammography. We determined the diagnosis of subsequent invasive or ductal carcinoma in situ for 275 cases, selected 825 controls matched for age, ethnicity, and mammography system, and assessed three measures of breast density: percent dense area, fibroglandular volume, and percent fibroglandular volume. Results: After adjustment for familial breast cancer history, body mass index, history of breast biopsy, and age at first live birth, the ORs for breast cancer risk in the highest versus lowest measurement quintiles were 2.5 (95% CI: 1.5–4.3) for percent dense area, 2.9 (95% CI: 1.7–4.9) for fibroglandular volume, and 4.1 (95% CI: 2.3–7.2) for percent fibroglandular volume. Net reclassification indexes for density measures plus risk factors versus risk factors alone were 9.6% (P = 0.07) for percent dense area, 21.1% (P = 0.0001) for fibroglandular volume, and 14.8% (P = 0.004) for percent fibroglandular volume. Fibroglandular volume improved the categorical risk classification of 1 in 5 women for both women with and without breast cancer. Conclusion: Volumetric measures of breast density are more accurate predictors of breast cancer risk than risk factors alone and than percent dense area. Impact: Risk models including dense fibroglandular volume may more accurately predict breast cancer risk than current risk models. Cancer Epidemiol Biomarkers Prev; 20(7); 1473–82. ©2011 AACR.

Agreement of mammographic measures of volumetric breast density to MRI.

Background Clinical scores of mammographic breast density are highly subjective. Automated technologies for mammography exist to quantify breast density objectively, but the technique that most accurately measures the quantity of breast fibroglandular tissue is not known. Purpose To compare the agreement of three automated mammographic techniques for measuring volumetric breast density with a quantitative volumetric MRI-based technique in a screening population. Materials and Methods Women were selected from the UCSF Medical Center screening population that had received both a screening MRI and digital mammogram within one year of each other, had Breast Imaging Reporting and Data System (BI-RADS) assessments of normal or benign finding, and no history of breast cancer or surgery. Agreement was assessed of three mammographic techniques (Single-energy X-ray Absorptiometry [SXA], Quantra, and Volpara) with MRI for percent fibroglandular tissue volume, absolute fibroglandular tissue volume, and total breast volume. Results Among 99 women, the automated mammographic density techniques were correlated with MRI measures with R2 values ranging from 0.40 (log fibroglandular volume) to 0.91 (total breast volume). Substantial agreement measured by kappa statistic was found between all percent fibroglandular tissue measures (0.72 to 0.63), but only moderate agreement for log fibroglandular volumes. The kappa statistics for all percent density measures were highest in the comparisons of the SXA and MRI results. The largest error source between MRI and the mammography techniques was found to be differences in measures of total breast volume. Conclusion Automated volumetric fibroglandular tissue measures from screening digital mammograms were in substantial agreement with MRI and if associated with breast cancer could be used in clinical practice to enhance risk assessment and prevention.

Single x-ray absorptiometry method for the quantitative mammographic measure of fibroglandular tissue volume

PURPOSE This study describes the design and characteristics of a highly accurate, precise, and automated single-energy method to quantify percent fibroglandular tissue volume (%FGV) and fibroglandular tissue volume (FGV) using digital screening mammography. METHODS The method uses a breast tissue-equivalent phantom in the unused portion of the mammogram as a reference to estimate breast composition. The phantom is used to calculate breast thickness and composition for each image regardless of x-ray technique or the presence of paddle tilt. The phantom adheres to the top of the mammographic compression paddle and stays in place for both craniocaudal and mediolateral oblique screening views. We describe the automated method to identify the phantom and paddle orientation with a three-dimensional reconstruction least-squares technique. A series of test phantoms, with a breast thickness range of 0.5-8 cm and a %FGV of 0%-100%, were made to test the accuracy and precision of the technique. RESULTS Using test phantoms, the estimated repeatability standard deviation equaled 2%, with a +/-2% accuracy for the entire thickness and density ranges. Without correction, paddle tilt was found to create large errors in the measured density values of up to 7%/mm difference from actual breast thickness. This new density measurement is stable over time, with no significant drifts in calibration noted during a four-month period. Comparisons of %FGV to mammographic percent density and left to right breast %FGV were highly correlated (r=0.83 and 0.94, respectively). CONCLUSIONS An automated method for quantifying fibroglandular tissue volume has been developed. It exhibited good accuracy and precision for a broad range of breast thicknesses, paddle tilt angles, and %FGV values. Clinical testing showed high correlation to mammographic density and between left and right breasts.

Compositional breast imaging using a dual-energy mammography protocol.

PURPOSE Mammography has a low sensitivity in dense breasts due to low contrast between malignant and normal tissue confounded by the predominant water density of the breast. Water is found in both adipose and fibroglandular tissue and constitutes most of the mass of a breast. However, significant protein mass is mainly found in the fibroglandular tissue where most cancers originate. If the protein compartment in a mammogram could be imaged without the influence of water, the sensitivity and specificity of the mammogram may be improved. This article describes a novel approach to dual-energy mammography, full-field digital compositional mammography (FFDCM), which can independently image the three compositional components of breast tissue: water, lipid, and protein. METHODS Dual-energy attenuation and breast shape measures are used together to solve for the three compositional thicknesses. Dual-energy measurements were performed on breast-mimicking phantoms using a full-field digital mammography unit. The phantoms were made of materials shown to have similar x-ray attenuation properties of the compositional compartments. They were made of two main stacks of thicknesses around 2 and 4 cm. Twenty-six thickness and composition combinations were used to derive the compositional calibration using a least-squares fitting approach. RESULTS Very high accuracy was achieved with a simple cubic fitting function with root mean square errors of 0.023, 0.011, and 0.012 cm for the water, lipid, and protein thicknesses, respectively. The repeatability (percent coefficient of variation) of these measures was tested using sequential images and was found to be 0.5%, 0.5%, and 3.3% for water, lipid, and protein, respectively. However, swapping the location of the two stacks of the phantom on the imaging plate introduced further errors showing the need for more complete system uniformity corrections. Finally, a preliminary breast image is presented of each of the compositional compartments separately. CONCLUSIONS FFDCM has been derived and exhibited good compositional thickness accuracy on phantoms. Preliminary breast images demonstrated the feasibility of creating individual compositional diagnostic images in a clinical environment.

Comparison of Clinical and Automated Breast Density Measurements: Implications for Risk Prediction and Supplemental Screening

Purpose To compare the classification of breast density with two automated methods, Volpara (version 1.5.0; Matakina Technology, Wellington, New Zealand) and Quantra (version 2.0; Hologic, Bedford, Mass), with clinical Breast Imaging Reporting and Data System (BI-RADS) density classifications and to examine associations of these measures with breast cancer risk. Materials and Methods In this study, 1911 patients with breast cancer and 4170 control subjects matched for age, race, examination date, and mammography machine were evaluated. Participants underwent mammography at Mayo Clinic or one of four sites within the San Francisco Mammography Registry between 2006 and 2012 and provided informed consent or a waiver for research, in compliance with HIPAA regulations and institutional review board approval. Digital mammograms were retrieved a mean of 2.1 years (range, 6 months to 6 years) before cancer diagnosis, with the corresponding clinical BI-RADS density classifications, and Volpara and Quantra density estimates were generated. Agreement was assessed with weighted κ statistics among control subjects. Breast cancer associations were evaluated with conditional logistic regression, adjusted for age and body mass index. Odds ratios, C statistics, and 95% confidence intervals (CIs) were estimated. Results Agreement between clinical BI-RADS density classifications and Volpara and Quantra BI-RADS estimates was moderate, with κ values of 0.57 (95% CI: 0.55, 0.59) and 0.46 (95% CI: 0.44, 0.47), respectively. Differences of up to 14% in dense tissue classification were found, with Volpara classifying 51% of women as having dense breasts, Quantra classifying 37%, and clinical BI-RADS assessment used to classify 43%. Clinical and automated measures showed similar breast cancer associations; odds ratios for extremely dense breasts versus scattered fibroglandular densities were 1.8 (95% CI: 1.5, 2.2), 1.9 (95% CI: 1.5, 2.5), and 2.3 (95% CI: 1.9, 2.8) for Volpara, Quantra, and BI-RADS classifications, respectively. Clinical BI-RADS assessment showed better discrimination of case status (C = 0.60; 95% CI: 0.58, 0.61) than did Volpara (C = 0.58; 95% CI: 0.56, 0.59) and Quantra (C = 0.56; 95% CI: 0.54, 0.58) BI-RADS classifications. Conclusion Automated and clinical assessments of breast density are similarly associated with breast cancer risk but differ up to 14% in the classification of women with dense breasts. This could have substantial effects on clinical practice patterns. (©) RSNA, 2015 Online supplemental material is available for this article.

Hip Fractures Risk in Older Men and Women Associated With DXA‐Derived Measures of Thigh Subcutaneous Fat Thickness, Cross‐Sectional Muscle Area, and Muscle Density

Mid‐thigh cross‐sectional muscle area (CSA), muscle attenuation, and greater trochanter soft tissue thickness have been shown to be independent risk factors of hip fracture. Our aim was to determine whether muscle and adipose tissue measures derived from dual‐energy X‐ray absorptiometry (DXA) scans would have a similar risk association as those measured using other imaging methods. Using a case‐cohort study design, we identified 169 incident hip fracture cases over an average of 13.5 years among participants from the Health ABC Study, a prospective study of 3075 individuals initially aged 70 to 79 years. We modeled the thigh 3D geometry and compared DXA and computed tomography (CT) measures. DXA‐derived thigh CSA, muscle attenuation, and subcutaneous fat thickness were found to be highly correlated to their CT counterparts (Pearsons r = 0.82, 0.45, and 0.91, respectively; p < 0.05). The fracture risk of men and women were calculated separately. We found that decreased subcutaneous fat, CT thigh muscle attenuation, and appendicular lean mass by height squared (ALM/Ht2) were associated with fracture risk in men; hazard ratios (HR) = 1.44 (1.02, 2.02), 1.40 (1.05, 1.85), and 0.58 (0.36, 0.91), respectively, after adjusting for age, race, clinical site, body mass index (BMI), chronic disease, hip bone mineral density (BMD), self‐reported health, alcohol use, smoking status, education, physical activity, and cognitive function. In a similar model for women, only decreases in subcutaneous fat and DXA CSA were associated with hip fracture risk; HR = 1.39 (1.07, 1.82) and 0.78 (0.62, 0.97), respectively. Men with a high ALM/Ht2 and low subcutaneous fat thickness had greater than 8 times higher risk for hip fracture compared with those with low ALM/Ht2 and high subcutaneous fat. In women, ALM/Ht2 did not improve the model when subcutaneous fat was included. We conclude that the DXA‐derived subcutaneous fat thickness is a strong marker for hip fracture risk in both men and women, especially in men with high ALM/Ht2.

Comparison of breast density measured by dual energy X-ray absorptiometry with mammographic density among adult women in Hawaii

BACKGROUND While use of mammography is limited, due to concerns related to radiation exposure, dual energy X-ray absorptiometry (DXA), commonly available in medical care settings, is characterized by low radiation exposure. METHODS In the current paper, we compared breast density measured by DXA with mammographic density in 101 adult women who had a screening mammogram during the last 2 years. DXA scans of both breasts were taken using a clinical DXA system calibrated to measure breast density. The total projected breast area was manually delineated on each image and percent fibroglandular volume density (%FGV), absolute fibroglandular volume, total breast area and volume were computed. After digitizing mammographic films, total breast area, dense area, and percent density (PD) were estimated using computer-assisted mammographic density assessment. RESULTS Both DXA and mammographic measures showed high correlations between left and right breasts ranging from 0.85 to 0.98 (p<0.0001). Mean %FGV was 38.8±14.3%, and mean percent density was 31.9±18.2% for craniocaudal views and 28.3±16.2% for mediolateral views. The correlation between the two measures was 0.76 for both views (p<0.0001). Associations with common risk factors showed similar patterns for DXA and mammographic densities; in particular, the inverse associations with BMI and age at menarche were evident for both methods. Multilinear regression with stepwise selection indicated an explained variance of 0.56 for %FGV alone and of 0.58 for %FGV plus number of children. CONCLUSION Despite some differences in methodology, the current comparison suggests that DXA may provide a low-radiation option in evaluating breast density.

Breast Density Assessment in Adolescent Girls Using Dual-Energy X-ray Absorptiometry: A Feasibility Study

Breast density, the radiographically opaque fraction of the breast in a mammogram, is one of the strongest biomarkers of breast cancer risk. However, younger populations do not typically have mammograms due to radiation concerns. This study explored a commercially available dual-energy X-ray absorptiometer (DXA) system as a low-dose method to measure breast fibroglandular density in adolescent girls. Eighteen girls (13-14 years old) indicated their breast development according to Tanner and underwent three dedicated DXA scans, two of their left and one of their right breasts. Total projected breast area was manually delineated on each image and percent fibroglandular volume density (%FGV), absolute fibroglandular volume (FGV), total breast area, and volume were computed. It was possible to image breasts representing all five Tanner stages; %FGV ranged from 31.9% to 92.2% with a mean of 71.1 ± 14.8%, whereas FGV ranged from 80 to 270 cm3 with a mean of 168 ± 54 cm3. Left and right breast %FGV were highly correlated (rp = 0.97, P < 0.0001) and of the same magnitude (P = 0.18). However, left total volume and FGV were larger than the right by 38 cm3 (P = 0.04) and 19 cm3 (P = 0.02), respectively. Total volume and FGV increased by Tanner stage, whereas %FGV did not. Our method had excellent precision for %FGV and moderate precision for FGV (root mean square SDs of 2.4% and 16.6 cm3). These pilot data indicate that dedicated DXA breast scans may be useful in studies exploring breast density in girls. (Cancer Epidemiol Biomarkers Prev 2008;17(7):1709–13)

Relationship of Terminal Duct Lobular Unit Involution of the Breast with Area and Volume Mammographic Densities

Elevated mammographic density (MD) is an established breast cancer risk factor. Reduced involution of terminal duct lobular units (TDLU), the histologic source of most breast cancers, has been associated with higher MD and breast cancer risk. We investigated relationships of TDLU involution with area and volumetric MD, measured throughout the breast and surrounding biopsy targets (perilesional). Three measures inversely related to TDLU involution (TDLU count/mm2, median TDLU span, median acini count/TDLU) assessed in benign diagnostic biopsies from 348 women, ages 40–65, were related to MD area (quantified with thresholding software) and volume (assessed with a density phantom) by analysis of covariance, stratified by menopausal status and adjusted for confounders. Among premenopausal women, TDLU count was directly associated with percent perilesional MD (P trend = 0.03), but not with absolute dense area/volume. Greater TDLU span was associated with elevated percent dense area/volume (P trend<0.05) and absolute perilesional MD (P = 0.003). Acini count was directly associated with absolute perilesional MD (P = 0.02). Greater TDLU involution (all metrics) was associated with increased nondense area/volume (P trend ≤ 0.04). Among postmenopausal women, TDLU measures were not significantly associated with MD. Among premenopausal women, reduced TDLU involution was associated with higher area and volumetric MD, particularly in perilesional parenchyma. Data indicating that TDLU involution and MD are correlated markers of breast cancer risk suggest that associations of MD with breast cancer may partly reflect amounts of at-risk epithelium. If confirmed, these results could suggest a prevention paradigm based on enhancing TDLU involution and monitoring efficacy by assessing MD reduction. Cancer Prev Res; 9(2); 149–58. ©2015 AACR.

Circulating insulin-like growth factor-I, insulin-like growth factor binding protein-3 and terminal duct lobular unit involution of the breast: a cross-sectional study of women with benign breast disease

BackgroundTerminal duct lobular units (TDLUs) are the primary structures from which breast cancers and their precursors arise. Decreased age-related TDLU involution and elevated mammographic density are both correlated and independently associated with increased breast cancer risk, suggesting that these characteristics of breast parenchyma might be linked to a common factor. Given data suggesting that increased circulating levels of insulin-like growth factors (IGFs) factors are related to reduced TDLU involution and increased mammographic density, we assessed these relationships using validated quantitative methods in a cross-sectional study of women with benign breast disease.MethodsSerum IGF-I, IGFBP-3 and IGF-I:IGFBP-3 molar ratios were measured in 228 women, ages 40-64, who underwent diagnostic breast biopsies yielding benign diagnoses at University of Vermont affiliated centers. Biopsies were assessed for three separate measures inversely related to TDLU involution: numbers of TDLUs per unit of tissue area (“TDLU count”), median TDLU diameter (“TDLU span”), and number of acini per TDLU (“acini count”). Regression models, stratified by menopausal status and adjusted for potential confounders, were used to assess the associations of TDLU count, median TDLU span and median acini count per TDLU with tertiles of circulating IGFs. Given that mammographic density is associated with both IGF levels and breast cancer risk, we also stratified these associations by mammographic density.ResultsHigher IGF-I levels among postmenopausal women and an elevated IGF-I:IGFBP-3 ratio among all women were associated with higher TDLU counts, a marker of decreased lobular involution (P-trend = 0.009 and <0.0001, respectively); these associations were strongest among women with elevated mammographic density (P-interaction <0.01). Circulating IGF levels were not significantly associated with TDLU span or acini count per TDLU.ConclusionsThese results suggest that elevated IGF levels may define a sub-group of women with high mammographic density and limited TDLU involution, two markers that have been related to increased breast cancer risk. If confirmed in prospective studies with cancer endpoints, these data may suggest that evaluation of IGF signaling and its downstream effects may have value for risk prediction and suggest strategies for breast cancer chemoprevention through inhibition of the IGF system.