Subcutaneous Adipose Tissue Area Research Articles

Visceral Adipose Tissue Reduction Measured by Deep Neural Network Architecture Improved Reflux Esophagitis Endoscopic Grade.

Visceral obesity is a risk factor for reflux esophagitis (RE). We investigated the risk of RE according to visceral adipose tissue (VAT) measured by deep neural network architecture using computed tomography (CT) and evaluated the longitudinal association between abdominal adipose tissue changes and the disease course of RE. Individuals receiving health checkups who underwent esophagogastroduodenoscopy (EGD) and abdominal CT at Seoul National University Healthcare System Gangnam Center between 2015 and 2016 were included. Visceral and subcutaneous adipose tissue areas and volumes were measured using a deep neural network architecture and CT. The association between the abdominal adipose tissue area and volume and the risk of RE was evaluated. Participants who underwent follow-up EGD and abdominal CT were selected; the effects of changes in abdominal adipose tissue area and volume on RE endoscopic grade were investigated using Cox proportional hazards regression. We enrolled 6,570 patients who underwent EGD and abdominal CT on the same day. RE was associated with male sex, hypertension, diabetes, excessive alcohol intake, current smoking status, and levels of physical activity. The VAT area and volume increased the risk of RE dose-dependently. A decreasing VAT volume was significantly associated with improvement in RE endoscopic grade (hazard ratio: 3.22, 95% confidence interval: 1.82-5.71). Changes in subcutaneous adipose tissue volume and the disease course of RE were not significantly correlated. Visceral obesity is strongly associated with RE. VAT volume reduction was prospectively associated with improvement in RE endoscopic grade dose-dependently. Visceral obesity is a potential target for RE treatment.

Abstract PO1-11-09: Body composition correlates with BMI and menopausal status in patients with breast cancer

Abstract Background: Obesity is associated with higher risk of breast cancer (BC)-related death, all-cause mortality, and recurrence. While used to estimate body fat, body mass index (BMI) is insensitive to body fat distribution and lean muscle mass. We hypothesized that BMI categories (BMI 18.5-24.9 [healthy], 25-29.9 [overweight], and ≥30 kg/m2 [obesity]) would not correlate with CT-derived body composition. Methods: We retrospectively identified 180 patients diagnosed with new or recurrent Stage I-IV BC who presented to Johns Hopkins from 2015-2018 and were part of an institutional database. We extracted demographics, diagnosis date, cancer characteristics, BMI, and CT abdomen pelvis scans from the medical record. Baseline BMI was defined as the closest measurement to diagnosis between 1 year prior and 1 month after diagnosis. Baseline CT was within 6 months of and closest to the baseline BMI date. Fully automated deep-learning algorithms identified L1 and performed muscle and adipose tissue segmentation and quantification. Body composition data included: cross-sectional areas (CSA) of subcutaneous, visceral, and total adipose tissue; the mean, median, and standard deviation of the average of the muscle attenuation (density); and the body wall musculature CSA. ANOVA tests assessed associations between body composition, BMI, and menopausal status. Results: Among 180 patients, 136 (76%) had early-stage BC, and 44 (24%) had metastatic BC. Most patients were women (98%) and non-Hispanic (94%). Patients identified as White (57%), Black (29%), Asian (6%), and Other Race (8%). Sixty percent were post-menopausal. Hormone receptor-positive, HER2-positive, and triple negative subtypes were 56%, 19% and 22%, respectively. At diagnosis, 24% had a healthy BMI while 36% and 41% had overweight and obesity, respectively. All body composition measures were significantly associated with BMI (Table 1). As BMI increased, the average body wall musculature and subcutaneous, visceral, and total adipose tissue CSAs increased while the average muscle attenuation decreased. Specifically, the average visceral adipose tissue CSAs were 2.7 and 4.0-fold larger for overweight and obesity compared to that of the healthy BMI group, respectively, while their average muscle attenuations were 62.4% and 40.6% of the healthy BMI group. Postmenopausal women had 1.5-fold higher visceral adipose tissue CSA and 44.7% less average muscle attenuation compared to premenopausal women. Conclusion: Body composition correlates with all BMI categories in primarily white, non-Hispanic women with breast cancer. As BMI increases, body composition changes reliably, with increased subcutaneous and visceral adipose tissue, increased muscle area, and decreased muscle density. Muscle density, not size/area, is more associated with muscle performance, which can relate to functional status and outcomes. Despite validity concerns, BMI is an accessible and economical surrogate for body adiposity in patients with breast cancer. Postmenopausal status was also associated with greater visceral and total adiposity and lower muscle density. Further investigation is needed to confirm these findings. Table 1: Correlation between body composition, BMI, and menopausal status in patients with breast cancer All measures of body composition were significantly associated with BMI. Visceral adipose tissue increased and muscle density decreased as BMI increased and with post-menopausal status. Citation Format: Terrence Tsou, Tingchang Wang, Amanda Blackford, Ronald Summers, Vered Stearns, Jennifer Sheng. Body composition correlates with BMI and menopausal status in patients with breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-11-09.

Development and validation of machine learning models and nomograms for predicting the surgical difficulty of laparoscopic resection in rectal cancer

BackgroundThe objective of this study is to develop and validate a machine learning (ML) prediction model for the assessment of laparoscopic total mesorectal excision (LaTME) surgery difficulty, as well as to identify independent risk factors that influence surgical difficulty. Establishing a nomogram aims to assist clinical practitioners in formulating more effective surgical plans before the procedure.MethodsThis study included 186 patients with rectal cancer who underwent LaTME from January 2018 to December 2020. They were divided into a training cohort (n = 131) versus a validation cohort (n = 55). The difficulty of LaTME was defined based on Escal’s et al. scoring criteria with modifications. We utilized Lasso regression to screen the preoperative clinical characteristic variables and intraoperative information most relevant to surgical difficulty for the development and validation of four ML models: logistic regression (LR), support vector machine (SVM), random forest (RF), and decision tree (DT). The performance of the model was assessed based on the area under the receiver operating characteristic curve(AUC), sensitivity, specificity, and accuracy. Logistic regression-based column-line plots were created to visualize the predictive model. Consistency statistics (C-statistic) and calibration curves were used to discriminate and calibrate the nomogram, respectively.ResultsIn the validation cohort, all four ML models demonstrate good performance: SVM AUC = 0.987, RF AUC = 0.953, LR AUC = 0.950, and DT AUC = 0.904. To enhance visual evaluation, a logistic regression-based nomogram has been established. Predictive factors included in the nomogram are body mass index (BMI), distance between the tumor to the dentate line ≤ 10 cm, radiodensity of visceral adipose tissue (VAT), area of subcutaneous adipose tissue (SAT), tumor diameter >3 cm, and comorbid hypertension.ConclusionIn this study, four ML models based on intraoperative and preoperative risk factors and a nomogram based on logistic regression may be of help to surgeons in evaluating the surgical difficulty before operation and adopting appropriate responses and surgical protocols.

Opportunistic CT for Prediction of Adverse Postoperative Events in Patients with Spinal Metastases.

The purpose of this study was to assess the value of body composition measures obtained from opportunistic abdominal computed tomography (CT) in order to predict hospital length of stay (LOS), 30-day postoperative complications, and reoperations in patients undergoing surgery for spinal metastases. 196 patients underwent CT of the abdomen within three months of surgery for spinal metastases. Automated body composition segmentation and quantifications of the cross-sectional areas (CSA) of abdominal visceral and subcutaneous adipose tissue and abdominal skeletal muscle was performed. From this, 31% (61) of patients had postoperative complications within 30 days, and 16% (31) of patients underwent reoperation. Lower muscle CSA was associated with increased postoperative complications within 30 days (OR [95% CI] = 0.99 [0.98-0.99], p = 0.03). Through multivariate analysis, it was found that lower muscle CSA was also associated with an increased postoperative complication rate after controlling for the albumin, ASIA score, previous systemic therapy, and thoracic metastases (OR [95% CI] = 0.99 [0.98-0.99], p = 0.047). LOS and reoperations were not associated with any body composition measures. Low muscle mass may serve as a biomarker for the prediction of complications in patients with spinal metastases. The routine assessment of muscle mass on opportunistic CTs may help to predict outcomes in these patients.

Lung CT harmonization of paired reconstruction kernel images using generative adversarial networks.

The kernel used in CT image reconstruction is an important factor that determines the texture of the CT image. Consistency of reconstruction kernel choice is important for quantitative CT-based assessment as kernel differences can lead to substantial shifts in measurements unrelated to underlying anatomical structures. In this study, we investigate kernel harmonization in a multi-vendor low-dose CT lung cancer screening cohort and evaluate our approach's validity in quantitative CT-based assessments. Using the National Lung Screening Trial, we identified CT scan pairs of the same sessions with one reconstructed from a soft tissue kernel and one from a hard kernel. In total, 1000 pairs of five different paired kernel types (200 each) were identified. We adopt the pix2pix architecture to train models for kernel conversion. Each model was trained on 100 pairs and evaluated on 100 withheld pairs. A total of 10 models were implemented. We evaluated the efficacy of kernel conversion based on image similarity metrics including root mean squared error (RMSE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM) as well as the capability of the models to reduce measurement shifts in quantitative emphysema and body composition measurements. Additionally, we study the reproducibility of standard radiomic features for all kernel pairs before and after harmonization. Our approach effectively converts CT images from one kernel to another in all paired kernel types, as indicated by the reduction in RMSE (p<0.05) and an increase in the PSNR (p<0.05) and SSIM (p<0.05) for both directions of conversion for all pair types. In addition, there is an increase in the agreement for percent emphysema, skeletal muscle area, and subcutaneous adipose tissue (SAT) area for both directions of conversion. Furthermore, radiomic features were reproducible when compared with the ground truth features. Kernel conversion using deep learning reduces measurement variation in percent emphysema, muscle area, and SAT area.

Influence of nutritional status and body composition on postoperative events and outcome in patients treated for primary localized retroperitoneal sarcoma.

Retroperitoneal sarcomas (RPS) are rare tumours of mesenchymal origin, commonly presented as a large tumour mass at time of diagnosis. We investigated the impact of body composition on outcome in patients operated on for primary localized RPS. We retrospectively analysed data for all patients operated on for primary RPS at our institution between 1999 and 2020. Preoperative skeletal muscle area (SMA), visceral and subcutaneous adipose tissue area (VAT and SAT) and muscle radiation attenuation (MRA) were calculated using computed tomography scans at the level of third lumbar vertebra. European Working Group on Sarcopenia in Older People (EWGSOP2) criteria were applied to define myopenia. Using maximum log-rank statistic method we determined the optimal cut-off values of body composition parameters. Myosteatosis was defined based on determined MRA cut-offs. In total 58 patient were eligible for the study. With a median follow-up of 116 months, the estimated 5-year overall survival (OS) and local-recurrence free survival (LRFS) were 66.8% and 77.6%, respectively. Patients with myopenia had significantly lower 5-year OS compared to non-myopenic (p = 0.009). Skeletal muscle index and subcutaneous adipose tissue index predicted LRFS on univariate analysis (p = 0.052 and p = 0.039, respectively). In multivariate analysis high visceral-to-subcutaneous adipose tissue area ratio (VSR) independently predicted higher postoperative complication rate (89.2% vs. 10.8%, p = 0.008). Myosteatosis was associated with higher postoperative morbidity. Myopenia affected survival, but not postoperative outcome in RPS. Visceral obesity, VSR (> 0.26) and myosteatosis were associated with higher postoperative morbidity. VSR was better prognostic factor than VAT in RPS.

Fully automated CT imaging biomarkers for opportunistic prediction of future hip fractures.

Assess automated CT imaging biomarkers in patients who went on to hip fracture, compared with controls. In this retrospective case-control study, 6926 total patients underwent initial abdominal CT over a 20-year interval at one institution. A total of 1308 patients (mean age at initial CT, 70.5 ± 12.0 years; 64.4% female) went on to hip fracture (mean time to fracture, 5.2 years); 5618 were controls (mean age 70.3 ± 12.0 years; 61.2% female; mean follow-up interval 7.6 years). Validated fully automated quantitative CT algorithms for trabecular bone attenuation (at L1), skeletal muscle attenuation (at L3), and subcutaneous adipose tissue area (SAT) (at L3) were applied to all scans. Hazard ratios (HRs) comparing highest to lowest risk quartiles and receiver operating characteristic (ROC) curve analysis including area under the curve (AUC) were derived. Hip fracture HRs (95% CI) were 3.18 (2.69-3.76) for low trabecular bone HU, 1.50 (1.28-1.75) for low muscle HU, and 2.18 (1.86-2.56) for low SAT. 10-year ROC AUC values for predicting hip fracture were 0.702, 0.603, and 0.603 for these CT-based biomarkers, respectively. Multivariate combinations of these biomarkers further improved predictive value; the 10-year ROC AUC combining bone/muscle/SAT was 0.733, while combining muscle/SAT was 0.686. Opportunistic use of automated CT bone, muscle, and fat measures can identify patients at higher risk for future hip fracture, regardless of the indication for CT imaging. CT data can be leveraged opportunistically for further patient evaluation, with early intervention as needed. These novel AI tools analyse CT data to determine a patient's future hip fracture risk.

Abdominal Body Composition Reference Ranges and Association With Chronic Conditions in an Age- and Sex-Stratified Representative Sample of a Geographically Defined American Population.

Body composition can be accurately quantified from abdominal computed tomography (CT) exams and is a predictor for the development of aging-related conditions and for mortality. However, reference ranges for CT-derived body composition measures of obesity, sarcopenia, and bone loss have yet to be defined in the general population. We identified a population-representative sample of 4900 persons aged 20 to 89 years who underwent an abdominal CT exam from 2010 to 2020. The sample was constructed using propensity score matching an age and sex stratified sample of persons residing in the 27-county region of Southern Minnesota and Western Wisconsin. The matching included race, ethnicity, education level, region of residence, and the presence of 20 chronic conditions. We used a validated deep learning based algorithm to calculate subcutaneous adipose tissue area, visceral adipose tissue area, skeletal muscle area, skeletal muscle density, vertebral bone area, and vertebral bone density from a CT abdominal section. We report CT-based body composition reference ranges on 4649 persons representative of our geographic region. Older age was associated with a decrease in skeletal muscle area and density, and an increase in visceral adiposity. All chronic conditions were associated with a statistically significant difference in at least one body composition biomarker. The presence of a chronic condition was generally associated with greater subcutaneous and visceral adiposity, and lower muscle density and vertebrae bone density. We report reference ranges for CT-based body composition biomarkers in a population-representative cohort of 4649 persons by age, sex, body mass index, and chronic conditions.

Association between type 2 diabetes mellitus and body composition based on MRI fat fraction mapping.

To explore the association between type 2 diabetes mellitus (T2DM) and body composition based on magnetic resonance fat fraction (FF) mapping. A total of 341 subjects, who underwent abdominal MRI examination with FF mapping were enrolled in this study, including 68 T2DM patients and 273 non-T2DM patients. The FFs and areas of visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT) and abdominal muscle (AM) were measured at the level of the L1-L2 vertebral. The FF of bone marrow adipose tissue (BMAT) was determined by the averaged FF values measured at the level of T12 and L1 vertebral, respectively. The whole hepatic fat fraction (HFF) and pancreatic fat fraction (PFF) were measured based on 3D semi-automatic segmentation on the FF mapping. All data were analyzed by GraphPad Prism and MedCalc. VAT area, VAT FF, HFF, PFF of T2DM group were higher than those of non-T2DM group after adjusting for age and sex (P < 0.05). However, there was no differences in SAT area, SAT FF, BMAT FF, AM area and AM FF between the two groups (P > 0.05). VAT area and PFF were independent risk factors of T2DM (all P < 0.05). The area under the curve (AUC) of the receiver operating characteristic (ROC) for VAT area and PFF in differentiating between T2DM and non-T2DM were 0.685 and 0.787, respectively, and the AUC of PFF was higher than VAT area (P < 0.05). Additionally, in seemingly healthy individuals, the SAT area, VAT area, and AM area were found to be significantly associated with being overweight and/or obese (BMI ≥ 25) (all P < 0.05). In this study, it was found that there were significant associations between T2DM and VAT area, VAT FF, HFF and PFF. In addition, VAT area and PFF were the independent risk factors of T2DM. Especially, PFF showed a high diagnostic performance in discrimination between T2DM and non-T2DM. These findings may highlight the crucial role of PFF in the pathophysiology of T2DM, and it might be served as a potential imaging biomarker of the prevention and treatment of T2DM. Additionally, in individuals without diabetes, focusing on SAT area, VAT area and AM area may help identify potential health risks and provide a basis for targeted weight management and prevention measures.

Body composition measurements and clinical outcomes in patients with resectable pancreatic adenocarcinoma – analysis from SWOG S1505

Sarcopenic obesity and muscle attenuation have been associated with survival in patients with borderline resectable and advanced pancreatic ductal adenocarcinoma (PDA); however, these relationships are unknown for patients with resectable PDA. This study examined the associations between skeletal muscle and adipose tissue as measured on baseline computed tomography (CT) and the overall survival (OS) of participants with resectable PDA in a secondary analysis of the Southwest Oncology Group S1505 clinical trial (identifier: NCT02562716). The S1505 phase II clinical trial enrolled patients with resectable PDA who were randomized to receive modified FOLFIRINOX or gemcitabine and nab-paclitaxel as perioperative chemotherapy, followed by surgical resection. Baseline axial CT images at the L3 level were analyzed with externally validated software, and measurements were recorded for skeletal muscle area and skeletal muscle density, visceral adipose tissue area (VATA) and density, and subcutaneous adipose tissue area and density. The relationships between CT metrics and OS were analyzed using Cox regression models, with adjustment for baseline participant characteristics. Of 98 eligible participants with available baseline abdominal CT, 8 were excluded because of imaging quality (eg, orthopedic hardware), resulting in 90 evaluable cases: 51 men (57.0%; mean age, 63.2 years [SD, 8.5]; mean body mass index [BMI], 29.3kg/m2 [SD, 6.4]), 80 White (89.0%), 6 Black (7.0%), and 4 unknown race (4.0%). Sarcopenia was present in 32 participants (35.9%), and sarcopenic obesity was present in 10 participants (11.2%). Univariable analyses for the 6 variables of interest indicated that the standardized mean difference (hazard ratio [HR], 0.75; 95% CI, 0.57-0.98; P=.04) was statistically significantly associated with OS. In models adjusted for sex, race, age, BMI, performance score, contrast use, sarcopenia, and sarcopenic obesity, VATA was statistically significantly associated with OS (HR, 1.58; 95% CI, 1.00-2.51; P=.05). No difference was observed in OS between participants according to sarcopenic obesity or sarcopenia categories. The median OS estimates were 25.1 months for participants without sarcopenic obesity, 18.6 months for participants with sarcopenic obesity, 23.6 months for participants without sarcopenia, and 27.9 months for participants with sarcopenia. This was the first study to systematically evaluate body composition parameters in a prospective multicenter trial of patients with resectable PDA who received perioperative chemotherapy. Visceral adipose tissue was associated with survival; however, there was no association between OS and sarcopenia or sarcopenic obesity. Further studies should evaluate these findings in more detail.

Prediction of Mortality and Hepatic Encephalopathy after Transjugular Intrahepatic Portosystemic Shunt Placement: Baseline and Longitudinal Body Composition Measurement

PurposeTo investigate effects of baseline and early longitudinal body composition changes on mortality and hepatic encephalopathy (HE) after transjugular intrahepatic portosystemic shunt (TIPS). Materials and MethodsThis is a case-control study with analysis of a TIPS registry (1995–2020) including data from patients with cirrhosis with computed tomography (CT) scans obtained within 1 month before and 3 months after TIPS. Core muscle area (CMA), macroscopic subcutaneous adipose tissue (mSAT), macroscopic visceral adipose tissue (mVAT) area, and muscle adiposity index (MAI) on CT were obtained. Multipredictor Cox proportional hazards models were used to assess the effect of body composition variables on mortality or HE. ResultsIn total, 280 patients (158 men; median age, 57.0 years; median Model for End-stage Liver Disease-sodium [MELD-Na] score, 14.0) were included. Thirty-four patients had post-TIPS imaging. Median baseline CMA was 68.3 cm2 (interquartile range, 57.7–83.5 cm2). Patients with higher baseline CMA had decreased risks of mortality (hazard ratio [HR]: 0.82; P = .04) and HE (HR: 0.82; P = .009). It improved prediction of mortality over MELD-Na and post-TIPS right atrial pressure alone (confidence interval = 0.729). An increase in CMA (HR: 0.60; P = .043) and mSAT (HR: 0.86; P = .022) or decrease in MAI (HR: 1.50; P = .049) from before to after TIPS was associated with a decreased risk of mortality. An increase in mSAT was associated with an increased risk of HE (HR: 1.11; P = .04). ConclusionsCMA on CT scan 1 month before TIPS placement predicts mortality and HE in patients with cirrhosis. Changes in body composition on CT measured 3 months after TIPS placement independently predict mortality and HE.

Implication of Bone Mineral Density and Body Composition Parameters for Length of Hospital Stay in Patients with COVID-19.

Multisystem information, including musculoskeletal information, can be captured from chest CT scans of patients with COVID-19 without further examination. This study aims to assess the relationship between chest CT-extracted baseline bone mineral density (BMD) and body composition parameters and the length of hospital stay in these patients. A retrospective analysis was performed in a cohort of 88 patients with COVID-19. Correlation analysis and a generalized linear model (GLM) were used to assess the associations between the length of hospital stay and covariates, including age, sex, body mass index (BMI), BMD and body composition variables. The mean length of hospital stay was 27.4±8.7 days. The length of hospital stay was significantly positively associated with age (r=0.202, p=0.046) and the paraspinal muscle fat ratio (r=0.246, p=0.021). The GLM involving age, sex, BMD, paraspinal muscle fat ratio, subcutaneous adipose tissue (SAT) area, visceral adipose tissue (VAT) area, and liver fat fraction (LFF) showed that the length of hospital stay was positively correlated with VAT area (β coefficients, 95% CI: 9.304, 1.141-17.478, p=0.025). The musculoskeletal features extracted from chest CT correlated with the prognosis of COVID-19 patients. Factors including old age, a higher paraspinal muscle fat ratio and a larger VAT area in patients with COVID-19 were associated with longer hospital stays.

Change in abdominal obesity after colon cancer surgery – effects of left-sided and right-sided colonic resection

BackgroundExcess abdominal visceral adipose tissue (VAT) is associated with metabolic diseases and poor survival in colon cancer (CC). We assessed the impact of different types of CC surgery on changes in abdominal fat depots.Material and methodsComputed tomography (CT)-scans performed preoperative and 3 years after CC surgery were analyzed at L3-level for VAT, subcutaneous adipose tissue (SAT) and total adipose tissue (TAT) areas. We assessed changes in VAT, SAT, TAT and VAT/SAT ratio after 3 years and compared the changes between patients who had undergone left-sided and right-sided colonic resection in the total population and in men and women separately.ResultsA total of 134 patients with stage I-III CC undergoing cancer surgery were included. Patients who had undergone left-sided colonic resection had after 3 years follow-up a 5% (95% CI: 2–9%, p < 0.01) increase in abdominal VAT, a 4% (95% CI: 2–6%, p < 0.001) increase in SAT and a 5% increase (95% CI: 2–7%, p < 0.01) in TAT. Patients who had undergone right-sided colonic resection had no change in VAT, but a 6% (95% CI: 4–9%, p < 0.001) increase in SAT and a 4% (95% CI: 1–7%, p < 0.01) increase in TAT after 3 years. Stratified by sex, only males undergoing left-sided colonic resection had a significant VAT increase of 6% (95% CI: 2–10%, p < 0.01) after 3 years.ConclusionAfter 3 years follow-up survivors of CC accumulated abdominal adipose tissue. Notably, those who underwent left-sided colonic resection had increased VAT and SAT, whereas those who underwent right-sided colonic resection demonstrated solely increased SAT.

RACIAL AND ETHNIC DISPARITIES IN NEIGHBORHOOD SOCIOECONOMIC CHARACTERISTICS ASSOCIATIONS WITH VISCERAL FAT

Abstract Visceral adipose tissue (VAT) has a more significant role in the pathophysiology of cardiometabolic diseases than subcutaneous adipose tissue (SAT). Our previous findings suggest VAT represents an important pathway through which racial disparities in the social environment are biologically embodied. To understand the role of structural racism in this pathway, this paper investigated racial disparities in neighborhood socioeconomic status (NSES) and VAT. We hypothesized that NSES is inversely associated with VAT and VAT/SAT ratio over 6 years and associations differ by race and ethnicity. Abdominal VAT and SAT area (cm2) were measured at years 0, 3, and 6 using dual-energy X-ray absorptiometry in a subsample (n=11,020) of the Women’s Health Initiative (age 50-79). The NSES Z-scores were obtained from the US Census and American Community Survey based on participant’s census tract residence. We evaluate racial and ethnic disparities in the exposure and outcome using ANOVA, and associations between NSES with VAT using mixed effects models. We found that NSES and VAT area differed by race and ethnicity. American Indian and Alaska Native (AIAN), Black, and Latina groups were significantly (P&amp;lt; 0.01) more likely to live in neighborhoods with NSES Z-scores below the population mean (Z-score=0) compared with White and Asian races. AIAN, Latina, and Black women had the highest VAT (220 cm2, 185 cm2, 177 cm2, respectively). Findings support the hypothesis that associations between NSES and VAT differ by race and ethnicity. Results from mixed effects models are expected to provide longitudinal evidence that structural determinants are associated with VAT.

Predictors of visceral and subcutaneous adipose tissue and muscle density: The ShapeUp! Kids study

Background and aimsBody fat distribution, i.e., visceral (VAT), subcutaneous adipose tissue (SAT) and intramuscular fat, is important for disease prevention, but sex and ethnic differences are not well understood. Our aim was to identify anthropometric, demographic, and lifestyle predictors for these outcomes. Methods and resultsThe cross-sectional ShapeUp!Kids study was conducted among five ethnic groups aged 5–18 years. All participants completed questionnaires, anthropometric measurements, and abdominal MRI scans. VAT and SAT areas at four lumbar levels and muscle density were assessed manually. General linear models were applied to estimate coefficients of determination (R2) and to compare the fit of VAT and SAT prediction models. After exclusions, the study population had 133 male and 170 female participants. Girls had higher BMI-z scores, waist circumference (WC), and SAT than boys but lower VAT/SAT and muscle density. SAT, VAT, and VAT/SAT but not muscle density differed significantly by ethnicity. R2 values were higher for SAT than VAT across groups and improved slightly after adding WC. For SAT, R2 increased from 0.85 to 0.88 (girls) and 0.62 to 0.71 (boys) when WC was added while VAT models improved from 0.62 to 0.65 (girls) and 0.57 to 0.62 (boys). VAT values were significantly lower among Blacks than Whites with little difference for the other groups. ConclusionThis analysis in a multiethnic population identified BMI-z scores and WC as the major predictors of MRI-derived SAT and VAT and highlights the important ethnic differences that need to be considered in diverse populations.

Exploring a simplified way to diagnose pelvic lipomatosis: prediction of pelvic fat volume using a single cross-sectional image.

Pelvic lipomatosis (PL) is a rare disease characterized by the overgrowth of pelvic adipose tissue (AT). We investigated the relationships between areas of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) and pelvic fat volume (PFV), and analyzed the feasibility of diagnosing PL from a single cross-sectional image. The study included 50 patients and 50 controls. We used nnU-Net to segment SAT and VAT automatically. L3 vertebra was set as the zero point (L0), and a total of 201 slices were obtained with a 1 mm interval (L-100 - L+100). We selected 5 pelvic slices, including slices of the anterior superior margin of the S1-S4 vertebrae and the slice above the bilateral femoral head (FH). SAT areas, VAT areas, and PFVs were calculated by computational software. Areas and volumes of 2 groups were compared by t-test or rank-sum test. The correlations among areas and PFV were calculated. Logistic regression models were developed to identify the best slice for predicting PL. Receiver operating characteristic (ROC) curves were performed, and the area under the curve (AUC) and thresholds [with sensitivity (SEN) and specificity (SPE)] were calculated. VAT areas of L-94 - L-100, L+79 - L+100, S1-S4, and FH indicated statistical differences between patients and controls (P<0.05). The linear regression model with VAT area as the independent variable was established to estimate PFV (FH level: r=0.745, P<0.001, R2=0.555). Among the univariate logistic regression models, VAT area at FH as the independent variable had the highest performance in predicting PL (AUC: 0.893, SEN: 74%, SPE: 94%), followed by S4 level (AUC: 0.800, SEN: 88%, SPE: 66%). The overall accuracy of the logistic regression model including VAT areas at S4 and FH in predicting PL was 88% (AUC: 0.927, SEN: 90%, SPE: 88%). VAT areas at the level of FH can help estimate the value of PFV. VAT areas of S4 and FH provide greater power than a single image for the diagnosis of PL.

Associations of infant feeding practices with abdominal and hepatic fat measures in childhood in the longitudinal Healthy Start Study

BackgroundInfant feeding patterns have been linked with obesity risk in childhood, but associations with precise measures of body fat distribution are unclear. ObjectiveWe examined associations of infant feeding practices with abdominal fat and hepatic fat trajectories in childhood. MethodsThis study included 356 children in the Healthy Start Study, a prospective prebirth cohort in Colorado. Infant feeding practices were assessed by postnatal interviews and categorized as any human milk <6 mo compared with ≥6 mo; complementary foods introduced ≤4 mo compared with >4 mo; soda introduced ≤18 mo compared with >18 mo. Abdominal subcutaneous (SAT) and visceral adipose tissue (VAT) areas and hepatic fat (%) were assessed by magnetic resonance imaging in early and middle childhood (median 5 and 9 y old, respectively). We examined associations of infant feeding with adiposity trajectories across childhood using linear mixed models. ResultsIn the sample of children, 67% consumed human milk ≥6 mo, 75% were introduced to complementary foods at >4 mo, and 81% were introduced to soda at >18 mo. We did not find any associations between duration of any human milk consumption and childhood adiposity trajectories. Early introduction to complementary foods (≤4 mo) was associated with faster rates of change for SAT and VAT during childhood (Slope [95% CI]: 15.1 [10.7,19.4] cm2/y for SAT; 2.5 [1.9,2.9] cm2/y for VAT), compared with introduction at >4 mo (5.5 [3.0,8.0] cm2/y and 1.6 [1.3,1.9] cm2/y, respectively). Similarly, early introduction to soda (≤18 mo) was associated with faster rates of change for all 3 outcomes during childhood (Slope [95% CI]: 20.6 [15.0,26.1] cm2/y for SAT, 2.7 [2.0,3.3] cm2/y for VAT, 0.3 [0.1,0.5] %/year for hepatic fat) compared with delayed introduction (5.4 [2.8,8.0] cm2/y, 1.7 [1.3, 2.0] cm2/y, -0.1 [-0.2,0.0] %/y, respectively). ConclusionsThe timing of introduction and quality of complementary foods in infancy was associated with rates of abdominal and hepatic fat accrual during childhood. Experimental studies are needed to assess underlying mechanisms.

Sex differences in abdominal visceral fat composition and metabolism as predictors of DLBCL prognosis: A retrospective cohort study

PurposeWe aimed to determine if sex differences in abdominal visceral fat composition and metabolism can help predict the prognosis of diffuse large B-cell lymphoma (DLBCL) patients. MethodsThis retrospective cohort study included 117 DLBCL patients. The area and metabolic activity of subcutaneous adipose tissue and visceral adipose tissue were measured using CT and PET imaging. Kaplan–Meier survival analysis was employed to evaluate the effect of these parameters on progression-free survival. Multivariate Cox proportional hazard regression models were used to determine the effects of relative visceral fat area (rVFA) on sex-specific survival. ResultsFemales with an rVFA greater than the optimal threshold of 35 % and a visceral-to-subcutaneous adipose tissue ratio (V/S) >3.24 had worse progression-free survival (p = 0.01, 0.001, respectively). No rVFA or V/S were identified in significantly stratified males with DLBCL (p = 0.249 and 0.895, respectively). Combining the changes in rVFA and V/S identified a subgroup of females with high rVFA and V/S values and exceptionally poor outcomes. The rVFA was a significant predictor of DLBCL progression in females alone. ConclusionOnce female DLBCL patients accumulate fat over the tolerable range in the visceral area, they might be at an increased risk of progression (hazard ratio, 3.87; 95 % CI, 1.81–12.69, p = 0.02).Sex differences in visceral fat composition and metabolism may provide a new risk stratification system for patients with DLBCL.

Abstract 15886: High Visceral to Subcutaneous Fat Ratio is Correlated With Increased Cardiovascular Events in Elderly Patients With Suspected Coronary Artery Disease

Introduction: Although abdominal fat distribution (AFD), presented as the ratio of visceral adipose tissue (VAT) to subcutaneous adipose tissue (SAT) area (V/S ratio), is possibly associated with an increased risk of cardiovascular disease (CVD), the relationship between V/S ratio and its long-term outcomes have rarely been studied. Methods: We assessed 942 consecutive patients with suspected coronary artery disease who underwent computed tomography (CT) angiography. The patients also underwent plain abdominal CT to measure VAT and SAT areas. The V/S ratio was calculated to assess the AFD. The patients were classified into four groups based on the median V/S ratio and median age (i.e., 0.625 and 69 years, respectively). We examined the association between the V/S ratio and its long-term outcomes in each age group. The primary outcome was major adverse cardiac events (MACEs), including all-cause death, any coronary revascularization, acute coronary syndrome, and emergent hospitalization due to CVD. Results: Over a median follow-up of 1507 days, the incidence of any cardiovascular event was not associated with the V/S ratio among younger patients; however, among older patients, the incidence of MACEs, all-cause death, and any coronary revascularization was higher in the high V/S ratio group than in the low V/S ratio group. According to the Kaplan-Meier analysis, only older patients had a significantly lower MACE-free survival rate in the high V/S ratio group than in the low V/S ratio group, and no differences were noted among the younger patients in both groups. After adjusting for traditional coronary risk factors, high V/S ratio was independently associated with incidence of MACEs in older patients (Figure). Conclusion: A high V/S ratio was associated with an increased risk of MACEs in older patients only. Therefore, a high V/S ratio may be an important risk factor for CVD, particularly in older patients. However, AFD did not affect CVD prognosis among younger patients.

The Interplay between Adipose Tissue Properties and Levels of NT-proBNP in People with HIV.

We aimed to assess the association between low N-terminal pro-brain natriuretic peptide (NT-proBNP) and body mass index (BMI), adipose tissue distribution, adiponectin, and HIV-specific risk factors among people with HIV (PWH). We included 811 PWH with measurement of height, weight and waist circumference, blood samples analyzed for NT-proBNP, and visceral-(VAT) and subcutaneous (SAT) adipose tissue areas measured from CT-scans. Low concentrations of NT-proBNP were defined as concentrations below the limit of quantification (5.9 pmol/L). Associations were explored with multivariable logistic regression analyses adjusted for relevant confounders. We identified 471 (58%) individuals with low concentrations of NT-proBNP. Increasing BMI was associated with higher odds of low NT-proBNP (adjusted OR (aOR) 1.06 (95% CI: 1.01-1.11) per 1 kg/m2). Central obesity and large areas of VAT were associated with higher odds of low NT-proBNP (aOR 1.66 (1.16-2.36) and aOR 1.69 (1.09-2.62), respectively). Higher adiponectin was associated with lower odds of low NT-proBNP (aOR 0.86 (0.79-0.95) per 10% increase). No associations were found between low NT-proBNP and HIV-specific risk factors. In PWH, low NT-proBNP is associated with an adverse adipose tissue profile with high BMI, central obesity, accumulation of VAT, and low adiponectin.