Trunk-to-leg volume and appendicular lean mass from a commercial 3-dimensional optical body scanner for disease risk identification.

BACKGROUND & AIMS: Body shape expressed as the trunk-to-leg volume ratio is associated with diabetes and mortality due to the associations between higher adiposity and lower lean mass with Metabolic Syndrome (MetS) risk. Reduced appendicular muscle mass is associated with malnutrition risk and age-related frailty, and is a risk factor for poor treatment outcomes related to MetS and other clinical conditions (e.g.; cancer). These measures are traditionally assessed by dual-energy X-ray absorptiometry (DXA), which can be difficult to access in clinical settings. The Shape Up! Adults trial (SUA) demonstrated the accuracy and precision of 3-dimensional optical imaging (3DO) for body composition as compared to DXA and other criterion measures. Here we assessed whether trunk-to-leg volume estimates derived from 3DO are associated with MetS risk in a similar way as when measured by DXA. We further explored if estimations of appendicular lean mass (ALM) could be made using 3DO to further improve the accessibility of measuring this important frailty and disease risk factor. METHODS: SUA recruited participants across sex, age (18-40, 40-60, >60 years), BMI (under, normal, overweight, obese), and race/ethnicity (non-Hispanic [NH] Black, NH White, Hispanic, Asian, Native Hawaiian/Pacific Islander) categories. Each participant had whole-body DXA and 3DO scans, and measures of cardiovascular health. The 3DO measures of trunk and leg volumes were calibrated to DXA to express equivalent trunk-to-leg volume ratios. We expressed each blood measure and overall MetS risk in quartile gradations of trunk-to-leg volume previously defined by National Health and Nutrition Examination Survey (NHANES). Finally, we utilized 3DO measures to estimate DXA ALM using ten-fold cross-validation of the entire dataset. RESULTS: Participants were 502 (273 female) adults, mean age = 46.0 ± 16.5y, BMI = 27.6 ± 7.1 kg/m2 and a mean DXA trunk-to-leg volume ratio of 1.47 ± 0.22 (females: 1.43 ± 0.23; males: 1.52 ± 0.20). After adjustments for age and sex, each standard deviation increase in trunk-to-leg volume by 3DO was associated with a 3.3 (95% odds ratio [OR] = 2.4-4.2) times greater risk of MetS, with individuals in the highest quartile of trunk-to-leg at 27.4 (95% CI: 9.0-53.1) times greater risk of MetS compared to the lowest quartile. Risks of elevated blood biomarkers as related to high 3DO trunk-to-leg volume ratios were similar to previously published comparisons using DXA trunk-to-leg volume ratios. Estimated ALM by 3DO was correlated to DXA (r2 = 0.96, root mean square error = 1.5 kg) using ten-fold cross-validation. CONCLUSION: Using thresholds of trunk-to-leg associated with MetS developed on a sample of US-representative adults, trunk-to-leg ratio by 3DO after adjustments for offsets showed significant associations to blood parameters and MetS risk. 3DO scans provide a precise and accurate estimation of ALM across the range of body sizes included in the study sample. The development of these additional measures improves the clinical utility of 3DO for the assessment of MetS risk as well as the identification of low muscle mass associated with poor cardiometabolic and functional health.

Prediction of future visceral adiposity and application to cancer research: The Multiethnic Cohort Study.

BACKGROUND: We previously developed a prediction score for MRI-quantified abdominal visceral adipose tissue (VAT) based on concurrent measurements of height, body mass index (BMI), and nine blood biomarkers, for optimal performance in five racial/ethnic groups. Here we evaluated the VAT score for prediction of future VAT and examined if enhancement with additional biomarkers, lifestyle behavior information, and medical history improves the prediction. METHODS: We examined 500 participants from the Multiethnic Cohort (MEC) with detailed data (age 50-66) collected 10 years prior to their MRI assessment of VAT. We generated three forecasted VAT prediction models: first by applying the original VAT equation to the past data on the predictors ("original"), second by refitting the past data on anthropometry and biomarkers ("refit"), and third by building a new prediction model based on the past data enhanced with lifestyle and medical history ("enhanced"). We compared the forecasted prediction scores to future VAT using the coefficient of determination (R2). In independent nested case-control data in MEC, we applied the concurrent and forecasted VAT models to assess association of the scores with subsequent incident breast cancer (950 pairs) and colorectal cancer (831 pairs). RESULTS: Compared to the VAT prediction by the concurrent VAT score (R2 = 0.70 in men, 0.68 in women), the forecasted original VAT score (R2 = 0.54, 0.48) performed better than past anthropometry alone (R2 = 0.47, 0.40) or two published scores (VAI, METS-VF). The forecasted refit (R2 = 0.61, 0.51) and enhanced (R2 = 0.62, 0.55) VAT scores each showed slight improvements. Similar to the concurrent VAT score, the forecasted VAT scores were associated with breast cancer, but not colorectal cancer. Both the refit score (adjusted OR for tertile 3 vs. 1 = 1.27; 95% CI: 1.00-1.62) and enhanced score (1.27; 0.99-1.62) were associated with breast cancer independently of BMI. CONCLUSIONS: Predicted VAT from midlife data can be used as a surrogate to assess the effect of VAT on incident diseases associated with obesity, as illustrated for postmenopausal breast cancer.

Advancing body composition assessment in patients with cancer: First comparisons of traditional versus multicompartment models.

BACKGROUND AND AIMS: Measurement of body composition using computed tomography (CT) scans may be a viable clinical tool for low muscle mass assessment in oncology. However, longitudinal assessments are often infeasible with CT. Clinically accessible body composition technologies can be used to track changes in fat-free mass (FFM) or muscle, though their accuracy may be impacted by cancer-related physiological changes. The purpose of this study was to examine the agreement among accessible body composition method with criterion methods for measures of whole-body FFM measurements and, when possible, muscle mass for the classification of low muscle in patients with cancer. METHODS: Patients with colorectal cancer were recruited to complete measures of whole-body DXA, air displacement plethysmography (ADP), and bioelectrical impedance analysis (BIA). These measures were used alone, or in combination to construct the criterion multicompartment (4C) mode for estimating FFM. Patients also underwent abdominal CT scans as part of routine clinical assessment. Agreement of each method with 4C model was analyzed using mean constant error (CE = criterion - alternative), linear regression including root mean square error (RMSE), Bland-Altman limits of agreement (LoA) and mean percentage difference (MPD). Additionally, appendicular lean soft tissue index (ALSTI) measured by DXA and predicted by CT were compared for the absolute agreement, while the ALSTI values and skeletal muscle index by CT were assessed for agreement on the classification of low muscle mass. RESULTS: Forty-five patients received all measures for the 4C model and 25 had measures within proximity of clinical CT measures. Compared to 4C, DXA outperformed ADP and BIA by showing the strongest overall agreement (CE = 1.96 kg, RMSE = 2.45 kg, MPD = 98.15 ± 2.38%), supporting its use for body composition assessment in patients with cancer. However, CT cutoffs for skeletal muscle index or CT-estimated ALSTI were lower than DXA ALSTI (average 1.0 ± 1.2 kg/m2) with 24.0% to 32.0% of patients having a different low muscle classification by CT when compared to DXA. CONCLUSIONS: Despite discrepancies between clinical body composition assessment and the criterion multicompartment model, DXA demonstrates the strongest agreement with 4C. Disagreement between DXA and CT for low muscle mass classification prompts further evaluation of the measures and cutoffs used with each technique. Multicompartment models may enhance our understanding of body composition variations at the individual patient level and improve the applicability of clinically accessible technologies for classification and monitoring change over time.

Time-specific impact of trace metals on breast density of adolescent girls in Santiago, Chile.

Whether trace metals modify breast density, the strongest predictor for breast cancer, during critical developmental stages such as puberty remains understudied. Our study prospectively evaluated the association between trace metals at Tanner breast stage B1 (n = 291) and at stages both B1 and B4 (n = 253) and breast density at 2 years post-menarche among Chilean girls from the Growth and Obesity Cohort Study. Dual-energy x-ray absorptiometry assessed the volume of dense breast tissue (absolute fibroglandular volume [FGV]) and percent breast density (%FGV). Urine trace metals included arsenic, barium, cadmium, cobalt, cesium, copper, magnesium, manganese, molybdenum, nickel, lead, antimony, selenium, tin, thallium, vanadium, and zinc. At B1, a doubling of thallium concentration resulted in 13.69 cm3 increase in absolute FGV (ß: 13.69, 95% confidence interval [CI]: 2.81, 24.52), while a doubling of lead concentration resulted in a 7.76 cm3 decrease in absolute FGV (ß: -7.76, 95%CI: -14.71, -0.73). At B4, a doubling of barium concentration was associated with a 10.06 cm3 increase (ß: 10.06, 95% CI: 1.44, 18.60), copper concentration with a 12.29 cm3 increase (ß: 12.29, 95% CI: 2.78, 21.56), lead concentration with a 9.86 cm3 increase (ß: 9.86, 95% CI: 0.73, 18.98), antimony concentration with a 12.97 cm3 increase (ß: 12.97, 95% CI: 1.98, 23.79) and vanadium concentration with a 13.14 cm3 increase in absolute FGV (ß: 13.14, 95% CI: 2.73, 23.58). Trace metals may affect pubertal breast density at varying developmental stages with implications for increased susceptibility for breast cancer.

The Associations between Intakes of One-Carbon Metabolism-Related Vitamins and Breast Density among Young Women.

BACKGROUND: Folate is the primary methyl donor and B vitamins are cofactors for one-carbon metabolism that maintain DNA integrity and epigenetic signatures implicated in carcinogenesis. Breast tissue is particularly susceptible to stimuli in early life. Only limited data are available on associations of one-carbon metabolism-related vitamin intake during youth and young adulthood with breast density, a strong risk factor for breast cancer. METHODS: Over 18 years in the DISC and DISC06 Follow-up Study, diets of 182 young women were assessed by three 24-hour recalls on five occasions at ages 8 to 18 years and once at 25 to 29 years. Multivariable-adjusted linear mixed-effects regression was used to examine associations of intakes of one-carbon metabolism-related vitamins with MRI-measured percent dense breast volume (%DBV) and absolute dense breast volume (ADBV) at ages 25 to 29 years. RESULTS: Folate intake in youth was inversely associated with %DBV (Ptrend = 0.006) and ADBV (Ptrend = 0.02). These inverse associations were observed with intake during post-, though not premenarche. In contrast, premenarche vitamin B2 intake was positively associated with ADBV (Ptrend < 0.001). Young adult folate and vitamin B6 intakes were inversely associated with %DBV (all Ptrend ≤ 0.04), whereas vitamins B6 and B12 were inversely associated with ADBV (all Ptrend ≤ 0.04). CONCLUSIONS: Among these DISC participants intakes of one-carbon metabolism-related vitamins were associated with breast density. Larger prospective studies among diverse populations are needed to replicate these findings. IMPACT: Our results suggest the importance of one-carbon metabolism-related vitamin intakes early in life with development of breast density and thereby potentially breast cancer risk later in life.

The association of a healthy lifestyle index and imaging-based body fat distribution with glycemic status and Type 2 diabetes in the Multi Ethnic Cohort: a cross-sectional analysis.

INTRODUCTION: As several behaviors captured by the Lifestyle Risk Factor Index (LSRI) are protective against Type 2 diabetes (T2D) and may affect body fat distribution, we examined its relation with both outcomes. METHODS: In a subset of the Multiethnic Cohort, participants from five ethnic groups (60-77 years) were assigned LSRI scores (one point each for consuming <1 (women)/<2 (men) alcoholic drinks/day, ≥1.5 physical activity hours/week, not smoking, and adhering to ≥3/7 dietary recommendations). All participants completed an extensive Quantitative Food Frequency Questionnaire to allow estimation of adherence to intake recommendations for fruits, vegetables, refined and whole grains, fish, processed and non-processed meat. Glycemic/T2D status was classified according to self-reports and fasting glucose. We estimated prevalence odds ratios (POR) of LSRI with glycemic/T2D status and DXA- and MRI-based body fat distribution using logistic regression. RESULTS: Of 1713 participants, 43% had normoglycemia, 30% Pre-T2D, 9% Undiagnosed T2D, and 18% T2D. Overall, 39% scored 0-2, 49% 3, and 12% 4 LSRI points. T2D prevalence was 55% (POR 0.45; 95% confidence intervals 0.27, 0.76) lower for 4 vs. 0-2 LSRI points with weaker associations for abnormal glycemic status. Despite the low adherence to dietary recommendations (22%), this was the only component related to lower T2D prevalence. The inverse LSRI-T2D association was only observed among Latinos and Japanese Americans in ethnic-specific models. Visceral fat measures were higher in T2D patients and attenuated the LSRI-T2D association. CONCLUSION: These findings support the role of a healthy lifestyle, especially diet, in T2D prevention with differences across ethnicity.

Accuracy and Precision of 3-dimensional Optical Imaging for Body Composition by Age, BMI, and Ethnicity.

BACKGROUND: The obesity epidemic brought a need for accessible methods to monitor body composition, as excess adiposity has been associated with cardiovascular disease, metabolic disorders, and some cancers. Recent 3-dimensional optical (3DO) imaging advancements have provided opportunities for assessing body composition. However, the accuracy and precision of an overall 3DO body composition model in specific subgroups are unknown. OBJECTIVES: This study aimed to evaluate 3DO's accuracy and precision by subgroups of age, body mass index, and ethnicity. METHODS: A cross-sectional analysis was performed using data from the Shape Up! Adults study. Each participant received duplicate 3DO and dual-energy X-ray absorptiometry (DXA) scans. 3DO meshes were digitally registered and reposed using Meshcapade. Principal component analysis was performed on 3DO meshes. The resulting principal components estimated DXA whole-body and regional body composition using stepwise forward linear regression with 5-fold cross-validation. Duplicate 3DO and DXA scans were used for test-retest precision. Student's t tests were performed between 3DO and DXA by subgroup to determine significant differences. RESULTS: Six hundred thirty-four participants (females = 346) had completed the study at the time of the analysis. 3DO total fat mass in the entire sample achieved R2 of 0.94 with root mean squared error (RMSE) of 2.91 kg compared to DXA in females and similarly in males. 3DO total fat mass achieved a % coefficient of variation (RMSE) of 1.76% (0.44 kg), whereas DXA was 0.98% (0.24 kg) in females and similarly in males. There were no mean differences for total fat, fat-free, percent fat, or visceral adipose tissue by age group (P > 0.068). However, there were mean differences for underweight, Asian, and Black females as well as Native Hawaiian or other Pacific Islanders (P < 0.038). CONCLUSIONS: A single 3DO body composition model produced accurate and precise body composition estimates that can be used on diverse populations. However, adjustments to specific subgroups may be warranted to improve the accuracy in those that had significant differences. This trial was registered at clinicaltrials.gov as NCT03637855 (Shape Up! Adults).

Automated body composition estimation from device-agnostic 3D optical scans in pediatric populations.

BACKGROUND: Excess adiposity in children is strongly correlated with obesity-related metabolic disease in adulthood, including diabetes, cardiovascular disease, and 13 types of cancer. Despite the many long-term health risks of childhood obesity, body mass index (BMI) Z-score is typically the only adiposity marker used in pediatric studies and clinical applications. The effects of regional adiposity are not captured in a single scalar measurement, and their effects on short- and long-term metabolic health are largely unknown. However, clinicians and researchers rarely deploy gold-standard methods for measuring compartmental fat such as magnetic resonance imaging (MRI) and dual X-ray absorptiometry (DXA) on children and adolescents due to cost or radiation concerns. Three-dimensional optical (3DO) scans are relatively inexpensive to obtain and use non-invasive and radiation-free imaging techniques to capture the external surface geometry of a patient's body. This 3D shape contains cues about the body composition that can be learned from a structured correlation between 3D body shape parameters and reference DXA scans obtained on a sample population. STUDY AIM: This study seeks to introduce a radiation-free, automated 3D optical imaging solution for monitoring body shape and composition in children aged 5-17. METHODS: We introduce an automated, linear learning method to predict total and regional body composition of children aged 5-17 from 3DO scans. We collected 145 male and 206 female 3DO scans on children between the ages of 5 and 17 with three scanners from independent manufacturers. We used an automated shape templating method first introduced on an adult population to fit a topologically consistent 60,000 vertex (60 k) mesh to 3DO scans of arbitrary scanning source and mesh topology. We constructed a parameterized body shape space using principal component analysis (PCA) and estimated a regression matrix between the shape parameters and their associated DXA measurements. We automatically fit scans of 30 male and 38 female participants from a held-out test set and predicted 12 body composition measurements. RESULTS: The coefficient of determination (R2) between 3DO predicted body composition and DXA measurements was at least 0.85 for all measurements with the exception of visceral fat on 3D scan predictions. Precision error was 1-4 times larger than that of DXA. No predicted variable was significantly different from DXA measurement except for male trunk lean mass. CONCLUSION: Optical imaging can quickly, safely, and inexpensively estimate regional body composition in children aged 5-17. Frequent repeat measurements can be taken to chart changes in body adiposity over time without risk of radiation overexposure.

A comparison of various methods for measuring breast density and breast tissue composition in adolescent girls and women.

This study compared different approaches to measuring breast density and breast tissue composition (BTC) in adolescent girls (n = 42, aged 14-16 years) and their mothers (n = 39, aged 36-61 years) from a cohort in Santiago, Chile. Optical spectroscopy (OS) was used to measure collagen, water, and lipid concentrations, which were combined into a percent breast density index (%BDI). A clinical dual-energy X-ray absorptiometry (DXA) system calibrated to measure breast density provided percent fibroglandular volume (%FGV) from manually delineated images. After digitizing mammogram films, the percent mammographic breast density (%MBD) was measured using computer-assisted software. Partial correlation coefficients (rpartial) were used to evaluate associations between breast density measures and BTC from these three different measurement approaches, adjusting for age and body mass index. %BDI from OS was associated with %FGV from DXA in adolescent girls (rpartial = 0.46, p-value = 0.003), but not in mothers (rpartial = 0.17, p-value = 0.32). In mothers, %FGV from DXA was associated with %MBD from mammograms (rpartial = 0.60, p-value < 0.001). These findings suggest that data from OS, DXA, and mammograms provide related but distinct information about breast density and BTC. Future studies should explore how the information provided by these different devices can be used for breast cancer risk prediction in cohorts of adolescent girls and women.

Habitual Phytoestrogen Intake Is Associated with Breast Composition in Girls at 2 Years after Menarche Onset.

BACKGROUND: High phytoestrogen intake during adolescence is associated with a reduced risk of breast cancer. Breast density (BD) is a strong predictor of breast cancer and can be considered an early marker. We aim to assess the association between the mean habitual intake of isoflavones, lignans, and total phytoestrogens intake during puberty until 2 years after menarche onset and absolute fibroglandular volume (AFGV) and percentage of fibroglandular volume (%FGV) in Hispanic girls at the end of puberty. METHODS: Longitudinal study set up in the Growth and Obesity Chilean Cohort Study (GOCS). We included 329 girls with dietary data (multiple 24-hours recalls) from puberty until 2 years after menarche onset (81% had 2-4 recalls). Two international datasets were used to estimate isoflavones, lignans, and total phytoestrogens in the diet. Breast composition was measured by dual energy X-ray absorptiometry at 2 years after menarche. Multiple linear regression models were used to assess the association between isoflavones, lignans, and total phytoestrogens intake and AFGV and %FGV. RESULTS: The average total phytoestrogen intake was 1 mg/day and %FGV was 50.7% (SD = 15.2) and AFGV 218.8 cm3 (SD = 79.3). An inverse association was found between consumption of isoflavones and AFGV, as well as, with total phytoestrogens [Q4 vs. Q1 adjusted model ß = -49.2 cm3; 95% CI (-85.5 to -13.0)]. CONCLUSIONS: Girls with a higher intake of total phytoestrogens and isoflavones during puberty until 2 years after menarche onset had significantly lower AFGV. IMPACT: Although the intake of phytoestrogens is low in Western populations, higher consumption of them during a critical period of life like puberty could be beneficial to reduce breast cancer during adulthood.

Technical note: Low clinical efficacy, but good acceptability of a point-of-care electronic palpation device for breast cancer screening for a lower middle-income environment.

BACKGROUND: Late-stage breast cancer rates in the Pacific where mammography services are limited are exceedingly high: Marshall Islands (61%), Palau (94%), and Samoa (79%). Due to the limited medical resources in these areas an alternative accessible technology is needed. The iBreast Exam (iBE) is a point-of-care electronic palpitation device that has a reported sensitivity of 86%. However, little is known about the performance and acceptability of this device for women in the Pacific. METHODS: A total of 39 women (ages 42-73 years) were recruited in Guam with 19 women having a mammogram requiring biopsy (Breast Imaging-Reporting and Data System [BI-RADS] category 4 or above) and 20 women with a negative screening mammogram before the study visit. Participants received an iBE exam and completed a 26-item breast health questionnaire to evaluate the iBE. Furthermore, the performance characteristics of the iBE were tested using gelatin breast phantoms in terms of tumor size, tumor depth, and overall breast stiffness. RESULTS: The iBE had a sensitivity of 20% (two true positives to eight false negatives) and specificity of 92% (24 false positives to 278 true negatives) when analyzed based on the location of the tumor by quadrant. The iBE also had generally poor agreement according to a Cohen's kappa value of 0.068. The phantom experiments showed that the iBE can detect tumors as deep as 2.5 cm, but only if the lesion is greater than 8 mm in diameter. However, the iBE did demonstrate acceptability; 67% of the women reported that they had high trust in iBE as an early detection device. CONCLUSIONS: The iBE had generally poor sensitivity and specificity when tested in a clinical setting which does not allow its use as a screening tool. IMPACT: This study demonstrates the need for an alternative screening method other than electronic palpation for lower-middle-income areas.

Changes in Bone Mineral Density Following Conventional Oral Phosphonate Treatment of Hypophosphatemic Osteomalacia: A Non-Randomized Controlled Study.

PURPOSE: There are limited clinical studies aimed at solving the problem of the efficiency of conventional treatment with oral phosphate and calcitriol in adults with hypophosphatemic osteomalacia (HO). In addition, there still had no good non-hazardous markers to evaluate the severity of bone loss of osteomalacia before and after treatment. Therefore, the purpose of this study was to assess the efficacy of conventional treatment with a self-blended phosphate supplementation and calcitriol on patients with HO and whether bone mineral density (BMD) can be helpful for monitoring the efficacy. PATIENTS AND METHODS: A total of 21 HO patients and 105 healthy controls were enrolled. All patients were tested for serum biomarkers and BMD of the lumbar spine (L1-L4), femoral neck, and total left hip. After three years of treatment, 11 of 21 HO patients were recalled for BMD measurement. According to the administration of drugs, HO patients with calcium and calcitriol were divided into three phosphate treatment groups: patients in group A (n = 3) received continuous phosphate supplementation, patients in group B (n = 5) received intermittent phosphate supplementation and patients in group C (n = 3) received no phosphate supplementation. RESULTS: The diagnoses of 21 HO patients were 5 cases of hereditary hypophosphatemic rickets, 4 cases of Fanconi syndrome with the features of renal tubular acidosis and vitamin D deficiency, and 12 cases of hereditary vitamin D abnormality. The average initial serum phosphorus level of the patient group was approximately 50% lower than that of the control group. Lower BMD was significantly observed in the HO group than the control group at the lumbar spine and total hip. Continuous treatment with the phosphate supplement could increase BMD in the lumbar spine and total hip by 33.4-52.3% and in the femoral neck increased by 43.2-79.3% compared with baseline, and the effect appears to be continued once treatment is discontinued. CONCLUSION: These findings suggest that conventional therapy can improve bone mineral defects in patients with HO, especially in the femoral neck. Detection of BMD in HO patients is a good tool to assess the extent of bone defects and the therapeutic effect. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR-OOC-16010095. Registered 7 December 2016. Retrospectively registered.

Deep Learning Predicts Interval and Screening-detected Cancer from Screening Mammograms: A Case-Case-Control Study in 6369 Women.

Background The ability of deep learning (DL) models to classify women as at risk for either screening mammography-detected or interval cancer (not detected at mammography) has not yet been explored in the literature. Purpose To examine the ability of DL models to estimate the risk of interval and screening-detected breast cancers with and without clinical risk factors. Materials and Methods This study was performed on 25 096 digital screening mammograms obtained from January 2006 to December 2013. The mammograms were obtained in 6369 women without breast cancer, 1609 of whom developed screening-detected breast cancer and 351 of whom developed interval invasive breast cancer. A DL model was trained on the negative mammograms to classify women into those who did not develop cancer and those who developed screening-detected cancer or interval invasive cancer. Model effectiveness was evaluated as a matched concordance statistic (C statistic) in a held-out 26% (1669 of 6369) test set of the mammograms. Results The C statistics and odds ratios for comparing patients with screening-detected cancer versus matched controls were 0.66 (95% CI: 0.63, 0.69) and 1.25 (95% CI: 1.17, 1.33), respectively, for the DL model, 0.62 (95% CI: 0.59, 0.65) and 2.14 (95% CI: 1.32, 3.45) for the clinical risk factors with the Breast Imaging Reporting and Data System (BI-RADS) density model, and 0.66 (95% CI: 0.63, 0.69) and 1.21 (95% CI: 1.13, 1.30) for the combined DL and clinical risk factors model. For comparing patients with interval cancer versus controls, the C statistics and odds ratios were 0.64 (95% CI: 0.58, 0.71) and 1.26 (95% CI: 1.10, 1.45), respectively, for the DL model, 0.71 (95% CI: 0.65, 0.77) and 7.25 (95% CI: 2.94, 17.9) for the risk factors with BI-RADS density (b rated vs non-b rated) model, and 0.72 (95% CI: 0.66, 0.78) and 1.10 (95% CI: 0.94, 1.29) for the combined DL and clinical risk factors model. The P values between the DL, BI-RADS, and combined model's ability to detect screen and interval cancer were .99, .002, and .03, respectively. Conclusion The deep learning model outperformed in determining screening-detected cancer risk but underperformed for interval cancer risk when compared with clinical risk factors including breast density. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Bae and Kim in this issue.

Associations of the gut microbiome with hepatic adiposity in the Multiethnic Cohort Adiposity Phenotype Study.

Nonalcoholic fatty liver disease (NAFLD) is a risk factor for liver cancer and prevalence varies by ethnicity. Along with genetic and lifestyle factors, the gut microbiome (GM) may contribute to NAFLD and its progression to advanced liver disease. Our cross-sectional analysis assessed the association of the GM with hepatic adiposity among African American, Japanese American, White, Latino, and Native Hawaiian participants in the Multiethnic Cohort. We used MRI to measure liver fat and determine nonalcoholic fatty liver disease (NAFLD) status (n = 511 cases) in 1,544 participants, aged 60-77 years, with 12-53% overall adiposity (BMI of 17.8-46.2 kg/m2). The GM was measured by 16S rRNA gene sequencing and, on a subset, by metagenomic sequencing. Alpha diversity was lower overall with NAFLD and in certain ethnicities (African Americans, Whites, and Latinos). In models regressing genus on NAFLD status, 62 of 149 genera (40%) exhibited a significant interaction between NAFLD and ethnicity stratified analysis found 69 genera significantly associated with NAFLD in at least one ethnic group. No single genus was significantly associated with NAFLD across all ethnicities. In contrast, the same bacterial metabolic pathways were over-represented in participants with NAFLD regardless of ethnicity. Imputed secondary bile acid and carbohydrate pathways were associated with NAFLD, the latter of which was corroborated by metagenomics, although different genera in different ethnicities were associated with these pathways. Overall, we found that NAFLD was associated with altered bacterial composition and metabolism, and that bacterial endotoxin, assessed by plasma lipopolysaccharide binding protein (LBP), may mediate liver fat-associated systemic inflammation in a manner that seems to vary by ethnicity.

Biomarker-based visceral adiposity score and incident type 2 diabetes in the multiethnic cohort.

PURPOSE: Visceral adipose tissue (VAT) may be more important than subcutaneous fat in type 2 diabetes (T2D) etiology. We examined a VAT score developed in reference to MRI measurement of VAT in the Multiethnic Cohort (MEC) as a risk factor for incident T2D. METHODS: Two nested case-control studies of cancer allowed calculation of the VAT score based on anthropometric measures and 8 biomarkers among 2,556 participants without T2D. Incident cases were identified from Medicare linkages and self-reports after blood draws in 2001-2006. Cox regression with age as time metric was applied to estimate the association of the VAT score with T2D. RESULTS: During 10.1 ± 2.4 years, 355 incident T2D cases were identified. VAT scores were higher in T2D cases than among those without disease (5.06±0.43 vs. 4.95±0.41; P<0.0001) and significantly associated with T2D (HR = 2.70; 95%CI 1.60, 4.58 per unit) with similar values in men (HR = 2.99; 95%CI 1.03, 8.73) and women (HR = 2.61; 95%CI 1.39, 4.91). A significant association was observed in all five ethnic groups but only statistically significant among Japanese Americans (HR = 6.24; 95%CI 2.34, 16.68). CONCLUSION: These findings support that VAT as estimated by a biomarker-based score predicts T2D incidence beyond BMI in particular among older adults of Japanese ancestry.

Association of Daily Alcohol Intake, Volumetric Breast Density, and Breast Cancer Risk.

High alcohol intake and breast density increase breast cancer (BC) risk, but their interrelationship is unknown. We examined whether volumetric density modifies and/or mediates the alcohol-BC association. BC cases (n = 2233) diagnosed from 2006 to 2013 in the San Francisco Bay area had screening mammograms 6 or more months before diagnosis; controls (n = 4562) were matched on age, mammogram date, race or ethnicity, facility, and mammography machine. Logistic regression was used to estimate alcohol-BC associations adjusted for age, body mass index, and menopause; interaction terms assessed modification. Percent mediation was quantified as the ratio of log (odds ratios [ORs]) from models with and without density measures. Alcohol consumption was associated with increased BC risk (2-sided P trend = .004), as were volumetric percent density (OR = 1.45 per SD, 95% confidence interval [CI] = 1.36 to 1.56) and dense volume (OR = 1.30, 95% CI = 1.24 to 1.37). Breast density did not modify the alcohol-BC association (2-sided P > .10 for all). Dense volume mediated 25.0% (95% CI = 5.5% to 44.4%) of the alcohol-BC association (2-sided P = .01), suggesting alcohol may partially increase BC risk by increasing fibroglandular tissue.

Dual-energy three-compartment breast imaging for compositional biomarkers to improve detection of malignant lesions.

Background: While breast imaging such as full-field digital mammography and digital breast tomosynthesis have helped to reduced breast cancer mortality, issues with low specificity exist resulting in unnecessary biopsies. The fundamental information used in diagnostic decisions are primarily based in lesion morphology. We explore a dual-energy compositional breast imaging technique known as three-compartment breast (3CB) to show how the addition of compositional information improves malignancy detection. Methods: Women who presented with Breast Imaging-Reporting and Data System (BI-RADS) diagnostic categories 4 or 5 and who were scheduled for breast biopsies were consecutively recruited for both standard mammography and 3CB imaging. Computer-aided detection (CAD) software was used to assign a morphology-based prediction of malignancy for all biopsied lesions. Compositional signatures for all lesions were calculated using 3CB imaging and a neural network evaluated CAD predictions with composition to predict a new probability of malignancy. CAD and neural network predictions were compared to the biopsy pathology. Results: The addition of 3CB compositional information to CAD improves malignancy predictions resulting in an area under the receiver operating characteristic curve (AUC) of 0.81 (confidence interval (CI) of 0.74-0.88) on a held-out test set, while CAD software alone achieves an AUC of 0.69 (CI 0.60-0.78). We also identify that invasive breast cancers have a unique compositional signature characterized by reduced lipid content and increased water and protein content when compared to surrounding tissues. Conclusion: Clinically, 3CB may potentially provide increased accuracy in predicting malignancy and a feasible avenue to explore compositional breast imaging biomarkers.

Myosteatosis in the Context of Skeletal Muscle Function Deficit: An Interdisciplinary Workshop at the National Institute on Aging.

Skeletal muscle fat infiltration (known as myosteatosis) is an ectopic fat depot that increases with aging and is recognized to negatively correlate with muscle mass, strength, and mobility and disrupt metabolism (insulin resistance, diabetes). An interdisciplinary workshop convened by the National Institute on Aging Division of Geriatrics and Clinical Gerontology on September 2018, discussed myosteatosis in the context of skeletal muscle function deficit (SMFD). Its purpose was to gain a better understanding of the roles of myosteatosis in aging muscles and metabolic disease, particularly its potential determinants and clinical consequences, and ways of properly assessing it. Special attention was given to functional status and standardization of measures of body composition (including the value of D3-creatine dilution method) and imaging approaches [including ways to better use dual-energy X-ray absorptiometry (DXA) through the shape and appearance modeling] to assess lean mass, sarcopenia, and myosteatosis. The workshop convened innovative new areas of scientific relevance to light such as the effect of circadian rhythms and clock disruption in skeletal muscle structure, function, metabolism, and potential contribution to increased myosteatosis. A muscle-bone interaction perspective compared mechanisms associated with myosteatosis and bone marrow adiposity. Potential preventive and therapeutic approaches highlighted ongoing work on physical activity, myostatin treatment, and calorie restriction. Myosteatosis' impact on cancer survivors raised new possibilities to identify its role and to engage in cross-disciplinary collaboration. A wide range of research opportunities and challenges in planning for the most appropriate study design, interpretation, and translation of findings into clinical practice were discussed and are presented here.

Stiff stroma increases breast cancer risk by inducing the oncogene ZNF217.

Women with dense breasts have an increased lifetime risk of malignancy that has been attributed to a higher epithelial density. Quantitative proteomics, collagen analysis, and mechanical measurements in normal tissue revealed that stroma in the high-density breast contains more oriented, fibrillar collagen that is stiffer and correlates with higher epithelial cell density. microRNA (miR) profiling of breast tissue identified miR-203 as a matrix stiffness-repressed transcript that is downregulated by collagen density and reduced in the breast epithelium of women with high mammographic density. Culture studies demonstrated that ZNF217 mediates a matrix stiffness- and collagen density-induced increase in Akt activity and mammary epithelial cell proliferation. Manipulation of the epithelium in a mouse model of mammographic density supported a causal relationship between stromal stiffness, reduced miR-203, higher levels of the murine homolog Zfp217, and increased Akt activity and mammary epithelial proliferation. ZNF217 was also increased in the normal breast epithelium of women with high mammographic density, correlated positively with epithelial proliferation and density, and inversely with miR-203. The findings identify ZNF217 as a potential target toward which preexisting therapies, such as the Akt inhibitor triciribine, could be used as a chemopreventive agent to reduce cancer risk in women with high mammographic density.

Circulating Biomarker Score for Visceral Fat and Risks of Incident Colorectal and Postmenopausal Breast Cancer: The Multiethnic Cohort Adiposity Phenotype Study.

BACKGROUND: Visceral adipose tissue (VAT) may play a greater role than subcutaneous fat in increasing cancer risk but is poorly estimated in epidemiologic studies. METHODS: We developed a VAT prediction score by regression equations averaged across 100 least absolute shrinkage and selection operator models in a cross-sectional study of 1,801 older adults in the Multiethnic Cohort (MEC). The score was then used as proxy for VAT in case-control studies of postmenopausal breast (950 case-control pairs) and colorectal (831 case-control pairs) cancer in an independent sample in MEC. Abdominal MRI-derived VAT; circulating biomarkers of metabolic, hormonal, and inflammation dysfunctions; and ORs for incident cancer adjusted for BMI and other risk factors were assessed. RESULTS: The final score, composed of nine biomarkers, BMI, and height, explained 11% and 15% more of the variance in VAT than BMI alone in men and women, respectively. The area under the receiver operator curve for VAT >150 cm2 was 0.90 in men and 0.86 in women. The VAT score was associated with risk of breast cancer [OR (95% confidence interval [CI]) by increasing tertiles: 1.00, 1.09 (0.86-1.39), 1.48 (1.16-1.89); P trend = 0.002] but not with colorectal cancer (P = 0.84), although an association [1.00, 0.98 (0.68-1.39), 1.24 (0.88-1.76); P trend = 0.08] was suggested for this cancer after excluding cases that occurred within 7 years of blood draw (P heterogeneity = 0.06). CONCLUSIONS: The VAT score predicted risks of postmenopausal breast cancer and can be used for risk assessment in diverse populations. IMPACT: These findings provide specific evidence for a role of VAT in breast cancer.