Association between single-slice measurements of visceral and abdominal subcutaneous adipose tissue with volumetric measurements: the Framingham Heart Study. Int J Obes (Lond). 2010;34:781-787. [PMID: 20065971 DOI: 10.1038/ijo.2009.279]

Comparison and precision of visceral adipose tissue measurement techniques in a multisite longitudinal study using MRI

BACKGROUND

Measurement of visceral adipose tissue (VAT) using magnetic resonance imaging (MRI) is considered accurate and safe. Single slice measurements perform similar to volumetric measurements for cross-sectional observation studies but may not perform as well for longitudinal studies. This study compared the performance of single slice to volumetric VAT measurements in a prospective longitudinal study. Consistency of results across sites and over time was also evaluated.

METHODS

A total of 935 healthy participants were recruited and scanned with MRI twice, approximately six months apart as part of a randomized, controlled, parallel arm, unblinded study conducted at four clinical centers in the United States. A 3D Dixon MRI sequence was used to image the abdomen, and visceral fat volumes were quantified for the abdomen, reduced coverage volumes (11 and 25 slices), and at single slices positioned at anatomical landmarks. A traveling phantom was scanned twice at all imaging sites.

RESULTS

The correlation of single slice VAT measurement to full abdomen volumetric measurements ranged from 0.78 to 0.93 for cross-sectional observation measurements and 0.30 to 0.55 for longitudinal change. Reduced coverage volumetric measurement outperformed single slice measurements but still showed improved precision with more slices with cross-sectional observation and longitudinal correlations of 0.94 and 0.66 for 11 slices and 0.94 and 0.70 for 25 slices, respectively. No significant differences were observed across sites or over time with the traveling phantom and the volume measurements had a standard deviation of 14.1 mL, 2.6% of the measured volume.

CONCLUSION

Single slice VAT measurements had significantly lower correlation with abdomen VAT volume for longitudinal change than for cross-sectional observation measurements and may not be suitable for longitudinal studies. Data from multiple sites, different scanners, and over time did not show significant differences.

Unhealthy visceral fat is associated with improved efficacy of immunotherapy in endometrial cancer

Obesity is a known driver of endometrial cancer. In this issue of the JCI, Gómez-Banoy and colleagues investigated a cohort of patients with advanced endometrial cancer treated with immune checkpoint inhibitors targeting the interaction between programmed cell death receptor-1 (PD-1) and its ligand (PD-L1). Notably, a BMI in the overweight or obese range was paradoxically associated with improved progression-free and overall survival. A second paradox emerged from CT analyses of visceral adipose tissue, viewed as an unhealthy fat depot in most other contexts, the quantity of which was also associated with improved treatment outcomes. Though visceral adiposity may have value as a biomarker to inform personalized treatment strategies, of even greater impact would be if a therapeutic strategy emerges from the future identification of adipose-derived mediators of this putative anticancer immune-priming effect.

Subcutaneous and Visceral Adipose Tissue Reference Values From the Framingham Heart Study Thoracic and Abdominal CT

BACKGROUND

Computed tomography (CT) captures the quantity, density, and distribution of subcutaneous and visceral (SAT and VAT) adipose tissue compartments. These metrics may change with age and sex.

OBJECTIVE

The study aims to provide age-, sex-, and vertebral level-specific reference values for SAT on chest CT and for SAT and VAT on abdomen CT.

MATERIALS AND METHODS

This secondary analysis of an observational study describes SAT and VAT measurements in participants of the Framingham Heart Study without known cancer diagnosis who underwent at least 1 of 2 CT examinations between 2002 and 2011. We used a previously validated machine learning-assisted pipeline and rigorous quality assurance to segment SAT at the fifth, eighth, and tenth thoracic vertebra (T5, T8, T10) and SAT and VAT at the third lumbar vertebra (L3). For each metric, we measured cross-sectional area (cm2) and mean attenuation (Hounsfield units [HU]) and calculated index (area/height2) (cm2/m2) and gauge (attenuation × index) (HU × cm2/m2). We summarized body composition metrics by age and sex and modeled sex-, age-, and vertebral level-specific reference curves.

RESULTS

We included 14,898 single-level measurements from up to 4 vertebral levels of 3797 scans of 3730 Framingham Heart Study participants (1889 [51%] male with a mean [standard deviation] age of 55.6 ± 10.6 years; range, 38-81 years). The mean VAT index increased with age from 65 (cm2/m2) in males and 29 (cm2/m2) in females in the <45-year-old age group to 99 (cm2/m2) in males and 60 (cm2/m2) in females in >75-year-old age group. The increase of SAT with age was less pronounced, resulting in the VAT/SAT ratio increasing with age. A free R package and online interactive visual web interface allow access to reference values.

CONCLUSIONS

This study establishes age-, sex-, and vertebral level-specific reference values for CT-assessed SAT at vertebral levels T5, T8, T10, and L3 and VAT at vertebral level L3.

Prediction of visceral adipose tissue magnitude using a new model based on simple clinical measurements

Aims

Waist circumference (WC) is a reliable obesity surrogate but may not distinguish between visceral and subcutaneous adipose tissue. Our aim was to develop a novel sex-specific model to estimate the magnitude of visceral adipose tissue measured by computed tomography (CT-VAT).

Methods

The model was initially formulated through the integration of anthropometric measurements, laboratory data, and CT-VAT within a study group (n=185), utilizing the Multivariate Adaptive Regression Splines (MARS) methodology. Subsequently, its correlation with CT-VAT was examined in an external validation group (n=50). The accuracy of the new model in estimating increased CT-VAT (>130 cm2) was compared with WC, body mass index (BMI), waist-hip ratio (WHR), visceral adiposity index (VAI), a body shape index (ABSI), lipid accumulation product (LAP), body roundness index (BRI), and metabolic score for visceral fat (METS-VF) in the study group. Additionally, the new model's accuracy in identifying metabolic syndrome was evaluated in our Metabolic Healthiness Discovery Cohort (n=430).

Results

The new model comprised WC, gender, BMI, and hip circumference, providing the highest predictive accuracy in estimating increased CT-VAT in men (AUC of 0.96 ± 0.02), outperforming other indices. In women, the AUC was 0.94 ± 0.03, which was significantly higher than that of VAI, WHR, and ABSI but similar to WC, BMI, LAP, BRI, and METS-VF. It's demonstrated high ability for identifying metabolic syndrome with an AUC of 0.76 ± 0.03 (p<0.001).

Conclusion

The new model is a valuable indicator of CT-VAT, especially in men, and it exhibits a strong predictive capability for identifying metabolic syndrome.

Preoperative Prediction of Shock Impedance for Subcutaneous Implantable Cardioverter Defibrillator Using Chest Computed Tomography

BACKGROUND

High shock impedance is associated with conversion failure among patients with subcutaneous implantable cardioverter defibrillators (S-ICD). Currently, there is no preoperative assessment method for predicting high shock impedance. This study examined the efficacy of chest computed tomography (CT) as a preoperative evaluation tool to assess the shock impedance of S-ICDs.

METHODS AND RESULTS

The amount of adipose tissue adjacent to the device and anteroposterior diameter at the basal heart region were measured preoperatively using chest CT. We examined the correlation between these measurements and shock impedance at the conversion test. We enrolled 43 patients with S-ICDs (mean [±SD] age 54±15 years; body mass index 23±4 kg/m2; PRAETORIAN score 30-270 points; amount of adipose tissue 1,250±716 cm3), who underwent intraoperative conversion tests by inducing ventricular fibrillation, which was terminated with a 65-J shock. A sufficient concordance correlation coefficient was observed between the shock impedance and the amount of adipose tissue (r=0.616, P<0.01) and anteroposterior diameter (r=0.645, P<0.01). In multiple regression analysis, the amount of adipose tissue (β=0.439, P=0.009) and anteroposterior diameter (β=0.344, P=0.038) were identified as independent predictive factors of shock impedance.

CONCLUSIONS

The preoperative CT-measured amount of adipose tissue and basal heart anteroposterior diameter are independent predictors of shock impedance. These parameters may be more accurate in identifying higher shock impedance in patients with S-ICDs.

Body mass index and adiposity influence responses to immune checkpoint inhibition in endometrial cancer

BACKGROUNDObesity is the foremost risk factor in the development of endometrial cancer (EC). However, the impact of obesity on the response to immune checkpoint inhibitors (ICI) in EC remains poorly understood. This retrospective study investigates the association among BMI, body fat distribution, and clinical and molecular characteristics of EC patients treated with ICI.METHODSWe analyzed progression-free survival (PFS) and overall survival (OS) in EC patients treated with ICI, categorized by BMI, fat-mass distribution, and molecular subtypes. Incidence of immune-related adverse events (irAEs) after ICI was also assessed based on BMI status.RESULTS524 EC patients were included in the study. Overweight and obese patients exhibited a significantly prolonged PFS and OS compared with normal BMI patients after treatment with ICI. Multivariable Cox's regression analysis confirmed the independent association of overweight and obesity with improved PFS and OS. Elevated visceral adipose tissue (VAT) was identified as a strong independent predictor for improved PFS to ICI. Associations between obesity and OS/PFS were particularly significant in the copy number-high/TP53abnormal (CN-H/TP53abn) EC molecular subtype. Finally, obese patients demonstrated a higher irAE rate compared with normal BMI individuals.CONCLUSIONObesity is associated with improved outcomes to ICI in EC patients and a higher rate of irAEs. This association is more pronounced in the CN-H/TP53abn EC molecular subtype.FUNDINGNIH/NCI Cancer Center; MSK Gerstner Physician Scholars Program; National Center for Advancing Translational Sciences (NCATS); Cycle for Survival; Breast Cancer Research Foundation.

Body mass index and adiposity influence responses to immune checkpoint inhibition in endometrial cancer

Background

Obesity is the foremost risk factor in the development of endometrial cancer (EC). However, the impact of obesity on the response to immune checkpoint inhibitors (ICI) in EC remains poorly understood. This retrospective study investigates the association between body mass index (BMI), body fat distribution, and clinical and molecular characteristics of EC patients treated with ICI.

Methods

We analyzed progression-free survival (PFS) and overall survival (OS) in EC patients treated with ICI, categorized by BMI, fat mass distribution, and molecular subtypes. Incidence of immune-related adverse events (irAE) after ICI was also assessed based on BMI status.

Results

524 EC patients were included in the study. Overweight and obese patients exhibited a significantly prolonged PFS and OS compared to normal BMI patients after treatment with ICI. Multivariable Cox regression analysis confirmed the independent association of overweight and obesity with improved PFS and OS. Elevated visceral adipose tissue (VAT) was identified as a strong independent predictor for improved PFS to ICI. Associations between obesity and OS/PFS were particularly significant in the copy number-high/TP53abnormal (CN-H/TP53abn) EC molecular subtype. Finally, obese patients demonstrated a higher irAE rate compared to normal BMI individuals.

Conclusion

Obesity is associated with improved outcomes to ICI in EC patients and a higher rate of irAEs. This association is more pronounced in the CN-H/TP53abn EC molecular subtype.

Funding

NIH/NCI Cancer Center Support Grant P30CA008748 (MSK). K08CA266740 and MSK Gerstner Physician Scholars Program (J.C.O). RUCCTS Grant #UL1 TR001866 (N.G-B and C.S.J). Cycle for survival and Breast Cancer Research Foundation grants (B.W).

Establishment of a novel weight reduction model after laparoscopic sleeve gastrectomy based on abdominal fat area

In light of ongoing research elucidating the intricacies of obesity and metabolic syndrome, the role of abdominal fat (especially visceral fat) has been particularly prominent. Studies have revealed that visceral adipose tissue can accelerate the development of metabolic syndrome by releasing various bioactive compounds and hormones, such as lipocalin, leptin and interleukin. A retrospective analysis was performed on the clinical data of 167 patients with obesity. Among them, 105 patients who satisfied predefined inclusion and exclusion criteria were included. The parameters evaluated included total abdominal fat area (TAFA), laboratory indicators and anthropometric measurements. Weight reduction was quantified through percent total weight loss (%TWL) and percent excess weight loss (%EWL) postoperatively. Binary logistic regression analysis and receiver operating characteristic (ROC) curve analysis were employed to identify predictors of weight loss. Binary logistic regression analysis emphasized that total abdominal fat area was an independent predictor of %EWL ≥75% (p < 0.001). Total abdominal fat area (p = 0.033) and BMI (p = 0.003) were independent predictors of %TWL ≥30%. In our cohort, %TWL ≥30% at 1 year after surgery was closely related to the abdominal fat area and BMI. Based on these results, we formulated a novel model based on these factors, exhibiting superior predictive value for excellent weight loss.

Relationship of Liver Blood Tests and T1 Relaxation Time With Intra-pancreatic Fat Deposition

Background

Liver is well recognised as a metabolically active organ. While intra-pancreatic fat deposition (IPFD) is emerging as an important player in the whole-body metabolism, the interplay between the liver and IPFD has been poorly investigated. This study aimed to investigate the associations of liver blood tests and non-invasive tests for hepatic fibrosis with IPFD.

Methods

Participants underwent a 3.0 Tesla magnetic resonance imaging to measure IPFD and map liver T1 (longitudinal relaxation time). Four liver tests were done on the same sample of blood. Hepatic fibrosis risk score (BARD) was calculated. Linear regression models were built, accounting for age, sex, visceral-to-subcutaneous fat ratio, and other covariates.

Results

A total of 143 individuals were studied. In the most adjusted model, alkaline phosphatase (P < 0.001), alanine aminotransferase (P < 0.001), and γ-glutamyl transferase (P = 0.042) were significantly positively associated with IPFD. The BARD score was not significantly associated with IPFD in the most adjusted model (P = 0.295). T1 relaxation time of the liver was not significantly associated with IPFD in the most adjusted model (P = 0.782).

Conclusions

Elevated alkaline phosphatase, alanine aminotransferase, and γ-glutamyl transferase are associated with increased IPFD. Hepatic fibrosis does not appear to be associated with IPFD.

Visceral Adiposity Independently Predicts Time to Flare in Inflammatory Bowel Disease but Body Mass Index Does Not

BACKGROUND

Obesity is associated with progression of inflammatory bowel disease (IBD). Visceral adiposity may be a more meaningful measure of obesity compared with traditional measures such as body mass index (BMI). This study compared visceral adiposity vs BMI as predictors of time to IBD flare among patients with Crohn's disease and ulcerative colitis.

METHODS

This was a retrospective cohort study. IBD patients were included if they had a colonoscopy and computed tomography (CT) scan within a 30-day window of an IBD flare. They were followed for 6 months or until their next flare. The primary exposure was the ratio of visceral adipose tissue to subcutaneous adipose tissue (VAT:SAT) obtained from CT imaging. BMI was calculated at the time of index CT scan.

RESULTS

A total of 100 Crohn's disease and 100 ulcerative colitis patients were included. The median age was 43 (interquartile range, 31-58) years, 39% had disease duration of 10 years or more, and 14% had severe disease activity on endoscopic examination. Overall, 23% of the cohort flared with median time to flare 90 (interquartile range, 67-117) days. Higher VAT:SAT was associated with shorter time to IBD flare (hazard ratio of 4.8 for VAT:SAT ≥1.0 vs VAT:SAT ratio <1.0), whereas higher BMI was not associated with shorter time to flare (hazard ratio of 0.73 for BMI ≥25 kg/m2 vs BMI <25 kg/m2). The relationship between increased VAT:SAT and shorter time to flare appeared stronger for Crohn's than for ulcerative colitis.

CONCLUSIONS

Visceral adiposity was associated with decreased time to IBD flare, but BMI was not. Future studies could test whether interventions that decrease visceral adiposity will improve IBD disease activity.

Visceral obesity determined by CT as a predictor of short-term postoperative complications in patients with ovarian cancer

OBJECTIVE

To explore the association between visceral obesity and short-term postoperative complications in patients with advanced ovarian cancer undergoing cytoreductive surgery.

METHODS

The medical records of patients with advanced epithelial ovarian cancer were reviewed. The visceral fat area, subcutaneous fat area and total fat area at the L3/4 level were measured on a preoperative single-slice CT scan. The receiver operating characteristic (ROC) curve was used to calculate the optimal cutoff value for the visceral fat area. The relationship between the visceral fat area and the characteristics of ovarian cancer patients were analyzed. Univariable and multivariable logistic regression analyses were performed to investigate relationship between perioperative characteristics and short-term complications.

RESULTS

According to the ROC curve, the best cutoff value of the VFA was 93 cm2. Of the 130 patients, 53.8% (70/130) had visceral obesity. Patients with visceral obesity were older than those with nonvisceral obesity (58.4 years old vs. 52.1 years old, p < 0.001). The proportion of patients with hypertension was higher (35.7 vs. 13.3%, p = 0.003). The total fat area and subcutaneous fat area were larger in patients with visceral obesity (294.3 ± 75.5 vs. 176.2 ± 68.7, p < 0.001; 158.9 ± 54.7 vs. 121.7 ± 52.6, p < 0.001). Compared with patients in the nonvisceral obese group, patients in the visceral obese group were more likely to have postoperative fever (21/70 30.0% vs. 8/60 1.25%, p = 0.023), leading to a longer length of hospital stay (21 days vs. 17 days, p = 0.009). The time from surgery to adjuvant chemotherapy for patients with visceral obesity was shorter (24 days vs. 19 days, p = 0.037). Multivariate analysis showed that visceral obesity (OR = 6.451, p < 0.001) and operation time (OR = 1.006, p < 0.001) were independent predictors of postoperative complications.

CONCLUSION

Visceral obesity is an important risk factor for short-term postoperative complications in patients with advanced ovarian cancer undergoing cytoreductive surgery.

Multimodality Imaging in Metabolic Syndrome: State-of-the-Art Review

Metabolic syndrome comprises a set of risk factors that include abdominal obesity, impaired glucose tolerance, hypertriglyceridemia, low high-density lipoprotein levels, and high blood pressure, at least three of which must be fulfilled for diagnosis. Metabolic syndrome has been linked to an increased risk of cardiovascular disease and type 2 diabetes mellitus. Multimodality imaging plays an important role in metabolic syndrome, including diagnosis, risk stratification, and assessment of complications. CT and MRI are the primary tools for quantification of excess fat, including subcutaneous and visceral adipose tissue, as well as fat around organs, which are associated with increased cardiovascular risk. PET has been shown to detect signs of insulin resistance and may detect ectopic sites of brown fat. Cardiovascular disease is an important complication of metabolic syndrome, resulting in subclinical or symptomatic coronary artery disease, alterations in cardiac structure and function with potential progression to heart failure, and systemic vascular disease. CT angiography provides comprehensive evaluation of the coronary and systemic arteries, while cardiac MRI assesses cardiac structure, function, myocardial ischemia, and infarction. Liver damage results from a spectrum of nonalcoholic fatty liver disease ranging from steatosis to fibrosis and possible cirrhosis. US, CT, and MRI are useful in assessing steatosis and can be performed to detect and grade hepatic fibrosis, particularly using elastography techniques. Metabolic syndrome also has deleterious effects on the pancreas, kidney, gastrointestinal tract, and ovaries, including increased risk for several malignancies. Metabolic syndrome is associated with cerebral infarcts, best evaluated with MRI, and has been linked with cognitive decline. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Pickhardt in this issue.

Association between visceral fat area and diabetic retinopathy among people with type 2 diabetes mellitus: a cross-sectional study in Ningbo, Zhejiang Province, China

Aim

The objective of this study is to investigate the relationship between visceral fat area (VFA) and diabetic retinopathy (DR) in the context of type 2 diabetes mellitus (T2DM) within Ningbo, China.

Methods

The data of a total of 3,707 subjects with T2DM treated at The First Affiliated Hospital of Ningbo University were enrolled. The existence and severity of diabetic retinopathy were assessed by employing the 45° two-field stereoscopic digital photography. Subjects were categorized into four distinct groups: those without DR (NDR), individuals with mild non-proliferative DR (mild NPDR), people with moderate non-proliferative DR (moderate NPDR), and those suffering from vision-threatening DR (VTDR). Bio-electrical impedance was employed to estimate the Visceral fat area (VFA). Multinomial logistic regression models were utilized to evaluate the association between VFA and DR.

Results

The mean VFA in patients without diabetic retinopathy (NDR) was notably lower compared to that of patients with diabetic retinopathy (DR) (85.21 ± 37.78 vs. 97.37 ± 44.58 cm2, p < 0.001). As the severity of DR increased, VFA increased gradually but insignificantly (94.41 ± 43.13 cm2, 96.75 ± 40.82 cm2, 100.84 ± 49.34 cm2, p = 0.294). After adjusting the confounding factors, there was an association identified between VFA and the occurrence of DR (OR = 1.020, 95% CI = 1.016-1.024). It showed that regardless of BMI, whether it's less than 25 kg/m2 or greater than or equal to 25 kg/m2, a higher VFA (≥100 cm2) level came with a higher prevalence of DR (p < 0.001).

Conclusion

The outcomes of this research indicate a modest association between VFA and the incidence of DR among Chinese patients who have been diagnosed with T2DM in Ningbo.

Direct deep learning-based survival prediction from pre-interventional CT prior to transcatheter aortic valve replacement

PURPOSE

To investigate survival prediction in patients undergoing transcatheter aortic valve replacement (TAVR) using deep learning (DL) methods applied directly to pre-interventional CT images and to compare performance with survival models based on scalar markers of body composition.

METHOD

This retrospective single-center study included 760 patients undergoing TAVR (mean age 81 ± 6 years; 389 female). As a baseline, a Cox proportional hazards model (CPHM) was trained to predict survival on sex, age, and the CT body composition markers fatty muscle fraction (FMF), skeletal muscle radiodensity (SMRD), and skeletal muscle area (SMA) derived from paraspinal muscle segmentation of a single slice at L3/L4 level. The convolutional neural network (CNN) encoder of the DL model for survival prediction was pre-trained in an autoencoder setting with and without a focus on paraspinal muscles. Finally, a combination of DL and CPHM was evaluated. Performance was assessed by C-index and area under the receiver operating curve (AUC) for 1-year and 2-year survival. All methods were trained with five-fold cross-validation and were evaluated on 152 hold-out test cases.

RESULTS

The CNN for direct image-based survival prediction, pre-trained in a focussed autoencoder scenario, outperformed the baseline CPHM (CPHM: C-index = 0.608, 1Y-AUC = 0.606, 2Y-AUC = 0.594 vs. DL: C-index = 0.645, 1Y-AUC = 0.687, 2Y-AUC = 0.692). Combining DL and CPHM led to further improvement (C-index = 0.668, 1Y-AUC = 0.713, 2Y-AUC = 0.696).

CONCLUSIONS

Direct DL-based survival prediction shows potential to improve image feature extraction compared to segmentation-based scalar markers of body composition for risk assessment in TAVR patients.

The association of radiologic body composition parameters with clinical outcomes in level-1 trauma patients

PURPOSE

The present study aims to assess whether CT-derived muscle mass, muscle density, and visceral fat mass are associated with in-hospital complications and clinical outcome in level-1 trauma patients.

METHODS

A retrospective cohort study was conducted on adult patients admitted to the University Medical Center Utrecht following a trauma between January 1 and December 31, 2017. Trauma patients aged 16 years or older without severe neurological injuries, who underwent a CT that included the abdomen within 7 days of admission, were included. An artificial intelligence (AI) algorithm was used to retrieve muscle areas to calculate the psoas muscle index and to retrieve psoas muscle radiation attenuation and visceral fat (VF) area from axial CT images. Multivariable logistic and linear regression analyses were performed to assess associations between body composition parameters and outcomes.

RESULTS

A total of 404 patients were included for analysis. The median age was 49 years (interquartile range [IQR] 30-64), and 66.6% were male. Severe comorbidities (ASA 3-4) were seen in 10.9%, and the median ISS was 9 (IQR 5-14). Psoas muscle index was not independently associated with complications, but it was associated with ICU admission (odds ratio [OR] 0.79, 95% confidence interval [CI] 0.65-0.95), and an unfavorable Glasgow Outcome Scale (GOS) score at discharge (OR 0.62, 95% CI 0.45-0.85). Psoas muscle radiation attenuation was independently associated with the development of any complication (OR 0.60, 95% CI 0.42-0.85), pneumonia (OR 0.63, 95% CI 0.41-0.96), and delirium (OR 0.49, 95% CI 0.28-0.87). VF was associated with developing a delirium (OR 1.95, 95% CI 1.12-3.41).

CONCLUSION

In level-1 trauma patients without severe neurological injuries, automatically derived body composition parameters are able to independently predict an increased risk of specific complications and other poor outcomes.

The neglected association between central obesity markers and abdominal aortic aneurysm presence: A systematic review and meta-analysis

Purpose

To review the association between central obesity and abdominal aortic aneurysm (AAA).

Materials and methods

The PubMed, Web of Sciences, Embase, The China national knowledge infrastructure (CNKI), and Cochrane Library were searched up to April 30, 2022. Researches includes investigation of the relationship between central obesity markers and AAA. Included studies must use recognized measures of central obesity, i.e., waist circumference (WC) and waist-to-hip ratio (WHR), or use imaging techniques to calculate abdominal fat distribution, such as computed tomography (CT) imaging.

Results

Eleven clinical researches were identified of which eight discussed the association between physical examination and AAA, and three studies mainly focused on abdominal fat volume (AFV). Seven researches concluded that there was a positive correlation between markers of central obesity and AAA. Three studies found no significant link between markers of central obesity and AAA. One of the remaining studies reported different results for each sex. Three studies pooled in a meta-analysis identified correlation between central obesity and AAA presence (RR = 1.29; 95% confidence interval, 1.14-1.46).

Conclusion

Central obesity plays a role in the risk of AAA. Standardized central obesity markers may be predictors of AAA. However, there was no association between abdominal fat volume and AAA. Additional relevant evidence and specific mechanisms warrant further study.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?IDCRD42022332519, identifier CRD42022332519.

Lipid accumulation product, visceral adiposity index and risk of chronic kidney disease

BACKGROUND

Lipid accumulation product (LAP) and visceral adiposity index (VAI) are novel, non-imaging markers of visceral adiposity that are calculated by using body mass index (BMI), waist circumference (WC) and serum lipid concentrations. We hypothesized that LAP and VAI are more strongly associated with adverse kidney outcomes than BMI and WC.

METHODS

Using data from the REasons for Geographic and Racial Differences in Stroke (REGARDS) study, we used multivariable logistic regression to evaluate associations of LAP, VAI, BMI and WC with incident chronic kidney disease (CKD), (incident eGFR < 60 ml/min/1.73m2 and > 25% decline).

RESULTS

Among the overall cohort of 27,550 participants, the mean baseline age was 65 years; 54% were women; and 41% were African American. After a median of 9.4 years (IQR 8.6, 9.9) of follow-up, a total of 1127 cases of incident CKD were observed. Each two-fold higher value of VAI (OR 1.12, 95% CI 1.04, 1.20), LAP (OR 1.21, 95% CI 1.13, 1.29), WC (OR 2.10, 95% CI 1.60, 2.76) and BMI (OR: 2.66, 95% CI 1.88, 3.77), was associated with greater odds of incident CKD.

CONCLUSIONS

LAP and VAI as measures of visceral adiposity are associated with higher odds of incident CKD but may not provide information beyond WC and BMI.

Development of automated segmentation of visceral adipose tissue in computed tomography

PURPOSE

Imaging modalities such as computed tomography (CT) or magnetic resonance imaging have been used to measure adiposity. However, manual segmentation of visceral adipose tissue (VAT) in the entire abdomen is laborious and time-consuming. We aimed to develop a new method for accurate visceral fat segmentation by automatically dividing the three anatomical compartments of the lung, soft tissue, and post-vertebral spaces.

METHODS

To automatically separate visceral fat, a three-step process was performed that sequentially divided tissues and regions in a three-dimensional CT image. Manual segmentation was performed in 99 individuals who underwent 18-fluoro-2-deoxyglucosepositron emission tomography/CT for cancer screening between January 2010 and December 2018 to validate the automated segmentation. The similarity index and Pearson's correlation analysis were performed to compare automated segmentation with manual segmentation. Clinical data, such as weight, height, and glucose and insulin levels, were measured. Pearson's correlation analysis was performed to investigate the association between the two methods.

RESULTS

VAT volume of automated segmentation (3,594.6 ± 1,776.5 cm³) strongly correlated with that of manual segmentation (3,375.7 ± 1567.5 cm³) (r = 0.9676, p < 0.0001). The similarity index positively correlated with the VAT volume (r = 0.6396, p < 0.0001) and negatively correlated with the mean Hounsfield units (HU) (r = -0.4328, p < 0.0001). Bland-Altman plots are presented with 5.1 % for VAT volume and 7.1 % for mean HU were outside 1.96 standard deviation from the mean value.

CONCLUSION

We developed an automated segmentation method for VAT in the entire abdomen. This automated segmentation method is feasible for measuring the VAT volume and VAT HU. This method could be employed in daily clinical practice to provide more detailed information about VAT.

AI-Supported Comprehensive Detection and Quantification of Biomarkers of Subclinical Widespread Diseases at Chest CT for Preventive Medicine

Automated image analysis plays an increasing role in radiology in detecting and quantifying image features outside of the perception of human eyes. Common AI-based approaches address a single medical problem, although patients often present with multiple interacting, frequently subclinical medical conditions. A holistic imaging diagnostics tool based on artificial intelligence (AI) has the potential of providing an overview of multi-system comorbidities within a single workflow. An interdisciplinary, multicentric team of medical experts and computer scientists designed a pipeline, comprising AI-based tools for the automated detection, quantification and characterization of the most common pulmonary, metabolic, cardiovascular and musculoskeletal comorbidities in chest computed tomography (CT). To provide a comprehensive evaluation of each patient, a multidimensional workflow was established with algorithms operating synchronously on a decentralized Joined Imaging Platform (JIP). The results of each patient are transferred to a dedicated database and summarized as a structured report with reference to available reference values and annotated sample images of detected pathologies. Hence, this tool allows for the comprehensive, large-scale analysis of imaging-biomarkers of comorbidities in chest CT, first in science and then in clinical routine. Moreover, this tool accommodates the quantitative analysis and classification of each pathology, providing integral diagnostic and prognostic value, and subsequently leading to improved preventive patient care and further possibilities for future studies.

Sex-specific Association of Primary Aldosteronism With Visceral Adiposity

Context

The association between primary aldosteronism and obesity, especially its sex difference, remains unknown.

Objective

To assess the association for each subtype of primary aldosteronism with obesity parameters including visceral adipose tissue and differences between sexes.

Methods

In this case-control study, 4 normotensive controls were selected for each case with primary aldosteronism. Multivariable conditional logistic regression models were used to estimate the association between each type of primary aldosteronism and obesity indicators. We used a random forest to identify which visceral or subcutaneous tissue areas had a closer association with disease status.

Results

The study subjects included 42 aldosterone-producing adenoma cases (22 women) and 68 idiopathic hyperaldosteronism cases (42 women). In multivariable conditional logistic regressions, aldosterone-producing adenoma was significantly associated with body mass index only in men (odds ratio [OR] [95% CI)], 4.62 [1.98-10.80] per 2.89 kg/m2) but not in women (OR [95% CI], 1.09 [0.69-1.72] per 3.93 kg/m2) compared with the matched controls, whereas idiopathic hyperaldosteronism was associated with body mass index in both men (OR [95% CI], 3.96 [2.03-7.73] per 3.75 kg/m2) and women (OR [95% CI], 2.65 [1.77-3.96] per 3.85 kg/m2) compared with the matched controls. In random forests, visceral adipose tissue areas were the better predictor of both aldosterone-producing adenoma and idiopathic hyperaldosteronism than subcutaneous adipose tissue.

Conclusions

Aldosterone-producing adenoma cases were obese among men, but not among women. Idiopathic hyperaldosteronism cases were obese among both men and women. Visceral adipose tissue may contribute to the pathophysiology of primary aldosteronism.

The site of waist measurement impacts the estimation of visceral fat: results from three-dimensional photonic body scanning

Currently, various protocols regarding the site of waist circumference (WC) measurement are in place. This study aimed to analyse the effect of the site of WC measurement on visceral adipose tissue (VAT) estimation. WC was obtained at 7 anatomical sites in 211 German volunteers (103 males) aged 23-81 years using three-dimensional photonic body scanning (PBS). At one site, WC was additionally measured by tape. The quantity of VAT was assessed by MRI. Models to estimate VAT based on WC were developed; the precision of the estimation is represented by R². The influence of the applied method of WC assessment (tape v. PBS) on the estimations is reported. Results show that the amount of estimated VAT and the precision of VAT estimation were dependent on the site of measurement. VAT was estimated most precisely by WC taken at the level of the lowest rib (WC_rib: R² = 0·75 females; 0·79 males), the minimum circumference (WC_min: R² = 0·75 females; 0·77 males) and at the narrowest part of the torso (WC_nar: R² = 0·76 females; 0·77 males), and least precisely by WC assessed at the top of iliac crest (WC_iliac: R² = 0·61 females; 0·60 males). VAT estimates based on WC obtained by PBS were smaller and estimations were slightly less precise compared to estimates based on tape measures. Our results indicate that the method and the site of waist measurement should be considered when estimating VAT based on WC. The implementation of a standardised protocol using either WC_rib, WC_min or WC_nar could improve the precision of VAT estimation.

Standardized measurement of abdominal muscle by computed tomography: association with cardiometabolic risk in the Framingham Heart Study

Objectives

To provide a standard for total abdominal muscle mass (TAM) quantification on computed tomography (CT) and investigate its association with cardiovascular risk in a primary prevention setting.

Methods

We included 3016 Framingham Heart Study participants free of cardiovascular disease (CVD) who underwent abdominal CT between 2002 and 2005. On a single CT slice at the level of L3/L4, we segmented (1) TAM-Area, (2) TAM-Index (= TAM-Area/height) and, (3) TAM-Fraction (= TAM-Area/total cross-sectional CT-area). We tested the association of these muscle mass measures with prevalent and incident cardiometabolic risk factors and incident CVD events during a follow-up of 11.0 ± 2.7 years.

Results

In this community-based sample (49% women, mean age: 50.0 ± 10.0 years), all muscle quantity measures were significantly associated with prevalent and incident cardiometabolic risk factors and CVD events. However, only TAM-Fraction remained significantly associated with key outcomes (e.g., adj. OR 0.68 [0.55, 0.84] and HR 0.73 [0.57, 0.92] for incident hypertension and CVD events, respectively) after adjustment for age, sex, body mass index, and waist circumference. Moreover, only higher TAM-Fraction was associated with a lower risk (e.g., adj. OR: 0.56 [0.36–0.89] for incident diabetes versus TAM-Area: adj. OR 1.26 [0.79–2.01] and TAM-Index: 1.09 [0.75–1.58]).

Conclusion

TAM-Fraction on a single CT slice at L3/L4 is a novel body composition marker of cardiometabolic risk in a primary prevention setting that has the potential to improve risk stratification beyond traditional measures of obesity.

Key Points

• In this analysis of the Framingham Heart Study (n = 3016), TAM-F on a single slice CT was more closely associated with prevalent and incident cardiometabolic risk factors as compared to TAM alone or TAM indexed to body surface area.

• TAM-F on a single abdominal CT slice at the level of L3/L4 could serve as a standard measure of muscle mass and improve risk prediction

Subcutaneous and visceral adipose tissue in patients with primary and recurrent incisional hernia

PURPOSE

Visceral obesity rather than body mass index has been reported to be associated with a higher incidence of incisional hernias. The aim of this study was to examine the relationship between CT measured adipose tissue and muscle in primary and recurrent incisional hernia.

METHODS

Patients with a 'Primary' or 'Recurrent incisional hernia' were obtained from a prospective cohort of patients who were being assessed for incisional hernia repair over a 2-year period. Computerised tomography (CT)-images were analysed using NIH Image-J software to quantify adipose tissue and skeletal muscle cross-sectional areas at the level of lumber vertebra 3/4 using standard Hounsfield units. To test inter-observer 'absolute agreement', each parameter was measured independently by two investigators and reliability analysis performed.

RESULTS

Thirty-six patients were included in the study: 15 had a Primary while 21 had a Recurrent incisional hernia. Both groups had similar baseline characteristics. Reliability analysis for CT-measured areas showed very high interclass correlation coefficient (ICC) between observers. Patients in the recurrent group had significantly greater subcutaneous adipose tissue (SAT) [median = 321.9cm2 vs 230.9cm2, p = 0.04] and visceral adipose tissue (VAT) [median = 221.1cm2 vs 146.8cm2, p = 0.03] than those in the primary group. There was no difference in skeletal muscle areas for right [median = 2.8cm2 vs 2.9cm2] and left [median = 3.7cm2 vs 4.1cm2] rectus muscles between groups.

CONCLUSION

Our study shows that patients with a recurrent incisional hernia have significantly more subcutaneous and visceral adipose tissue than those with a primary incisional hernia. Further studies in this area are required if we are to reduce the burden of recurrent hernia following repair of a primary incisional hernia.

Associations of Body Fat Distribution and Cardiometabolic Risk of Testicular Cancer Survivors after Cisplatin-Based Chemotherapy

Background

It is unknown how body fat distribution modulates the cardiometabolic risk of testicular cancer survivors (TCSs) after cisplatin-based chemotherapy.

Methods

For 455 patients enrolled in The Platinum Study at Memorial Sloan Kettering Cancer Center, visceral (VAT) and subcutaneous (SAT) adipose tissue was quantified on pre-chemotherapy CT. VAT/SAT ratio was calculated as a quantitative measure of central adiposity. Endpoints were incidence of new post-chemotherapy cardiometabolic disease (new antihypertensive, lipid-lowering, or diabetes medication), and post-chemotherapy Framingham risk scores. Cox models and linear regression with interaction terms were applied. Post-chemotherapy body fat distribution was analyzed in 108 patients. All statistical tests were 2-sided.

Results

Baseline median age was 31 years (IQR = 26, 39), BMI 26 kg/m2 (IQR: 24, 29), and VAT/SAT ratio 0.49 (IQR: 0.31, 0.75). Median follow-up was 26 months (IQR: 16, 59). Higher pre-chemotherapy VAT/SAT ratios inferred a higher likelihood of new cardiometabolic disease among patients with BMI ≥30 kg/m2 (age-adjusted HR = 3.14, 95% CI = 1.02–9.71, p = 0.047), but not other BMI groups. Pre-chemotherapy VAT/SAT ratio was associated with post-chemotherapy Framingham risk scores in univariate regression analysis (exp(β)-estimate: 2.10, 95% CI: 1.84, 2.39, p &lt; 0.001); in a multivariate model, this association was stronger in younger versus older individuals. BMI increased in most patients after chemotherapy and correlated with increases in VAT/SAT (Spearman r = 0.39; p &lt; 0.001).

Conclusions

In TCSs, central adiposity is associated with increased cardiometabolic risk after cisplatin-based chemotherapy, particularly in obese or young men. Weight gain after chemotherapy occurs preferentially in the visceral compartment, providing insight into the pathogenesis of cardiovascular disease in this population.

Exploring the Impact of the Obesity Paradox on Lung Cancer and Other Malignancies

Simple Summary

Studies have shown that obesity is associated with many adverse health effects, including worse cancer outcomes. Many studies paradoxically suggest a survival benefit for obesity in treatment outcomes of cancers such as non-small-cell lung cancer. This relationship is not seen in animal models. We hypothesize that this relationship is secondary to suboptimal quantification of adiposity, enhanced immunotherapy response, and variables such as sex, medications, and smoking status. There are many ways to measure and classify adiposity, but the ability to distinguish abdominal obesity is likely key in predicting accurate prognosis. There are many ways obesity impacts cancer treatment course from diagnosis to survivorship. In this paper, we aim to analyze the factors contributing to the obesity paradox and its effect on lung cancer. This can aid the treatment and prognosis of lung cancer and may support further research into obesity-specific impacts on this malignancy.

Abstract

There is a paradoxical relationship between obesity, as measured by BMI, and many types of cancer, including non-small-cell lung cancer. Obese non-small-cell lung cancer patients have been shown to fare better than their non-obese counterparts. To analyze the multifaceted effects of obesity on oncologic outcomes, we reviewed the literature on the obesity paradox, methods to measure adiposity, the obesity-related derangements in immunology and metabolism, and the oncologic impact of confounding variables such as gender, smoking, and concomitant medications such as statins and metformin. We analyzed how these aspects may contribute to the obesity paradox and cancer outcomes with a focus on lung cancer. We concluded that the use of BMI to measure adiposity is limited and should be replaced by a method that can differentiate abdominal obesity. We also concluded that the concomitant metabolic and immunologic derangements caused by obesity contribute to the obesity paradox. Medications, gender, and smoking are additional variables that impact oncologic outcomes, and further research needs to be performed to solidify the mechanisms.

Percentile-based averaging and skeletal muscle gauge improve body composition analysis: validation at multiple vertebral levels

BACKGROUND

Skeletal muscle metrics on computed tomography (CT) correlate with clinical and patient-reported outcomes. We hypothesize that aggregating skeletal muscle measurements from multiple vertebral levels and skeletal muscle gauge (SMG) better predict outcomes than skeletal muscle radioattenuation (SMRA) or -index (SMI) at a single vertebral level.

METHODS

We performed a secondary analysis of prospectively collected clinical (overall survival, hospital readmission, time to unplanned hospital readmission or death, and readmission or death within 90 days) and patient-reported outcomes (physical and psychological symptom burden captured as Edmonton Symptom Assessment Scale and Patient Health Questionnaire) of patients with advanced cancer who experienced an unplanned admission to Massachusetts General Hospital from 2014 to 2016. First, we assessed the correlation of skeletal muscle cross-sectional area, SMRA, SMI, and SMG at one or more of the following thoracic (T) or lumbar (L) vertebral levels: T5, T8, T10, and L3 on CT scans obtained ≤50 days before index assessment. Second, we aggregated measurements across all available vertebral levels using percentile-based averaging (PBA) to create the average percentile. Third, we constructed one regression model adjusted for age, sex, sociodemographic factors, cancer type, body mass index, and intravenous contrast for each combination of (i) vertebral level and average percentile, (ii) muscle metrics (SMRA, SMI, & SMG), and (iii) clinical and patient-reported outcomes. Fourth, we compared the performance of vertebral levels and muscle metrics by ranking otherwise identical models by concordance statistic, number of included patients, coefficient of determination, and significance of muscle metric.

RESULTS

We included 846 patients (mean age: 63.5 ± 12.9 years, 50.5% males) with advanced cancer [predominantly gastrointestinal (32.9%) or lung (18.9%)]. The correlation of muscle measurements between vertebral levels ranged from 0.71 to 0.84 for SMRA and 0.67 to 0.81 for SMI. The correlation of individual levels with the average percentile was 0.90-0.93 for SMRA and 0.86-0.92 for SMI. The intrapatient correlation of SMRA with SMI was 0.21-0.40. PBA allowed for inclusion of 8-47% more patients than any single-level analysis. PBA outperformed single-level analyses across all comparisons with average ranks 2.6, 2.9, and 1.6 for concordance statistic, coefficient of determination, and significance (range 1-5, μ = 3), respectively. On average, SMG outperformed SMRA and SMI across outcomes and vertebral levels: the average rank of SMG was 1.4, 1.4, and 1.4 for concordance statistic, coefficient of determination, and significance (range 1-3, μ = 2), respectively.

CONCLUSIONS

Multivertebral level skeletal muscle analyses using PBA and SMG independently and additively outperform analyses using individual levels and SMRA or SMI.

Gut Microbiome Alterations in Patients With Visceral Obesity Based on Quantitative Computed Tomography

The gut microbiota is crucial in the pathogenesis of obesity. Abdominal obesity is known to significantly increase the risk of metabolic syndrome and cardiovascular disease, so further study is needed to investigate the changes of intestinal microorganisms in patients with excessive visceral fat. In our study, 41 people (n = 41) with normal body mass index (BMI) (18.5 ≤ BMI < 23.9) were included and divided into the low visceral fat area (L-VFA) group (n = 23, VFA < 100 cm2) and the high visceral fat area (H-VFA) group (n = 18, VFA ≥ 100 cm2). Several clinical indicators of the H-VFA group were significantly higher than those of the L-VFA group, including the waist circumference (WC), the fasting blood glucose (FBG), the triglyceride (TG), the total cholesterol (TC), the low-density lipoprotein cholesterol (LDL), the serum uric acid (SUA), the white blood cell count (WBC), the blood neutrophil count (NEC), and the blood lymphocyte count (LYC). Using whole-genome shotgun sequencing, we found that the types of the intestinal microbiota of H-VFA patients were different from those of the L-VFA patients, with 18 bacteria enriched in the H-VFA group and nine bacteria in the L-VFA group. A total of 16 species of gut microbes showed a strong correlation with VFA, and Escherichia coli has the strongest correlation, followed by Mitsuokella unclassified, Bifidobacterium longum, Escherichia unclassified, Ruminococcus torques, Dialister succinatiphilus, Eubacterium hallii, and Ruminococcus gnavus. Compared to the VFA, only two species show a strong correlation with BMI and WC. Further functional genetic studies suggested that the degradation of short-chain fatty acids (SCFAs) and the generation of lipopolysaccharide (LPS) might be related to visceral fat accumulation. Together, visceral fat was more closely correlated with the gut microbiome compared with BMI and WC. It suggested an intrinsic connection between the gut microbiome and visceral fat and its related metabolic disorders. Specific microbial species and pathways associated with visceral fat accumulation might contribute to new targeted therapies for visceral fat and its metabolic disorders.

Association between visceral adipose tissue volume, measured using computed tomography, and cardio-metabolic risk factors

We evaluated the associations between metabolic parameters with visceral adipose tissue (VAT) volume in women with prediabetes or type 2 diabetes (T2DM), and we compared the VAT volume with the VAT area. We enrolled women aged > 20 years with prediabetes or T2DM, who underwent oral glucose tolerance test and whose VAT was evaluated using computed tomography (CT) at our institution between 2017 and 2019. All participants underwent unenhanced spiral CT with a 3-mm slice thickness from the level of the diaphragm to the level of the mid-thigh. The two VAT areas were defined as the free drawn area on the levels of the umbilicus and L2 vertebra. The VAT areas were also manually drawn from the level of the diaphragm to the level of the pelvic floor and were used to calculate the VAT volumes by summing all areas with a slice thickness of 3 mm after setting the attenuation values from -45 to -195 Hounsfield Unit. All metabolic characteristics, except blood pressure, were significantly correlated with the VAT volume. The VAT areas measured at the level of the L2 vertebra and umbilicus were correlated with serum triglyceride, high-density lipoprotein cholesterol, and Framingham steatosis index alone. Multivariable regression analyses revealed that the VAT volume was significantly associated with several metabolic parameters. In conclusion, in women with prediabetes and T2DM, the VAT volume acquired from CT-based calculation has more significant correlations with metabolic risk factors compared with the VAT area.

The Optimal Axial Anatomical Site for a Single-Slice Area to Quantify the Total Volume of Visceral Adipose Tissue in Quantitative CT

PURPOSE

Determine the association between cross-sectional visceral adipose tissue (VAT) area of different anatomic locations and total abdominopelvic VAT volume; identify the optimal measurement site in a single-slice to quantify the total VAT volume.

METHOD

Participants who underwent non-contrast abdominal scan by quantitative CT (QCT) were enrolled from May 2021 to October 2021. The VAT area (cm²) at different anatomic sites as upper-pole, lower-pole, and hilum of the kidney, intervertebral disc of L2/L3 and L5/S1, and umbilical level were measured on QCT PRO BMD workstation (Mindways QCT PRO workstation). The total VAT volume (cm³) from the upper pole of kidney to the L5/S1 intervertebral disc of the pelvis (abdominopelvic region) was obtained by using Siemens Healthineers Syngo via Frontier cardiac risk assessment. Regression models were used to identify the optimal single-slice in different gender for estimating VAT volume. Statistical significance was established at P < 0.05.

RESULTS

Total of 311 Chinese participants including 179 men [age, 55.1 ± 14.9 years; body mass index (BMI), 24.2 ± 3.2 kg/m²; total VAT volume, 2482.6 ± 1276.5 mL] and 132 women [age, 54.3 ± 14.9; BMI, 23.5 ± 2.9; total VAT volume, 1761.5 ± 876.4]. Pearson's correlation analysis revealed a strong association between the VAT area and total abdominopelvic VAT volume at the hilum of the kidney in both men (r=0.938, P<0.001) and women (r=0.916, P<0.001). Adjust for covariates including age, BMI, and waist circumference make a relatively small effect on predicting the total VAT volume.

CONCLUSIONS

Measurement of cross-sectional areas at the hilum of the kidney in both genders showed a strongest relation to TVAT volume. Our results may provide an identifiable and valuable axial landmark for measuring visceral adipose tissue in clinical practice.

Relationship Between Body Composition and Death in Patients with COVID-19 Differs Based on the Presence of Gastrointestinal Symptoms

BACKGROUND

Patients with SARS-CoV-2 who present with gastrointestinal symptoms have a milder clinical course than those who do not. Risk factors for severe COVID-19 disease include increased adiposity and sarcopenia.

AIMS

To determine whether body composition risk factors are associated with worse outcomes among patients with gastrointestinal symptoms.

METHODS

This was a retrospective study of hospitalized patients with COVID-19 who underwent abdominal CT scan for clinical indications. Abdominal body composition measures including skeletal muscle index (SMI), intramuscular adipose tissue index (IMATI), visceral adipose tissue index (VATI), subcutaneous adipose tissue index (SATI), visceral-to-subcutaneous adipose tissue ratio (VAT/SAT ratio), and liver and spleen attenuation were collected. The association between body composition measurements and 30-day mortality was evaluated in patients with and without gastrointestinal symptoms at the time of positive SARS-CoV-2 test.

RESULTS

Abdominal CT scans of 190 patients with COVID-19 were evaluated. Gastrointestinal symptoms including nausea, vomiting, diarrhea, or abdominal pain were present in 117 (62%). Among patients without gastrointestinal symptoms, those who died had greater IMATI (p = 0.049), less SMI (p = 0.010), and a trend toward a greater VAT/SAT ratio. Among patients with gastrointestinal symptoms, those who died had significantly greater IMATI (p = 0.025) but no differences in other measures.

CONCLUSIONS

Among patients with COVID-19, those without gastrointestinal symptoms showed the expected associations between mortality and low SMI, high IMATI, and trend toward higher VAT/SAT ratio, but those with gastrointestinal symptoms did not. Future studies should explore the mechanisms for the altered disease course in patients with COVID-19 who present with gastrointestinal symptoms.

Impact of visceral fat on the prognosis of coronavirus disease 2019: an observational cohort study

Background

Clarification of the risk factors for coronavirus disease 2019 (COVID-19) severity is strongly warranted for global health. Recent studies have indicated that elevated body mass index (BMI) is associated with unfavorable progression of COVID-19. This is assumed to be due to excessive deposition of visceral adipose tissue (VAT); however, the evidence investigating the association between intra-abdominal fat and COVID-19 prognosis is sparse. We therefore investigated whether measuring the amount of intra-abdominal fat is useful to predict the prognosis of COVID-19.

Methods

The present study enrolled 53 consecutive cases of COVID-19 patients aged ≥ 20 years with chest computed tomography (CT) scans. The VAT area, total adipose tissue (TAT) area, and VAT/TAT ratio were estimated using axial CT images at the level of the upper pole of the right kidney. Severe COVID-19 was defined as death or acute respiratory failure demanding oxygen at ≥ 6 L per minute, a high-flow nasal cannula, or mechanical ventilation. The association of VAT/TAT with the incidence of progression to a severe state was estimated as a hazard ratio (HR) using Cox regression analysis. To compare the prediction ability for COVID-19 disease progression between BMI and VAT/TAT, the area under the receiver operating characteristic curve (AUC) of each was assessed.

Results

A total of 15 cases (28.3% of the whole study subjects) progressed to severe stages. The incidence of developing severe COVID-19 increased significantly with VAT/TAT (HR per 1% increase = 1.040 (95% CI 1.008–1.074), P = 0.01). After adjustment for potential confounders, the positive association of VAT/TAT with COVID-19 aggravation remained significant (multivariable-adjusted HR = 1.055 (95% CI 1.000–1.112) per 1% increase, P = 0.049). The predictive ability of VAT/TAT for COVID-19 becoming severe was significantly better than that of BMI (AUC of 0.73 for VAT/TAT and 0.50 for BMI; P = 0.0495 for the difference).

Conclusions

A higher ratio of VAT/TAT was an independent risk factor for disease progression among COVID-19 patients. VAT/TAT was superior to BMI in predicting COVID-19 morbidity. COVID-19 patients with high VAT/TAT levels should be carefully observed as high-risk individuals for morbidity and mortality.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06958-z.

Methodology, clinical applications, and future directions of body composition analysis using computed tomography (CT) images: A review

PURPOSE OF THE REVIEW

We aim to review the methods, current research evidence, and future directions in body composition analysis (BCA) with CT imaging.

RECENT FINDINGS

CT images can be used to evaluate muscle tissue, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) compartments. Manual and semiautomatic segmentation methods are still the gold standards. The segmentation of skeletal muscle tissue and VAT and SAT compartments is most often performed at the level of the 3rd lumbar vertebra. A decreased amount of CT-determined skeletal muscle mass is a marker of impaired survival in many patient populations, including patients with most types of cancer, some surgical patients, and those admitted to the intensive care unit (ICU). Patients with increased VAT are more susceptible to impaired survival / worse outcomes; however, those patients who are critically ill or admitted to the ICU or who will undergo surgery appear to be exceptions. The independent significance of SAT is less well established. Recently, the roles of the CT-determined decrease of muscle mass and increased VAT area and epicardial adipose tissue (EAT) volume have been shown to predict a more debilitating course of illness in patients suffering from severe acute respiratory syndrome coronavirus 2 (COVID-19) infection.

SUMMARY

The field of CT-based body composition analysis is rapidly evolving and shows great potential for clinical implementation.

Postmenopausal Chinese-Singaporean Women Have a Higher Ratio of Visceral to Subcutaneous Adipose Tissue Volume than Caucasian Women of the Same Age and BMI

Central fat accumulation is a significant determinant of cardio-metabolic health risk, known to differ between ethnically distinct human populations. Despite evidence for preferential central adiposity in Asian populations, the proportional distribution between the subcutaneous and visceral compartments in Chinese postmenopausal women has not been thoroughly investigated. For this analysis, volumetrically quantified subcutaneous and visceral adipose tissue (SAT, VAT) in the pelvic and abdominal regions of postmenopausal Asian (Chinese-Singaporean) and Caucasian (German) women matched for age and Body Mass Index (BMI) was undertaken, to examine such differences between the two groups. Volumes were calculated from segmentations of magnetic resonance imaging datasets of the abdomen and pelvis. Despite SAT, VAT, and the corresponding total adipose tissue (TAT) being similar between the groups, VAT/SAT and VAT/TAT were higher in the Asian group (by 24.5% and 18.2%, respectively, each p = 0.02). Further, VAT/SAT and VAT/TAT were positively correlated with BMI in the Caucasian group only (p = 0.02 and p = 0.01, respectively). We concluded that VAT is proportionally higher in the non-obese Asian women, compared to the Caucasian women of matched age and BMI. This conclusion is in agreement with existing literature showing higher abdominal adiposity in Asian populations. Additionally, in the Asian group, BMI did not correlate with visceral adiposity on a significant level. Further analysis is required to examine the extent to which this increased VAT may impact cardio-metabolic health. There is, however, a need to emphasize healthy lifestyle behaviors in non-obese post-menopausal women of Chinese ancestry.

How much abdominal fat do obese patients lose short term after laparoscopic sleeve gastrectomy? A quantitative study evaluated with MRI

Background

This study aimed to elucidate the changes in the amount of abdominal adipose tissue after laparoscopic sleeve gastrectomy in obese Chinese patients over a relatively short follow-up period and to analyze the differences in the effects of surgery between genders.

Methods

Ninety-one patients were enrolled in the study, including 18 males and 73 females. These patients underwent laparoscopic sleeve gastrectomy between November 2017 and November 2019. Before and short term after surgery, the areas of subcutaneous/visceral adipose tissue and the liver proton density fat fraction were calculated with upper abdominal magnetic resonance (MR) examinations.

Results

Approximately 100 days after surgery, the median values of weight loss and body mass index reduction were 23.1 kg and 8.1 kg/m², respectively. The patients achieved a greater absolute loss of subcutaneous adipose tissue index than of visceral adipose tissue index (3.2×10^-3 vs. 1.6×10^-3, P<0.001). The amount of weight loss, body mass index loss and absolute/relative reduction in visceral adipose tissue index were much greater in males than in females (31.7 vs. 21.7 kg, P<0.001; 9.8 vs. 7.9 kg/m², P=0.016; 2.5×10^-3 vs. 1.3×10^-3, P=0.007; 28.2% vs. 20.9%, P=0.029). There was a correlation between decreased amounts in subcutaneous and visceral adipose tissue in sum and weight loss (r=0.282, P=0.032). The absolute/relative reduction in visceral adipose tissue index was also correlated with absolute/relative reduction in liver proton density fat fraction (r=0.283, P=0.013; r=0.372, P=0.001).

Conclusions

The reductions in body weight and visceral fat were more significant in male patients. The sum of absolute reduction in subcutaneous and visceral fat deposits was correlated with weight loss, in all patients enrolled. For severely obese patients, an upper abdominal MR examination could assess the body tissue composition and how it changes after bariatric surgery.

Comparison of Body Composition, Strength, and Physical Performance Measurements Between Healthy Participants and Hemodialysis Patients

Purpose

This study evaluated the difference in physical performance tests, strength, and total and regional mass using a comprehensive dataset between maintenance hemodialysis (HD) patients and a healthy population.

Patients and Methods

A total of 84 HD patients were enrolled. We selected 42 healthy participants (HPs) age- and sex-matched to the 84 HD patients as controls. Collected data were sex, age, body mass index (BMI), laboratory findings, total and regional measurements for lean mass or fat mass, thigh muscle area (TMA), handgrip strength, and physical performance measurements.

Results

There were no significant differences in BMI, total lean mass, or total fat mass including regional fat mass between the two groups. Lean leg mass and TMA were greater in HPs than in HD patients. All measurements of physical performance, including handgrip strength, were better in HPs than in HD patients. A multivariate analysis of lean leg mass, TMA, and physical performance measures had similar results to the same data studied with a univariate analysis.

Conclusion

We demonstrated that HD patients had decreased physical performance and strength compared to HPs. The difference in leg muscle mass was most prominent among the total and regional body compositions between HPs and HD patients.

Segmentation and characterization of visceral and abdominal subcutaneous adipose tissue on CT with and without contrast medium: influence of 2D- and 3D-segmentation

Background

Adipose tissue is a valuable biomarker. Although validation and correlation to clinical data have mostly been performed on non-enhanced scans (NES), a previous study has shown conversion of values of contrast enhanced scan (CES) into those of NES to be feasible with segmentation of the entire abdomen (3D-segmentation). In this study we analyzed if density and area of abdominal adipose tissue segmented in a single slice (2D-segmentation) of CES may be converted into that of NES. Furthermore, we compared the precision of conversion between 2D- and 3D-segmentation.

Methods

Thirty-one multi-phasic abdominal CT examinations at identical scan settings were retrospectively included. Exams included NES (n=31), arterial (ART) (n=23), portal-venous (PVN) (n=10), and/or venous scan (VEN) (n=31). Density and area of visceral (VAT) and subcutaneous adipose tissue (SAT) were quantified semi-automatically with fixed thresholds. For conversion of values from CES into those of NES regression analyses were performed and tested. 2D- and 3D-segmentation were compared with respect to conversion accuracy (normalized deviations of converted NES values from original measurements).

Results

After the application of contrast medium 2D-segmented adipose tissue increased in density (max. +5.6±2.4 HU) and decreased in area (max. -10.91%) (10.47%), with few exceptions (P<0.05). This was more pronounced in later scans (VEN ≈ PVN > ART) and more marked in VAT than SAT. Density and area in CES correlated very well with NES, allowing for conversion with only small error. While converted density is slightly more precise applying 3D-segmentation, conversion error of quantity was occasionally smaller with 2D-segmentation.

Conclusions

Contrast medium changes density and quantity of segmented adipose tissue in differing degrees between compartments, contrast phases and 2D- and 3D-segmentation. However, changes are fairly constant for a given compartment, contrast phase and mode of segmentation. Therefore, conversion of values into those of NES may be achieved with comparable precision for 2D- and 3D-segmentation.

MRI-Derived Subcutaneous and Visceral Adipose Tissue Reference Values for Children Aged 6 to Under 18 Years

The assessment of body composition in pediatric population is essential for proper nutritional support during hospitalization. However, currently available methods have limitations. This study aims to propose a novel approach for nutrition status assessment and introduce magnetic resonance imaging (MRI)-derived subcutaneous and visceral fat normative reference values. A total of 262 healthy subjects aged from 6 to 18 years underwent MRI examinations and anthropometric measurements. MRI images at the second lumbar vertebrae were used by two radiologists to perform the semi-automatic tissue segmentation. Based on obtained adipose tissue surface areas and body mass index (BMI) scores sex-specific standard percentile curves (3rd, 10th, 25th, 50th, 75th, 90th, 97th) and z-scores were constructed using LMS method. Additionally, 85th and 95th centiles of subcutaneous and visceral adipose tissue were proposed as equivalents of overweight and obesity. Bland-Altman plots revealed an excellent intra-observer reproducibility and inter-observer agreement. In conclusion, our findings demonstrate highly reproducible method and suggest that MRI-derived reference values can be implemented in clinical practice.

End-to-end automated body composition analyses with integrated quality control for opportunistic assessment of sarcopenia in CT

OBJECTIVES

To develop a pipeline for automated body composition analysis and skeletal muscle assessment with integrated quality control for large-scale application in opportunistic imaging.

METHODS

First, a convolutional neural network for extraction of a single slice at the L3/L4 lumbar level was developed on CT scans of 240 patients applying the nnU-Net framework. Second, a 2D competitive dense fully convolutional U-Net for segmentation of visceral and subcutaneous adipose tissue (VAT, SAT), skeletal muscle (SM), and subsequent determination of fatty muscle fraction (FMF) was developed on single CT slices of 1143 patients. For both steps, automated quality control was integrated by a logistic regression model classifying the presence of L3/L4 and a linear regression model predicting the segmentation quality in terms of Dice score. To evaluate the performance of the entire pipeline end-to-end, body composition metrics, and FMF were compared to manual analyses including 364 patients from two centers.

RESULTS

Excellent results were observed for slice extraction (z-deviation = 2.46 ± 6.20 mm) and segmentation (Dice score for SM = 0.95 ± 0.04, VAT = 0.98 ± 0.02, SAT = 0.97 ± 0.04) on the dual-center test set excluding cases with artifacts due to metallic implants. No data were excluded for end-to-end performance analyses. With a restrictive setting of the integrated segmentation quality control, 39 of 364 patients were excluded containing 8 cases with metallic implants. This setting ensured a high agreement between manual and fully automated analyses with mean relative area deviations of ΔSM = 3.3 ± 4.1%, ΔVAT = 3.0 ± 4.7%, ΔSAT = 2.7 ± 4.3%, and ΔFMF = 4.3 ± 4.4%.

CONCLUSIONS

This study presents an end-to-end automated deep learning pipeline for large-scale opportunistic assessment of body composition metrics and sarcopenia biomarkers in clinical routine.

KEY POINTS

• Body composition metrics and skeletal muscle quality can be opportunistically determined from routine abdominal CT scans. • A pipeline consisting of two convolutional neural networks allows an end-to-end automated analysis. • Machine-learning-based quality control ensures high agreement between manual and automatic analysis.

Brown adipose tissue is associated with healthier body fat distribution and metabolic benefits independent of regional adiposity

The association of brown adipose tissue (BAT) and body fat distribution and their combined effects on metabolic health in humans remains unknown. Here, we retrospectively identify individuals with and without BAT on ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET)/computed tomography (CT) and assemble a propensity score-matched study cohort to compare body fat distribution and determine its role in mediating the benefits of brown fat. We find that BAT is associated with lower amounts of visceral adipose tissue and higher amounts of subcutaneous adipose tissue, resulting in less central obesity. In addition, BAT is independently associated with lower blood glucose and white blood cell count, improved lipids, lower prevalence of type 2 diabetes mellitus, and decreased liver fat accumulation. These observations are most prominent in individuals with central obesity. Our results support a role of BAT in protection from visceral adiposity and improved metabolic health.

Brown adipose tissue is associated with more subcutaneous and less visceral fat

Brown adipose tissue is associated with health independent of fat distribution

Brown adipose tissue is associated with less liver fat and type 2 diabetes

Brown adipose tissue is most beneficial in individuals with central obesity

Pancreatic enzymes and abdominal adipose tissue distribution in new-onset prediabetes/diabetes after acute pancreatitis

BACKGROUND

New-onset prediabetes/diabetes after acute pancreatitis (NODAP) is the most common sequela of pancreatitis, and it differs from type 2 prediabetes/diabetes mellitus (T2DM).

AIM

To study the associations between circulating levels of pancreatic amylase, pancreatic lipase, chymotrypsin and fat phenotypes in NODAP, T2DM, and health.

METHODS

Individuals with NODAP (n = 30), T2DM (n = 30), and sex-matched healthy individuals (n = 30) were included. Five fat phenotypes (intra-pancreatic fat, liver fat, skeletal muscle fat, visceral fat, and subcutaneous fat) were determined using the same magnetic resonance imaging protocol and scanner magnet strength for all participants. One-way analysis of covariance, linear regression analysis, and relative importance analysis were conducted.

RESULTS

Intra-pancreatic fat deposition (IPFD) was higher in NODAP (9.4% ± 1.8%) and T2DM (9.8% ± 1.1%) compared with healthy controls (7.8% ± 1.9%) after adjusting for covariates (P = 0.003). Similar findings were observed in regards to visceral fat volume (P = 0.005), but not subcutaneous fat volume, liver fat, or skeletal muscle fat. Both IPFD (β = -2.201, P = 0.023) and visceral fat volume (β = -0.004, P = 0.028) were significantly associated with circulating levels of pancreatic amylase in NODAP, but not in T2DM or healthy individuals. Of the five fat phenotypes, IPFD explained the highest amount of variance in pancreatic amylase concentration (R² = 15.3% out of 41.2%). None of the phenotypes contributed meaningfully to the variance in pancreatic lipase or chymotrypsin.

CONCLUSION

Both NODAP and T2DM are characterized by increased IPFD and visceral fat volume. However, only NODAP is characterized by significant inverse associations between the two fat phenotypes and pancreatic amylase.

Genetic architecture of 11 organ traits derived from abdominal MRI using deep learning

Cardiometabolic diseases are an increasing global health burden. While socioeconomic, environmental, behavioural, and genetic risk factors have been identified, a better understanding of the underlying mechanisms is required to develop more effective interventions. Magnetic resonance imaging (MRI) has been used to assess organ health, but biobank-scale studies are still in their infancy. Using over 38,000 abdominal MRI scans in the UK Biobank, we used deep learning to quantify volume, fat, and iron in seven organs and tissues, and demonstrate that imaging-derived phenotypes reflect health status. We show that these traits have a substantial heritable component (8-44%) and identify 93 independent genome-wide significant associations, including four associations with liver traits that have not previously been reported. Our work demonstrates the tractability of deep learning to systematically quantify health parameters from high-throughput MRI across a range of organs and tissues, and use the largest-ever study of its kind to generate new insights into the genetic architecture of these traits.

Visceral Obesity Promotes Lung Cancer Progression-Toward Resolution of the Obesity Paradox in Lung Cancer

INTRODUCTION

Although obesity is associated with adverse cancer outcomes in general, most retrospective clinical studies suggest a beneficial effect of obesity in NSCLC.

METHODS

Hypothesizing that this "obesity paradox" arises partly from the limitations of using body mass index (BMI) to measure obesity, we quantified adiposity using preoperative computed tomography images. This allowed the specific determination of central obesity as abdominal visceral fat area normalized to total fat area (visceral fat index [VFI]). In addition, owing to the previously reported salutary effect of metformin on high-BMI patients with lung cancer, metformin users were excluded. We then explored associations between visceral obesity and outcomes after surgical resection of stage I and II NSCLC. We also explored potential immunologic underpinnings of such association using complimentary analyses of tumor gene expression data from NSCLC tumors and the tumor transcriptome and immune microenvironment in an immunocompetent model of lung cancer with diet-induced obesity.

RESULTS

We found that in 513 patients with stage I and II NSCLC undergoing lobectomy, a high VFI is associated with decreased recurrence-free and overall survival. VFI was also inversely related to an inflammatory transcriptomic signature in NSCLC tumors, consistent with observations made in immunocompetent murine models wherein diet-induced obesity promoted cancer progression while exacerbating elements of immune suppression in the tumor niche.

CONCLUSIONS

In all, this study uses multiple lines of evidence to reveal the adverse effects of visceral obesity in patients with NSCLC, which align with those found in animal models. Thus, the obesity paradox may, at least in part, be secondary to the use of BMI as a measure of obesity and the confounding effects of metformin use.

Sex Differences in the Associations of Visceral Adipose Tissue and Cardiometabolic and Cardiovascular Disease Risk: The Framingham Heart Study

Background

Men and women are labeled as obese on the basis of a body mass index (BMI) using the same criterion despite known differences in their fat distributions. Subcutaneous adipose tissue and visceral adipose tissue (VAT), as measured by computed tomography, are advanced measures of obesity that closely correlate with cardiometabolic risk independent of BMI. However, it remains unknown whether prognostic significance of anthropometric measures of adiposity versus VAT varies in men versus women.

Methods and Results

In 3482 FHS (Framingham Heart Study) participants (48.1% women; mean age, 50.8±10.3 years), we tested the associations of computed tomography–based versus anthropometric measures of fat with cardiometabolic and cardiovascular disease (CVD) risk. Mean follow‐up was 12.7±2.1 years. In men, VAT, as compared with BMI, had a similar strength of association with incident cardiometabolic risk factors (eg, adjusted odds ratio [OR], 2.36 [95% CI, 1.84–3.04] versus 2.66 [95% CI, 2.04–3.47] for diabetes mellitus) and CVD events (eg, adjusted hazard ratio [HR], 1.32 [95% CI, 0.97–1.80] versus 1.74 [95% CI, 1.14–2.65] for CVD death). In women, however, VAT, when compared with BMI, conferred a markedly greater association with incident cardiometabolic risk factors (eg, adjusted OR, 4.51 [95% CI, 3.13–6.50] versus 2.33 [95% CI, 1.88–3.04] for diabetes mellitus) as well as CVD events (eg, adjusted HR, 1.85 [95% CI, 1.26–2.71] versus 1.19 [95% CI, 1.01–1.40] for CVD death).

Conclusions

Anthropometric measures of obesity, including waist circumference and BMI, adequately capture VAT‐associated cardiometabolic and cardiovascular risk in men but not in women. In women, abdominal computed tomography–based VAT measures permit more precise assessment of obesity‐associated cardiometabolic and cardiovascular risk.

Quantification of adipose tissues by Dual-Energy X-Ray Absorptiometry and Computed Tomography in colorectal cancer patients

BACKGROUND & AIMS

Excess adipose tissue may affect colorectal cancer (CRC) patients' disease progression and treatment. In contrast to the commonly used anthropometric measurements, Dual-Energy X-Ray Absorptiometry (DXA) and Computed Tomography (CT) can differentiate adipose tissues. However, these modalities are rarely used in the clinic despite providing high-quality estimates. This study aimed to compare DXA's measurement of abdominal visceral adipose tissue (VAT) and fat mass (FM) against a corresponding volume by CT in a CRC population. Secondly, we aimed to identify the best single lumbar CT slice for abdominal VAT. Lastly, we investigated the associations between anthropometric measurements and VAT estimated by DXA and CT.

METHODS

Non-metastatic CRC patients between 50-80 years from the ongoing randomized controlled trial CRC-NORDIET were included in this cross-sectional study. Corresponding abdominal volumes were acquired by Lunar iDXA and from clinically acquired CT examinations. Also, single CT slices at L2-, L3-and L4-level were obtained. Agreement between the methods was investigated using univariate linear regression and Bland-Altman plots.

RESULTS

Sixty-six CRC patients were included. Abdominal volumetric VAT and FM measured by DXA explained up to 91% and 96% of the variance in VAT and FM by CT, respectively. Bland-Altman plots demonstrated an overestimation of VAT by DXA compared to CT (mean difference of 76 cm³) concurrent with an underestimation of FM (mean difference of -319 cm³). A higher overestimation of VAT (p = 0.015) and underestimation of FM (p = 0.036) were observed in obese relative to normal weight subjects. VAT in a single slice at L3-level showed the highest explained variance against CT volume (R² = 0.97), but a combination of three slices (L2, L3, L4) explained a significantly higher variance than L3 alone (R² = 0.98, p < 0.006). The anthropometric measurements explained between 31-65% of the variance of volumetric VAT measured by DXA and CT.

CONCLUSIONS

DXA and the combined use of three CT slices (L2-L4) are valid to predict abdominal volumetric VAT and FM in CRC patients when using volumetric CT as a reference method. Due to the poor performance of anthropometric measurements we recommend exploring the added value of advanced body composition by DXA and CT integrated into CRC care.

Significance of Acquisition Parameters for Adipose Tissue Segmentation on CT Images

OBJECTIVE. CT-based body composition analysis quantifies skeletal muscle and adipose tissue. However, acquisition parameters and quality can vary between CT images obtained for clinical care, which may lead to unreliable measurements and systematic error. The purpose of this study was to estimate the influence of IV contrast medium, tube current-exposure time product, tube potential, and slice thickness on cross-sectional area (CSA) and mean attenuation of subcutaneous (SAT), visceral (VAT), and inter-muscular adipose tissue (IMAT). MATERIALS AND METHODS. We retrospectively analyzed 244 images from 105 patients. We applied semiautomated threshold-based segmentation to CTA, dual-energy CT, and CT images acquired as part of PET examinations. An axial image at the level of the third lumbar vertebral body was extracted from each examination to generate 139 image pairs. Images from each pair were obtained with the same scanner, from the same patient, and during the same examination. Each image pair varied in only one acquisition parameter, which allowed us to estimate the effect of the parameter using one-sample t or median tests and Bland-Altman plots. RESULTS. IV contrast medium application reduced CSA in each adipose tissue compartment, with percentage change ranging from -0.4% (p = .03) to -9.3% (p < .001). Higher tube potential reduced SAT CSA (median percentage change, -4.2%; p < .001) and VAT CSA (median percentage change, -2.8%; p = .001) and increased IMAT CSA (median percentage change, -5.4%; p = .001). Thinner slices increased CSA in the VAT (mean percentage change, 3.0%; p = .005) and IMAT (median percentage change, 17.3%; p < .001) compartments. Lower tube current-exposure time product had a variable effect on CSA (median percentage change, -3.2% for SAT [p < .001], -12.6% for VAT [p = .001], and 58.8% for IMAT [p < .001]). IV contrast medium and higher tube potential increased mean attenuation, with percentage change ranging from 0.8% to 1.7% (p < .05) and from 6.2% to 20.8% (p < .001), respectively. Conversely, thinner slice and lower tube current-exposure time product reduced mean attenuation, with percentage change ranging from -5.4% to -1.0% (p < .001) and from -8.7% to -1.8% (p < .001), respectively. CONCLUSION. Acquisition parameters significantly affect CSA and mean attenuation of adipose tissue. Details of acquisition parameters used for CT-based body composition analysis need to be scrutinized and reported to facilitate interpretation of research studies.

3D-segmentation and characterization of visceral and abdominal subcutaneous adipose tissue on CT: influence of contrast medium and contrast phase

Background

Adipose tissue as part of body composition analysis may serve as a powerful biomarker. Validation of segmented adipose tissue and correlation to clinical data has been performed on non-enhanced scans (NES). As many patients require a contrast enhanced scan (CES) for other aspects of clinical decision making, the utility of CES for body composition analysis would be most useful. Therefore, we analyzed the influence of iodinated contrast medium (ICM) and contrast phase on the characterization and segmentation of adipose tissue.

Methods

Exams of 31 patients undergoing multi-phasic CT at identical scan settings containing an NES were retrospectively included. In addition to NES, patients received an arterial (ART) (n=23), portal-venous (PVN) (n=10), and/or venous scan (VEN) (n=31) after intravenous injection of 90 mL ICM. Density and volume of adipose tissue were quantified semi-automatically with thresholds between -190 HU and -30 HU and recorded separately for visceral (VAT) and subcutaneous adipose tissue (SAT). Density and volume of total adipose tissue (TAT) were computed. For conversion of values from CES into those of NES regression analyses were performed and tested.

Results

Density of adipose tissue increased after application of ICM more on later scans (VEN ≈ PVN > ART) and more markedly in VAT than SAT (VAT > TAT > SAT). Except in SAT on ART, all changes were significant (P<0.001). Measured volume of adipose tissue decreased on all CES (VEN ≈ PVN > ART) (P<0.001), but only reached statistical significance for VAT and TAT (VAT > TAT) on all CES (P<0.05). Density and volume in CES correlate extremely well with NES and may be calculated from one another [root-mean-square error (RMSE): <6 HU; <0.85 dm³].

Conclusions

Density and volume of segmented adipose tissue are altered by the injection of ICM in differing degrees between compartments and contrast phases. However, as the effect of ICM is fairly constant for a given compartment and contrast phase, values may be converted into those of NES with relative precession. This conversion allows body composition analysis to be carried out also in contrast enhanced CT examinations, e.g., for risk stratification and the comparison of the obtained results to previous studies.

Toward a Routine Assessment of Visceral Adipose Tissue Volume from Computed Tomographic Data

OBJECTIVE

The study's aim was to determine to what extent total visceral adipose tissue (VAT) volume (V_VAT-T ) measured from segmented VAT areas (A_VAT ) on all axial computed tomography (CT) sections (thickness of 5 mm) between the diaphragm and pelvic floor can be predicted by the A_VAT of commonly selected landmark sections in patients with overweight or obesity.

METHODS

A total of 113 patients (31 females, 82 males) with images of full abdominopelvic coverage and proper image quality were included (BMI = 25.0-64.1 kg/m² , 29.5 ± 4.9 kg/m² ). Linear regression between A_VAT and V_VAT-T (reference) was used to determine approximate equations for VAT volume for all parameters (single sex, different anatomical landmarks or lumbar intervertebral disc spaces, one or five axial sections). Agreement was evaluated by the multivariate coefficient of determination and by the SD of the percentage difference (s_d% ) between the estimated VAT volume on one or five sections and V_VAT-T .

RESULTS

The V_VAT-T was 0.9 to 8.4 (3.8 ± 2.2) L for females and 2.7 to 11.7 (5.6 ± 2.1) L for males. Best agreement was found at L2-3 (s_d%  = 14.3%-15.5%) for females and at L1-2 or L2-3 (11.7%-12.4%) for males. Agreement at the umbilicus or the femoral heads was poor (20.2%-57.9%). Segmentation of one or five sections was substantially faster (11/70 seconds) than whole-abdomen processing (15 minutes).

CONCLUSIONS

V_VAT-T can be rapidly estimated by VAT segmentation of axial CT sections at sex-specific lumbar intervertebral disc spaces.

Visceral adipose tissue in patients with COVID-19: risk stratification for severity

Purpose

To assess visceral (VAT), subcutaneous (SAT), and total adipose tissue (TAT) estimates at abdominopelvic CT in COVID-19 patients with different severity, and analyze Body Mass Index (BMI) and CT estimates of fat content in patients requiring hospitalization.

Methods

In this retrospective IRB approved HIPPA compliant study, 51 patients with SARS-CoV-2 infection with abdominopelvic CT were included. Patients were stratified based on disease severity as outpatient (no hospital admission) and patients who were hospitalized. Subset of hospitalized patient required mechanical ventilation (MV). A radiologist blinded to the clinical outcome evaluated single axial slice on CT at L3 vertebral body for VAT_L3, SAT_L3, TAT_L3, and VAT/TAT_L3. These measures along with age, gender, and BMI were compared. A clinical model that included age, sex, and BMI was compared to clinical + CT model that also included VAT_L3 to discriminate hospitalized patients from outpatients.

Results

There were ten outpatients and 41 hospitalized patients. 11 hospitalized patients required MV. There were no significant differences in age and BMI between the hospitalized and outpatients (all p > 0.05). There was significantly higher VAT_L3 and VAT/TAT_L3 in hospitalized patients compared to the outpatients (all p < 0.05). Area under the curve (AUC) of the clinical + CT model was higher compared to the clinical model (AUC 0.847 versus 0.750) for identifying patients requiring hospitalization.

Conclusion

Higher VAT_L3 was observed in COVID-19 patients that required hospitalization compared to the outpatients, and addition of VAT_L3 to the clinical model improved AUC in discriminating hospitalized from outpatients in this preliminary study.

Visceral adipose tissue area predicts intensive care unit admission in COVID-19 patients

We retrospectively investigated, in 62 consecutive hospitalised COVID-19 patients (aged 70 ± 14 years, 40 males), the prognostic value of CT-derived subcutaneous adipose tissue and visceral adipose tissue (VAT) metrics, testing them in four predictive models for admission to intensive care unit (ICU), with and without pre-existing comorbidities. Multivariate logistic regression identified VAT score as the best ICU admission predictor (odds ratios 4.307–12.842). A non-relevant contribution of comorbidities at receiver operating characteristic analysis (area under the curve 0.821 for the CT-based model, 0.834 for the one including comorbidities) highlights the potential one-stop-shop prognostic role of CT-derived lung and adipose tissue metrics.