Predictive accuracy of single- and multi-slice MRI for the estimation of total visceral adipose tissue in overweight to severely obese patients

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.

Body composition analysis by radiological imaging - methods, applications, and prospects

BACKGROUND

 This review discusses the quantitative assessment of tissue composition in the human body (body composition, BC) using radiological methods. Such analyses are gaining importance, in particular, for oncological and metabolic problems. The aim is to present the different methods and definitions in this field to a radiological readership in order to facilitate application and dissemination of BC methods. The main focus is on radiological cross-sectional imaging.

METHODS

 The review is based on a recent literature search in the US National Library of Medicine catalog (pubmed.gov) using appropriate search terms (body composition, obesity, sarcopenia, osteopenia in conjunction with imaging and radiology, respectively), as well as our own work and experience, particularly with MRI- and CT-based analyses of abdominal fat compartments and muscle groups.

RESULTS AND CONCLUSION

 Key post-processing methods such as segmentation of tomographic datasets are now well established and used in numerous clinical disciplines, including bariatric surgery. Validated reference values are required for a reliable assessment of radiological measures, such as fatty liver or muscle. Artificial intelligence approaches (deep learning) already enable the automated segmentation of different tissues and compartments so that the extensive datasets can be processed in a time-efficient manner - in the case of so-called opportunistic screening, even retrospectively from diagnostic examinations. The availability of analysis tools and suitable datasets for AI training is considered a limitation.

KEY POINTS

  · Radiological imaging methods are increasingly used to determine body composition (BC).. · BC parameters are usually quantitative and well reproducible.. · CT image data from routine clinical examinations can be used retrospectively for BC analysis.. · Prospectively, MRI examinations can be used to determine organ-specific BC parameters.. · Automated and in-depth analysis methods (deep learning or radiomics) appear to become important in the future..

CITATION FORMAT

· Linder N, Denecke T, Busse H. Body composition analysis by radiological imaging - methods, applications, and prospects. Fortschr Röntgenstr 2024; DOI: 10.1055/a-2263-1501.

Automated abdominal adipose tissue segmentation and volume quantification on longitudinal MRI using 3D convolutional neural networks with multi-contrast inputs

OBJECTIVE

Increased subcutaneous and visceral adipose tissue (SAT/VAT) volume is associated with risk for cardiometabolic diseases. This work aimed to develop and evaluate automated abdominal SAT/VAT segmentation on longitudinal MRI in adults with overweight/obesity using attention-based competitive dense (ACD) 3D U-Net and 3D nnU-Net with full field-of-view volumetric multi-contrast inputs.

MATERIALS AND METHODS

920 adults with overweight/obesity were scanned twice at multiple 3 T MRI scanners and institutions. The first scan was divided into training/validation/testing sets (n = 646/92/182). The second scan from the subjects in the testing set was used to evaluate the generalizability for longitudinal analysis. Segmentation performance was assessed by measuring Dice scores (DICE-SAT, DICE-VAT), false negatives (FN), and false positives (FP). Volume agreement was assessed using the intraclass correlation coefficient (ICC).

RESULTS

ACD 3D U-Net achieved rapid (< 4.8 s/subject) segmentation with high DICE-SAT (median ≥ 0.994) and DICE-VAT (median ≥ 0.976), small FN (median ≤ 0.7%), and FP (median ≤ 1.1%). 3D nnU-Net yielded rapid (< 2.5 s/subject) segmentation with similar DICE-SAT (median ≥ 0.992), DICE-VAT (median ≥ 0.979), FN (median ≤ 1.1%) and FP (median ≤ 1.2%). Both models yielded excellent agreement in SAT/VAT volume versus reference measurements (ICC > 0.997) in longitudinal analysis.

DISCUSSION

ACD 3D U-Net and 3D nnU-Net can be automated tools to quantify abdominal SAT/VAT volume rapidly, accurately, and longitudinally in adults with overweight/obesity.

Synergic prognostic value of 3D CT scan subcutaneous fat and muscle masses for immunotherapy-treated cancer

BACKGROUND

Our aim was to explore the prognostic value of anthropometric parameters in a large population of patients treated with immunotherapy.

METHODS

We retrospectively included 623 patients with advanced non-small cell lung cancer (NSCLC) (n=318) or melanoma (n=305) treated by an immune-checkpoint-inhibitor having a pretreatment (thorax-)abdomen-pelvis CT scan. An external validation cohort of 55 patients with NSCLC was used. Anthropometric parameters were measured three-dimensionally (3D) by a deep learning software (Anthropometer3DNet) allowing an automatic multislice measurement of lean body mass, fat body mass (FBM), muscle body mass (MBM), visceral fat mass (VFM) and sub-cutaneous fat mass (SFM). Body mass index (BMI) and weight loss (WL) were also retrieved. Receiver operator characteristic (ROC) curve analysis was performed and overall survival was calculated using Kaplan-Meier (KM) curve and Cox regression analysis.

RESULTS

In the overall cohort, 1-year mortality rate was 0.496 (95% CI: 0.457 to 0.537) for 309 events and 5-year mortality rate was 0.196 (95% CI: 0.165 to 0.233) for 477 events. In the univariate Kaplan-Meier analysis, prognosis was worse (p<0.001) for patients with low SFM (<3.95 kg/m2), low FBM (<3.26 kg/m2), low VFM (<0.91 kg/m2), low MBM (<5.85 kg/m2) and low BMI (<24.97 kg/m2). The same parameters were significant in the Cox univariate analysis (p<0.001) and, in the multivariate stepwise Cox analysis, the significant parameters were MBM (p<0.0001), SFM (0.013) and WL (0.0003). In subanalyses according to the type of cancer, all body composition parameters were statistically significant for NSCLC in ROC, KM and Cox univariate analysis while, for melanoma, none of them, except MBM, was statistically significant. In multivariate Cox analysis, the significant parameters for NSCLC were MBM (HR=0.81, p=0.0002), SFM (HR=0.94, p=0.02) and WL (HR=1.06, p=0.004). For NSCLC, a KM analysis combining SFM and MBM was able to separate the population in three categories with the worse prognostic for the patients with both low SFM (<5.22 kg/m2) and MBM (<6.86 kg/m2) (p<0001). On the external validation cohort, combination of low SFM and low MBM was pejorative with 63% of mortality at 1 year versus 25% (p=0.0029).

CONCLUSIONS

3D measured low SFM and MBM are significant prognosis factors of NSCLC treated by immune checkpoint inhibitors and can be combined to improve the prognostic value.

Body composition assessment of people with overweight/obesity with a simplified magnetic resonance imaging method

To develop a simplified magnetic resonance imaging method (MRI) to assess total adipose tissue (AT) and adipose tissue free mass (ATFM) from three single MRI slices in people with overweight/obesity in order to implement body composition follow-up in a clinical research setting. Body composition of 310 participants (70 women and 240 men, age: 50.8 ± 10.6 years, BMI: 31.3 ± 5.6 kg.m^-2) was assessed with 3 single slices (T6-T7, L4-L5 and at mid-thigh) MRI. Multiple regression analysis was used to develop equations predicting AT and ATFM from these three single slices. Then we implemented a longitudinal phase consisting in a 2-month exercise training program during which we tested the sensitivity of these equations in a subgroup of participants with overweight/obesity (n = 79) by comparing the exercise-induced variations between predicted and measured AT and ATFM. The following equations: total AT = - 12.74105 + (0.02919 × age) + (4.27634 × sex (M = 0, F = 1)) + (0.22008 × weight) + (26.92234 × AT T6-T7) + (23.70142 × AT L4-L5) + (37.94739 × AT mid-thigh) and total ATFM = - 33.10721 + (- 0.02363 × age) + (- 3.58052 × sex (M = 0, F = 1)) + (30.02252 × height) + (0.08549 × weight) + (11.36859 × ATFM T6-T7) + (27.82244 × ATFM L4-L5) + (58.62648 × ATFM mid-thigh) showed an excellent prediction (adjusted R² = 97.2% and R² = 92.5%; CCC = 0.986 and 0.962, respectively). There was no significant difference between predicted and measured methods regarding the AT variations (- 0.07 ± 2.02 kg, p = 0.70) and the ATFM variations (0.16 ± 2.41 kg, p = 0.49) induced by 2-months of exercise training. This simplified method allows a fully accurate assessment of the body composition of people with obesity in less than 20 min (10 min for images acquisition and analysis, respectively), useful for a follow-up.

Sex and race/ethnicity specific reference predictive equations for abdominal adiposity indices using anthropometry in US adults

BACKGROUND AND AIMS

Abdominal adiposity indices have stronger associations with cardiometabolic risk factors compared to anthropometric measures but are rarely used in large scale studies due to the cost and efficiency. The aim of this study is to establish sex and race/ethnicity specific reference equations using anthropometric measures.

METHODS AND RESULTS

A secondary data analysis (n = 6589) of healthy adults was conducted using data from National Health and Nutrition Examination Survey 2011-2018. Variables included in the analyses were anthropometric measures (height; weight; waist circumference, WC) and abdominal adiposity indices (android percent fat; android to gynoid ratio, A/G ratio; visceral adipose tissue area, VATA; visceral to subcutaneous adipose area ratio, VSR). Multivariable prediction models were developed using quantile regression. Bland-Altman was used for external validation of prediction models. Reference equations to estimate android percent fat, A/G ratio, VATA and VSR from anthropometric measurements were developed using a randomly selected subsample of 4613. These reference equations for four abdominal adiposity indices were then cross-validated in the remaining subsample of 1976. The measured and predicted android percent fat, A/G ratio, VATA and VSR were not statistically different (p > 0.05) except for the A/G ratio in Asian males and VSR in White females. The results of Bland-Altman further revealed that ≥93% of predicted abdominal adiposity indices fell within the limits of agreement (±1.96 standard deviation).

CONCLUSION

The sex and race/ethnicity specific reference equations for abdominal adiposity indices established using anthropometrics in the present study have strong predictive ability in US healthy adults.

The Modified Assessment Tool Based on Scapular Y-View for Global Fatty Infiltration in the Supraspinatus Muscle: Correlation, Predictive Performance, and Reliability Analyses

BACKGROUND

The accurate evaluation of rotator cuff (RC) fatty degeneration after tears is critical for appropriate surgical decision making and prognosis. However, there is currently no reliable and practical tool to reflect the global fatty infiltration (Global-FI) throughout the 3-dimensional (3D) volumetric RC muscles.

PURPOSE

(1) To determine the correlations between 2 modified assessment tools and the Global-FI and their predictive performances and reliabilities for Global-FI prediction, and (2) to compare these predictive parameters with those of the conventional tool using a single scapular Y-view slice.

STUDY DESIGN

Cohort study (diagnosis); Level of evidence, 3.

METHODS

A total of 49 patients with full-thickness RC tears scheduled to undergo arthroscopic repairs were included, and their surgical shoulders underwent 6-point Dixon magnetic resonance imaging preoperatively. The Global-FI was measured by calculating the 3D-volumetric fat fraction (FF) of the whole supraspinatus muscle through all acquired oblique sagittal slices. As a commonly used radiological landmark, the scapular Y-view was used to evaluate single-plane fatty infiltration (Y-FI) by calculating the FF in 1 slice, defined as the conventional assessment tool. Two modified assessment tools expand the analytic imaging by integrating the FFs from the scapular Y-view slice and its neighboring slices, which were calculated by averaging the FFs of these 3 slices (^meanY₃-FI) and accumulating local 3D-volumetric FFs from 3 slices (^volY₃-FI), respectively. The correlations between 3 assessment tools and the Global-FI were analyzed, and the predictive performance for Global-FI prediction using these tools was determined by goodness of fit and agreement. Moreover, the inter- and intraobserver reliabilities of these assessment tools were evaluated. Similar analyses were performed in the small-medium, large, or massive tear subgroups.

RESULTS

The Y-FI was significantly higher than the Global-FI in all cases and tear size subgroups, while the 2 modified assessment tools (^meanY₃-FI and ^volY₃-FI) did not significantly differ from the Global-FI. All assessment tools were significantly correlated with the Global-FI, but the ^meanY₃-FI and ^volY₃-FI showed stronger correlations than the Y-FI, which was also determined in different tear sizes. Moreover, the regression models of the ^meanY₃-FI and ^volY₃-FI showed superior goodness of fit to Y-FI in Global-FI prediction in all cases and subgroups, with larger coefficients of determination (R²) and smaller root mean square errors. The predicted Global-FI using the regression model of ^volY₃-FI had the best agreement with the measured Global-FI, followed by the ^meanY₃-FI, both showing smaller biases and standard deviation of the percentage difference between predicted- and measured Global-FI than the conventional Y-FI. In addition, the 2 modified assessment tools achieved better interobserver and intraobserver reliabilities than the conventional tool in all cases and subgroups.

CONCLUSION

Two modified assessment tools (^meanY₃-FI and ^volY₃-FI) were comparable with the Global-FI of the whole supraspinatus muscle, showing stronger correlations with the Global-FI and better predictive performances and reliabilities than the conventional tool (Y-FI). Moreover, the ^volY₃-FI was slightly superior to ^meanY₃-FI in the predictive performance and reliability.

The 3-Dimensional Fatty Infiltration in the Overall Supraspinatus Can Be Predicted by Localized Sectional Accumulation Units: A Cross-Sectional Study in Patients with Atraumatic Small-to-Massive Rotator Cuff Tears

BACKGROUND

Fatty infiltration (FI) of the rotator cuff (RC) muscles is one of the most common risk factors for a retear following RC repair. Recent methodological developments focus on using 3-dimensional measurements of the overall FI of RC muscles instead of using single-plane-based measurements. However, the required labor-intensive segmentation and time-consuming post-processing steps need to be optimized for routine clinical use.

METHODS

We collected all 6-point Dixon magnetic resonance imaging (MRI) slices of the overall supraspinatus in 46 patients with atraumatic small-to-massive RC tears. Using emerging techniques, the overall 3-dimensional FI of the supraspinatus (overall FI, using all N slices) was assessed as the reference. Each sagittal segment of the supraspinatus was defined as a sectional accumulation unit (SAU). The localized FI in SAUs with different scales of N/3, N/6, and N/12 slices (SAU-FIs) was then calculated using piecewise accumulation by stacking neighboring slices after the overall supraspinatus had been sequentially segmented using MRI slices of the same thickness. The capacity of the SAU-FIs to predict the overall FI, and the ideal locations for prediction, were evaluated using linear regression models after the associations were examined. Goodness-of-fit of the regression models was appraised by the coefficient of determination (R 2 ) and root-mean-square error (RMSE). The agreement between the predicted and measured overall FI was assessed using Bland-Altman analysis and the standard deviation of the percent differences (sd%).

RESULTS

The localized SAU-FIs of the N/3, N/6, and N/12 SAUs generally displayed comparable distributions throughout the normalized distal-proximal long axis of the supraspinatus. The localized SAU-FIs showed substantial correspondence with the overall FI, and the highest correlations were found in the 2/3 SAU (Pearson r and Spearman ρ: 0.95, 0.98), 3/6 and 4/6 SAUs (Pearson r and Spearman ρ: 0.97), and 5/12 to 7/12 SAUs (Pearson r and Spearman ρ: 0.95 to 0.96). The strongest predictors to estimate the overall supraspinatus FI in the regression analysis were these SAU-FIs located in the middle third, which demonstrated good fits to the overall FI (all R 2 ≥ 0.90; RMSE ≤ 1.69). The best agreements between the overall FI predicted by the regression models and the measured overall FI were found in these SAUs (2/3 SAU: sd% = 4.84%; 3/6 and 4/6 SAUs: sd% = 5.14%; 5/12 to 7/12 SAUs: sd% = 6.44%).

CONCLUSIONS

Specific SAUs near the center of the supraspinatus (2/3, 3/6 and 4/6, and 5/12 to 7/12 SAUs), which displayed the best agreement between the predictions and actual measurements of overall FI values, can serve as appropriate surrogates to estimate the overall FI of the supraspinatus in small-to-massive RC tears. The potential to assess the overall FI of the supraspinatus using specific localized SAUs may improve the speed of analytical strategies for accurately assessing the overall FI of RC muscles and thus enable their routine clinical use in the future.

LEVEL OF EVIDENCE

Prognostic Level IV . See Instructions for Authors for a complete description of levels of evidence.

Anthropometric Equations to Predict Visceral Adipose Tissue in European and American Youth

OBJECTIVE

To investigate whether prediction equations including a limited but selected number of anthropometrics that consider differences in subcutaneous abdominal adipose tissue may improve prediction of the visceral adipose tissue (VAT) in youth.

STUDY DESIGN

Anthropometrics and abdominal adipose tissue by MRI were available in 7-18 years old youth with overweight or obesity: 181 White Europeans and 186 White and Black Americans. Multivariable regressions were performed to develop and validate the VAT anthropometric predictive equations in a cross-sectional study.

RESULTS

A model with both waist circumference (WaistC) and hip circumference (HipC) (VAT = [1.594 × WaistC] - [0.681 × HipC] + [1.74 × Age] - 48.95) more strongly predicted VAT in girls of White European ethnicity (R² = 50.8%; standard error of the estimate [SEE] = 13.47 cm²), White American ethnicity (R² = 41.9%; SEE, 15.63 cm²), and Black American ethnicity (R² = 25.1%; SEE, 16.34 cm²) (P < .001), than WaistC or BMI. In boys, WaistC was the strongest predictor of VAT; HipC did not significantly improve VAT prediction.

CONCLUSIONS

A model including both WaistC and HipC that considers differences in subcutaneous abdominal adipose tissue more accurately predicts VAT in girls and is superior to commonly measured anthropometrics used individually. In boys, other anthropometric measures did not significantly contribute to the prediction of VAT beyond WaistC alone. This demonstrates that selected anthropometric predictive equations for VAT can be an accessible, cost-effective alternative to imaging methods that can be used in both clinics and research.

Body Composition to Define Prognosis of Cancers Treated by Anti-Angiogenic Drugs

Background: Body composition could help to better define the prognosis of cancers treated with anti-angiogenics. The aim of this study is to evaluate the prognostic value of 3D and 2D anthropometric parameters in patients given anti-angiogenic treatments. Methods: 526 patients with different types of cancers were retrospectively included. The software Anthropometer3DNet was used to measure automatically fat body mass (FBM3D), muscle body mass (MBM3D), visceral fat mass (VFM3D) and subcutaneous fat mass (SFM3D) in 3D computed tomography. For comparison, equivalent two-dimensional measurements at the L3 level were also measured. The area under the curve (AUC) of the receiver operator characteristics (ROC) was used to determine the parameters’ predictive power and optimal cut-offs. A univariate analysis was performed using Kaplan−Meier on the overall survival (OS). Results: In ROC analysis, all 3D parameters appeared statistically significant: VFM3D (AUC = 0.554, p = 0.02, cutoff = 0.72 kg/m2), SFM3D (AUC = 0.544, p = 0.047, cutoff = 3.05 kg/m2), FBM3D (AUC = 0.550, p = 0.03, cutoff = 4.32 kg/m2) and MBM3D (AUC = 0.565, p = 0.007, cutoff = 5.47 kg/m2), but only one 2D parameter (visceral fat area VFA2D AUC = 0.548, p = 0.034). In log-rank tests, low VFM3D (p = 0.014), low SFM3D (p < 0.0001), low FBM3D (p = 0.00019) and low VFA2D (p = 0.0063) were found as a significant risk factor. Conclusion: automatic and 3D body composition on pre-therapeutic CT is feasible and can improve prognostication in patients treated with anti-angiogenic drugs. Moreover, the 3D measurements appear to be more effective than their 2D counterparts.

Improvement of Pancreatic Steatosis and Indices of Insulin Resistance After Metabolic Surgery

Purpose

Obesity is associated with fat accumulation in ectopic sites such as the pancreas, the so-called pancreatic steatosis (PS). Bariatric surgery has been shown to be associated with reducing pancreatic fat. This study investigated the effect of laparoscopic sleeve gastrectomy (LSG) on pancreatic volume and its fat content and glucose homeostasis.

Methods

The study enrolled 54 patients subjected to LSG. Metabolic variables and pancreatic exocrine function were assessed immediately before surgery and 12 months after. MRI of the abdomen was performed to measure pancreatic fat content and its total volume and visceral adipose tissue (VAT).

Results

Surgery resulted in a significant reduction in body weight and BMI. HbA1c, fasting insulin, C-peptide levels, HOMA-IR, and Hs-CRP levels decreased significantly. Surgery resulted in significant improvement in lipid profile except for HDL-cholesterol and liver function tests. Total VAT volume decreased significantly. Total pancreas volume decreased by a mean of 9.0 cm³ (95% CI: 6.6–11.3). The median change of pancreatic fat was −26.1% (range: −55.6 to 58.3%). Pancreatic lipase decreased significantly (P < 0.001). There was a positive correlation between the percentage of total weight loss and decrease in pancreatic fat volume (r = 0.295, P = 0.030).

Conclusion

Weight loss after LSG is associated with a reduction of total VAT volume, total pancreatic volume, and pancreatic fat content. These changes are associated with improved glucose homeostasis, reduced systemic inflammation, and decreased pancreatic lipase secretion.

Effects of enriched seafood sticks (heat-inactivated B. animalis subsp. lactis CECT 8145, inulin, omega-3) on cardiometabolic risk factors and gut microbiota in abdominally obese subjects: randomized controlled trial

PURPOSE

To assess the effects of enriched seafood sticks with postbiotic and bioactive compounds on CMD risk factors and the gut microbiota in abdominally obese individuals.

METHODS

Randomized, double-blind, parallel, placebo-controlled trial with abdominally obese individuals. Participants (n = 120) consumed 50 g/day of enriched seafood sticks containing SIAP: (10¹⁰ colony forming units (CFUs) of heat-inactivated B. animalis subsp. lactis CECT8145, 370 mg/day omega 3 and 1.7 g/day inulin), or 50 g/day of placebo seafood sticks for 12 weeks. At 12 weeks, an acute single-dose study of 4 h was performed.

RESULTS

Sustained SIAP2 consumption significantly decreased the insulin by - 5.25 mg/dL and HOMA-IR (homeostatic Model Assessment of Insulin Resistance) by - 1.33. In women, SIAP2 consumption significantly decreased the pulse pressure (PP) by - 4.69 mmHg. Gut microbiota analysis showed a negative association between glycemic parameter reduction and Alistipes finegoldii and Ruminococcaceae, and between PP reduction and Prevotella 9-ASV0283 and Christensenellaceae. In the acute single dose-study 4-h, SIAP2 consumption produced a lower increase in the postprandial circulating triglyceride levels [23.9 (7.03) mg/dL (mean [standard error])] than the observed with placebo [49.0 (9.52)] mg/dL.

CONCLUSION

In abdominally obese individuals, enriched seafood sticks induce a potential protection against type 2 diabetes development by the reduction in the insulin and HOMA-IR; and in cardiovascular disease, in women, by the PP reduction. These effects are accompanied by partial changes in the gut microbiota composition. The enriched seafood sticks reduce the atherogenic triglyceride postprandial concentrations. Our results support the use of enriched seafood sticks as a complementary strategy in the management of CMD risk factors. REGISTRATION NUMBER OF CLINICAL TRIAL: ( www.

CLINICALTRIALS

gov ): NCT03630588 (August 15, 2018).

Waist Circumference and BMI Are Strongly Correlated with MRI-Derived Fat Compartments in Young Adults

Young adulthood is increasingly considered as a vulnerable age group for significant weight gain, and it is apparent that there is an increasing number of new cases of metabolic syndrome developing among this population. This study included 60 young adult volunteers (18-26 years old). All participants obtained a calculated total abdominal fat percentage, subcutaneous fat percentage, and visceral fat percentage using a semiautomatic segmentation technique from T1-weighted magnetic resonance imaging (MRI) images of the abdomen. The results show strongest correlation between abdominal fat and BMI (r = 0.824) followed by subcutaneous fat (r = 0.768), and visceral fat (r = 0.633) respectively, (p < 0.001 for all, after having been adjusted for age and gender). Among anthropometric measurements, waist circumference showed strong correlation with all fat compartments (r = 0.737 for abdominal, r = 0.707 for subcutaneous fat, and r = 0.512 for visceral fat; p < 0.001 for all). The results obtained from examining the blood revealed that there was a moderate positive correlation relationship between all fat compartments with triglyceride, high-density lipoprotein, and fasting glucose levels (p < 0.05 for all). This study suggests that both BMI and waist circumference could be used to assess the fat compartments and treatment targets to reduce the risk of metabolic disorders and health risks in the young adult population.

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.

Fatty Acid Synthase Correlates With Prognosis-Related Abdominal Adipose Distribution and Metabolic Disorders of Clear Cell Renal Cell Carcinoma

Purpose: Lipid metabolism reprogramming is a major pathway in tumor evolution. This study investigated fatty acid synthase (FASN) mRNA expression in anthropometric adipose tissue and elucidated the prognostic value and potential mechanism of clear cell renal cell carcinoma (ccRCC).

Materials and Methods: Transcription profiles were obtained from 533 ccRCC samples in The Cancer Genome Atlas (TCGA) cohorts. Real-time quantitative PCR (RT-qPCR) and immunohistochemistry were performed to detect FASN expression in 380 paired ccRCC and normal tissues from the Fudan University Shanghai Cancer Center (FUSCC). Visceral adipose tissue (VAT) and subcutaneous adipose tissue were at the level of the umbilicus as measured by magnetic resonance imaging (MRI). Non-targeted metabolomics and in vitro experiments were used to reveal the biological functions of FASN.

Results: Increased FASN expression was significantly relevant to advanced T, N, and American Joint Committee on Cancer (AJCC) stages (p < 0.01) and significantly correlated to poor progression-free survival (PFS) and overall survival (OS) of 913 ccRCC patients in FUSCC and TCGA cohorts. Pearson's correlation coefficient indicated that FASN amplification was positively correlated to VAT% (r = 0.772, p < 0.001), which significantly correlated to poor PFS (HR = 2.066, p = 0.028) and OS (HR = 2.773, p = 0.023) in the FUSCC cohort. Transient inhibition or overexpression of FASN significantly regulated A498 and 786O cell proliferation and migration by regulating epithelial–mesenchymal transition. Inhibition of FASN led to a higher apoptotic rate and decreased lipid droplet formation compared with normal control in ccRCC cells. Non-targeted metabolomics showed that decreased de novo lipogenesis might be required to sustain an elevation of glycolytic activity in 786O cells by regulating galactinol, dl-lactate, N-acetylaspartylglutamate, and sucrose, thereby participating in carcinogenesis and progression of ccRCC.

Conclusion: This study demonstrated that FASN expression is positively related to aggressive cell proliferation, migration, apoptosis, and lipid droplet formation and regulates metabolic disorders of the ccRCC microenvironment. Additionally, elevated FASN mRNA expression is significantly correlated to the abdominal obesity distribution, especially VAT%, which is a significant predictor of a poor prognosis for ccRCC patients.

Abdominal subcutaneous fat quantification in obese patients from limited field-of-view MRI data

Different types of adipose tissue can be accurately localized and quantified by tomographic imaging techniques (MRI or CT). One common shortcoming for the abdominal subcutaneous adipose tissue (ASAT) of obese subjects is the technically restricted imaging field of view (FOV). This work derives equations for the conversion between six surrogate measures and fully segmented ASAT volume and discusses the predictive power of these image-based quantities. Clinical (gender, age, anthropometry) and MRI data (1.5 T, two-point Dixon sequence) of 193 overweight and obese patients (116 female, 77 male) from a single research center for obesity were analyzed retrospectively. Six surrogate measures of fully segmented ASAT volume (V_ASAT) were considered: two simple ASAT lengths, two partial areas (A_p-FH, A_p-ASIS) and two partial volumes (V_p-FH, V_p-ASIS) limited by either the femoral heads (FH) or the anterior superior iliac spine (ASIS). Least-squares regression between each measure and V_ASAT provided slope and intercept for the computation of estimated ASAT volumes (V^~_ASAT). Goodness of fit was evaluated by coefficient of determination (R²) and standard deviation of percent differences (s_d%) between V^~_ASAT and V_ASAT. Best agreement was observed for partial volume V_p-FH (s_d% = 14.4% and R² = 0.78), followed by V_p-ASIS (s_d% = 18.1% and R² = 0.69) and AWF_ASIS (s_d% = 23.9% and R² = 0.54), with minor gender differences only. Other estimates from simple lengths and partial areas were moderate only (s_d% > 23.0% and R² < 0.50). Gender differences in R² generally ranged between 0.02 (d_ven) and 0.29 (A_p-FH). The common FOV restriction for MRI volumetry of ASAT in obese subjects can best be overcome by estimating V_ASAT from V_p-FH using the equation derived here. The very simple AWF_ASIS can be used with reservation.

Anthropometer3D: Automatic Multi-Slice Segmentation Software for the Measurement of Anthropometric Parameters from CT of PET/CT

Anthropometric parameters like muscle body mass (MBM), fat body mass (FBM), lean body mass (LBM), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) are used in oncology. Our aim was to develop and evaluate the software Anthropometer3D measuring these anthropometric parameters on the CT of PET/CT. This software performs a multi-atlas segmentation of CT of PET/CT with extrapolation coefficients for the body parts beyond the usual acquisition range (from the ischia to the eyes). The multi-atlas database is composed of 30 truncated CTs manually segmented to isolate three types of voxels (muscle, fat, and visceral fat). To evaluate Anthropomer3D, a leave-one-out cross-validation was performed to measure MBM, FBM, LBM, VAT, and SAT. The reference standard was based on the manual segmentation of the corresponding whole-body CT. A manual segmentation of one CT slice at level L3 was also used. Correlations were analyzed using Dice coefficient, intra-class coefficient correlation (ICC), and Bland-Altman plot. The population was heterogeneous (sex ratio 1:1; mean age 57 years old [min 23; max 74]; mean BMI 27 kg/m² [min 18; max 40]). Dice coefficients between reference standard and Anthropometer3D were excellent (mean+/-SD): muscle 0.95 ± 0.02, fat 1.00 ± 0.01, and visceral fat 0.97 ± 0.02. The ICC was almost perfect (minimal value of 95% CI of 0.97). All Bland-Altman plot values (mean difference, 95% CI and slopes) were better for Anthropometer3D compared to L3 level segmentation. Anthropometer3D allows multiple anthropometric measurements based on an automatic multi-slice segmentation. It is more precise than estimates using L3 level segmentation.

Measurement of total and visceral fat mass in young adult women: a comparison of MRI with anthropometric measurements with and without bioelectrical impedance analysis

OBJECTIVE

MRI is established for measurement of body fat mass (FM) and abdominal visceral adipose tissue (VAT). Anthropometric measurements and bioelectrical impedance analysis (BIA) have been proposed as surrogates to estimation by MRI. Aim of this work is to assess the predictive value of these methods for FM and VAT measured by MRI.

METHODS

Patients were selected from cohort study PPS-Diab (prediction, prevention and subclassification of Type 2 diabetes). Total FM and VAT were quantified by MRI and BIA together with clinical variables like age, waist and hip circumference and height. Least-angle regressions were utilized to select anthropometric and BIA parameters for their use in multivariable linear regression models to predict total FM and VAT. Bland-Altman plots, Pearson correlation coefficients, Wilcoxon signed-rank tests and univariate linear regression models were applied.

RESULTS

116 females with 35 ± 3 years and a body mass index of 25.1 ± 5.3 kg/m2 were included into the analysis. A multivariable model revealed weight (β = 0.516, p < 0.001), height (β = -0.223, p < 0.001) and hip circumference (β = 0.156, p = 0.003) as significantly associated with total FM measured by MRI. A additional multivariable model also showed a significant predictive value of FMBIA (β = 0.583, p < 0.001) for FM. In addition, waist circumference (β = 0.054, p < 0.001), weight (β = 0.016, p = 0.031) in one model and FMBIA (β = 0.026, p = 0.018) in another model were significantly associated with VAT quantified by MRI. However, deviations reached more than 5 kg for total FM and more than 1 kg for VAT.

CONCLUSION

Anthropometric measurements and BIA show significant association with total FM and VAT.

ADVANCES IN KNOWLEDGE

As these measurements show significant deviations from the absolute measured values determined by MRI, MRI should be considered the gold-standard for quantification.

MRI estimated changes in visceral adipose tissue and liver fat fraction in patients with obesity during a very low-calorie-ketogenic diet compared to a standard low-calorie diet

AIM

To compare the changes in visceral adipose tissue (VAT), liver fat fraction, and liver stiffness using quantitative magnetic resonance imaging (MRI) during a very-low-calorie ketogenic (VLCK) diet and a standard low-calorie diet (LC).

MATERIALS AND METHODS

The study involved secondary analysis of prospective collected clinical data. Patients undergoing weight loss interventions were randomised to either a LC or a VLCK diet. VAT, liver fat fraction, and stiffness were measured at baseline and after 2 months.

RESULTS

Forty-six patients were included; 39 patients were evaluated at baseline and at 2 months follow-up. Mean weight loss was -9.7±3.8 kg (interquartile range [IQR]: -12.3; -7 kg) in the VLCK group and -1.67±2.2 kg (IQR: -3.3, -0.1 kg) in the LC group (p<0.0001). Mean VAT reductions were -39.3±40 cm² (IQR: -52, -10 cm²) and -12.5±38.3 cm² (IQR: -29, 5 cm²; p=0.0398), and mean liver proton density fat fraction (PDFF) reductions were -4.77±4.2% (IQR: -7.3, -1.7%) and -0.79±1.7%, (IQR: -1.8, -0.4%; p<0.005) in the VLCK group and in the LC group, respectively. No significant changes in liver stiffness occurred from baseline to follow-up.

CONCLUSION

A VLCK diet resulted in greater weight loss than a standard low-calorie diet and in significantly greater reduction in liver PDFF. As anthropometric measurements may not correlate with liver fat changes, it may be advantageous to include quantitative MRI to the monitoring strategies of patients undergoing weight-loss programmes.

Prognostic value of anthropometric measures extracted from whole-body CT using deep learning in patients with non-small-cell lung cancer

INTRODUCTION

The aim of the study was to extract anthropometric measures from CT by deep learning and to evaluate their prognostic value in patients with non-small-cell lung cancer (NSCLC).

METHODS

A convolutional neural network was trained to perform automatic segmentation of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and muscular body mass (MBM) from low-dose CT images in 189 patients with NSCLC who underwent pretherapy PET/CT. After a fivefold cross-validation in a subset of 35 patients, anthropometric measures extracted by deep learning were normalized to the body surface area (BSA) to control the various patient morphologies. VAT/SAT ratio and clinical parameters were included in a Cox proportional-hazards model for progression-free survival (PFS) and overall survival (OS).

RESULTS

Inference time for a whole volume was about 3 s. Mean Dice similarity coefficients in the validation set were 0.95, 0.93, and 0.91 for SAT, VAT, and MBM, respectively. For PFS prediction, T-stage, N-stage, chemotherapy, radiation therapy, and VAT/SAT ratio were associated with disease progression on univariate analysis. On multivariate analysis, only N-stage (HR = 1.7 [1.2-2.4]; p = 0.006), radiation therapy (HR = 2.4 [1.0-5.4]; p = 0.04), and VAT/SAT ratio (HR = 10.0 [2.7-37.9]; p < 0.001) remained significant prognosticators. For OS, male gender, smoking status, N-stage, a lower SAT/BSA ratio, and a higher VAT/SAT ratio were associated with mortality on univariate analysis. On multivariate analysis, male gender (HR = 2.8 [1.2-6.7]; p = 0.02), N-stage (HR = 2.1 [1.5-2.9]; p < 0.001), and the VAT/SAT ratio (HR = 7.9 [1.7-37.1]; p < 0.001) remained significant prognosticators.

CONCLUSION

The BSA-normalized VAT/SAT ratio is an independent predictor of both PFS and OS in NSCLC patients.

KEY POINTS

• Deep learning will make CT-derived anthropometric measures clinically usable as they are currently too time-consuming to calculate in routine practice. • Whole-body CT-derived anthropometrics in non-small-cell lung cancer are associated with progression-free survival and overall survival. • A priori medical knowledge can be implemented in the neural network loss function calculation.

Magnetic Resonance Imaging and Bioelectrical Impedance Analysis to Assess Visceral and Abdominal Adipose Tissue

OBJECTIVE

This study aimed to compare a state-of-the-art bioelectrical impedance analysis (BIA) device with two-point Dixon magnetic resonance imaging (MRI) for the quantification of visceral adipose tissue (VAT) as a health-related risk factor.

METHODS

A total of 63 male participants were measured using a 3-T MRI scanner and a segmental, multifrequency BIA device. MRI generated fat fraction (FF) maps, in which VAT volume, total abdominal adipose tissue volume, and FF of visceral and total abdominal compartments were quantified. BIA estimated body fat mass and VAT area.

RESULTS

Coefficients of determination between abdominal (r²  = 0.75) and visceral compartments (r²  = 0.78) were similar for both groups, but slopes differed by a factor of two. The ratio of visceral to total abdominal FF was increased in older men compared with younger men. This difference was not detected with BIA. MRI and BIA measurements of the total abdominal volume correlated moderately (r²  = 0.31-0.56), and visceral measurements correlated poorly (r²  = 0.13-0.44).

CONCLUSIONS

Visceral BIA measurements agreed better with MRI measurements of the total abdomen than of the visceral compartment, indicating that BIA visceral fat area assessment cannot differentiate adipose tissue between visceral and abdominal compartments in young and older participants.

Efficacy of a 2-Month Very Low-Calorie Ketogenic Diet (VLCKD) Compared to a Standard Low-Calorie Diet in Reducing Visceral and Liver Fat Accumulation in Patients With Obesity

Background: Currently the treatment of non-alcoholic fatty liver disease (NAFLD) is based on weight loss through lifestyle changes, such as exercise combined with calorie-restricted dieting. Objectives: To assess the effects of a commercially available weight loss program based on a very low-calorie ketogenic diet (VLCKD) on visceral adipose tissue (VAT) and liver fat content compared to a standard low-calorie (LC) diet. As a secondary aim, we evaluated the effect on liver stiffness measurements. Methods: Open, randomized controlled, prospective pilot study. Patients were randomized and treated either with an LC or a VLCKD and received orientation and encouragement to physical activity equally for both groups. VAT, liver fat fraction, and liver stiffness were measured at baseline and after 2 months of treatment using magnetic resonance imaging. Paired t-tests were used for comparison of continuous variables between visits and unpaired test between groups. Categorical variables were compared using the χ²-test. Pearson correlation was used to assess the association between VAT, anthropometric measures, and hepatic fat fraction. A significance level of the results was established at p < 0.05. Results: Thirty-nine patients (20 with VLCKD and 19 with LC) were evaluated at baseline and 2 months of intervention. Relative weight loss at 2 months was -9.59 ± 2.87% in the VLCKD group and -1.87 ± 2.4% in the LC group (p < 0.001). Mean reductions in VAT were -32.0 cm² for VLCKD group and -12.58 cm² for LC group (p < 0.05). Reductions in liver fat fraction were significantly more pronounced in the VLCKD group than in the LC group (4.77 vs. 0.79%; p < 0.005). Conclusion: Patients undergoing a VLCKD achieved superior weight loss, with significant VAT and liver fat fraction reductions when compared to the standard LC diet. The weight loss and rapid mobilization of liver fat demonstrated with VLCKD could serve as an effective alternative for the treatment of NAFLD. Clinical Trial Registration: ClinicalTrials.gov, identifier: NCT04322110.

Half-body MRI volumetry of abdominal adipose tissue in patients with obesity

Background

The purpose of this study was to determine to what extent the whole volumes of abdominal subcutaneous (ASAT) and visceral adipose tissue (VAT) of patients with obesity can be predicted by using data of one body half only. Such a workaround has already been reported for dual-energy x-ray absorption (DEXA) scans and becomes feasible whenever the field of view of an imaging technique is not large enough.

Methods

Full-body abdominal MRI data of 26 patients from an obesity treatment center (13 females and 13 males, BMI range 30.8–41.2 kg/m², 32.6–61.5 years old) were used as reference (REF). MRI was performed with IRB approval on a clinical 1.5 T MRI (Achieva dStream, Philips Healthcare, Best, Netherlands). Segmentation of adipose tissue was performed with a custom-made Matlab software tool. Statistical measures of agreement were the coefficient of determination R² of a linear fit.

Results

Mean ASAT_REF was 12,976 (7812–24,161) cm³ and mean VAT_REF was 4068 (1137–7518) cm³. Mean half-body volumes relative to the whole-body values were 50.8% (48.2–53.7%) for ASAT_L and 49.2% (46.3–51.8%) for ASAT_R. Corresponding volume fractions were 56.4% (51.4–65.9%) for VAT_L and 43.6% (34.1–48.6%) for VAT_R. Correlations of ASAT_REF with ASAT_L as well as with ASAT_R were both excellent (R² > 0.99, p < 0.01). Corresponding correlations of VAT_REF were marginally lower (R² = 0.98 for VAT_L, p < 0.01, and R² = 0.97 for VAT_R, p < 0.01).

Conclusions

In conclusion, abdominal fat volumes can be reliably assessed by half-body MRI data, in particular the subcutaneous fat compartment.

Elevated CD36 expression correlates with increased visceral adipose tissue and predicts poor prognosis in ccRCC patients

Objective: Growing evidence has proved obesity one of the confirmed important etiologic indicators for renal cell carcinoma (RCC). CD36 is underpinned to be involved in adipose absorption, but its role in clear cell renal cell carcinoma (ccRCC) remains unclear. This study aimed to investigate the mRNA expression of CD36 in anthropometric measures of adipose tissue and defining its value in predicting prognosis in ccRCC patients. Methods: Real-Time qPCR gene expression analysis was detected from 367 paired ccRCC and adjacent normal tissues. Distributions of categorical clinical-pathological data together with levels of CD36 expression were compared with χ²-test in a contingency table. Subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) were measured by magnetic resonance imaging (MRI) and identified at the level of the umbilicus. Pearson's correlation coefficient was utilized to quantify relations between body mass index (BMI), VAT%, SAT and CD36 expression respectively. Partial likelihood test from univariate and multivariate Cox regression analysis were developed to address the influence of independent factors on progression-free survival (PFS) and overall survival (OS). The Kaplan-Meier method and log-rank test were performed to assess the survival benefits between discrete levels. Results: In the current study, CD36 mRNA was demonstrated highly expressed in ccRCC compared with normal tissues. In addition, CD36 mRNA expression was significantly increased in patients with advanced TNM stage (p=0.003, p<0.001, p<0.001), and high VAT% (p=0.004). Pearson's correlation coefficient indicated that CD36 amplification positively correlated with BMI (r=0.117, p=0.025), VAT% (r=0.465, p<0.001), while negatively associated with SAT (r=-0.296, p=0.002). Median PFS was 60 months and OS was 99 months. Meanwhile, ccRCC patients with elevated CD36 expression held shorter PFS and OS, with hazard ratios [HR; 95% confidence interval (CI)] of 4.873 (3.300-7.196, p<0.001) and 4.610 (2.956-7.189, p<0.001). In 104 cases with available MRI scans, VAT was significantly correlated with poor PFS and OS, with HR of 2.556 (1.036-6.310, p<0.042) and 3.291 (1.034-10.477, p<0.044). A total of 100 significant genes were obtained from GSEA, and CD36 was found involved in the most significant pathways including fatty acid metabolism, UV response, angiogenesis and transforming growth factor beta (TGF-β) signaling pathways. Conclusion: In conclusion, our study first reveal that elevated CD36 mRNA expression is positively correlated to distribution of abdominal adipose, particularly VAT%, which, in addition, notably predicts poor prognosis in ccRCC patients.

A pilot study of visceral fat and its association with adipokines, stool calprotectin and symptoms in patients with diverticulosis

BACKGROUND

Complications of diverticular disease are increasingly common, possibly linked to increasing obesity. Visceral fat could contribute to the development of symptomatic diverticular disease through its pro-inflammatory effects.

OBJECTIVE

The study had 2 aims. A) to develop a semi-automated algorithm to measure abdominal adipose tissue from 2-echo magnetic resonance imaging (MRI) data; B) to use this to determine if visceral fat was associated with bowel symptoms and inflammatory markers in patients with symptomatic and asymptomatic diverticular disease.

DESIGN

An observational study measuring visceral fat using MRI together with serum adiponectin, leptin, stool calprotectin and patient-reported somatisation and bowel habit.

SETTING

Medical and imaging research centres of a university hospital.

PARTICIPANTS

MRI scans were performed on 55 patients after an overnight fast measuring abdominal subcutaneous and visceral adipose tissue volumes together with small bowel water content (SBWC). Blood and stool samples were collected and patients kept a 2 week stool diary and completed a somatisation questionnaire.

MAIN OUTCOME MEASURES

Difference in the volume of visceral fat between symptomatic and asymptomatic patients.

RESULTS

There were no significant differences in visceral (p = 0.98) or subcutaneous adipose (p = 0.60) tissue between symptomatic and asymptomatic patients. However measured fat volumes were associated with serum adipokines. Adiponectin showed an inverse correlation with visceral adipose tissue (VAT) (Spearman ρ = -0.5, p = 0.0003), which correlated negatively with SBWC (ρ = -0.3, p = 0.05). Leptin correlated positively with subcutaneous adipose tissue (ρ = 0.8, p < 0.0001). Overweight patients (BMI > 25 kgm-2) showed a moderate correlation between calprotectin and VAT (ρ = 0.3, p = 0.05). Somatization scores were significantly higher in symptomatic patients (p < 0.0003).

CONCLUSIONS

Increasing visceral fat is associated with lower serum adiponectin and increased faecal calprotectin suggesting a pro-inflammatory effect which may predispose to the development of complications of diverticulosis.

Power of computed-tomography-defined sarcopenia for prediction of morbidity after pancreaticoduodenectomy

BACKGROUND

The goal of our study was to evaluate the current approach in prediction of postoperative major complications after pancreaticoduodenectomy (PD), especially symptomatic pancreatic fistula (POPF), using parameters derived from computed tomography (CT).

METHODS

Patients after PD were prospectively collected in a database of the local department of surgery and all patients with CT scans available were assessed in this study. CT parameters were measured at the level of the intervertebral disc L3/L4 and consisted of the areas of the visceral adipose tissue (AVAT), the diameters of the pancreatic parenchyma (DPP) and the pancreatic duct (DPD), the areas of ventral abdominal wall muscle (AMVEN), psoas muscle (AMPSO), paraspinal muscle (AMSPI), total muscle (AMTOT), as well as the mean muscle attenuation (MA) and skeletal muscle index (SMI). Mann-Whitney-U Test for two independent samples and binary logistic regression were used for statistical analysis.

RESULTS

One hundred thirty-nine patients (55 females, 84 males) were included. DPD was 2.9 mm (Range 0.7-10.7) on median and more narrow in patients with complications equal to or greater stadium IIIb (p < 0.04) and severe POPF (p < 0.01). DPP median value was 17 (6.9-37.9) mm and there was no significant difference regarding major complications or POPF. AVAT showed a median value of 127.5 (14.5-473.0) cm2 and was significantly larger in patients with POPF (p < 0.01), but not in cases of major complications (p < 0.06). AMPSO, AMSPI, AMVEN and AMTOT showed no significant differences between major complications and POPF. MA was both lower in groups with major complications (p < 0.01) and POPF (p < 0.01). SMI failed to differentiate between patients with or without major complications or POPF.

CONCLUSION

Besides the known factors visceral obesity and narrowness of the pancreatic duct, the mean muscle attenuation can easily be examined on routine preoperative CT scans and seems to be promising parameter to predict postoperative complications and POPF.

MRI assessment of changes in adipose tissue parameters after bariatric surgery

Bariatric surgery and other therapeutic options for obese patients are often evaluated by the loss of weight, reduction of comorbidities or improved quality of life. However, little is currently known about potential therapy-related changes in the adipose tissue of obese patients. The aim of this study was therefore to quantify fat fraction (FF) and T1 relaxation time by magnetic resonance imaging (MRI) after Roux-en-Y gastric bypass surgery and compare the resulting values with the preoperative ones. Corresponding MRI data were available from 23 patients (16 females and 7 males) that had undergone MRI before (M0) and one month after (M1) bariatric surgery. Patients were 22–59 years old (mean age 44.3 years) and their BMI ranged from 35.7–54.6 kg/m² (mean BMI 44.6 kg/m²) at M0. Total visceral AT volumes (V_VAT-T, in L) were measured by semi-automatic segmentation of axial MRI images acquired between diaphragm and femoral heads. MRI FF and T1 relaxation times were measured in well-defined regions of visceral (VAT) and subcutaneous (SAT) adipose tissue using two custom-made analysis tools. Average BMI values were 45.4 kg/m² at time point M0 and 42.4 kg/m² at M1. Corresponding V_VAT-T values were 5.94 L and 5.33 L. Intraindividual differences in both BMI and V_VAT-T were highly significant (p<0.001). Average relaxation times T1_VAT were 303.7 ms at M0 and 316.9 ms at M1 (p<0.001). Corresponding T1_SAT times were 283.2 ms and 280.7 ms (p = 0.137). Similarly, FF_VAT differences (M0: 85.7%, M1: 83.4%) were significant (p <0.01) whereas FF_SAT differences (M0: 86.1, M1: 85.9%) were not significant (p = 0.517). In conclusion, bariatric surgery is apparently not only related to a significant reduction in common parameters of adipose tissue distribution, here BMI and total visceral fat volume, but also significant changes in T1 relaxation time and fat fraction of visceral adipose tissue. Such quantitative MRI measures may potentially serve as independent biomarkers for longitudinal and cross-sectional measurements in obese patients.

Estimation of visceral fat in 9- to 13-year-old girls using dual-energy X-ray absorptiometry (DXA) and anthropometry

OBJECTIVES

Accumulation of visceral fat (VF) in children increases the risk of cardiovascular disease and type 2 diabetes, and measurement of VF in children using computed tomography and magnetic resonance imaging (MRI) is expensive. Dual-energy X-ray absorptiometry (DXA) may provide a low-cost alternative. This study aims to determine if DXA VF estimates can accurately estimate VF in young girls, determine if adding anthropometry would improve the estimate and determine if other DXA fat measures, with and without anthropometry, could be used to estimate VF in young girls.

METHODS

Visceral fat was measured at lumbar intervertebral sites (L1-L2, L2-L3, L3-L4 and L4-L5) using 3.0T MRI on 32 young girls (mean age 11.3 ± 1.3 years). VF was estimated using the GE CoreScan application. Measurement of DXA android and total body fat was performed. Weight, height and waist circumference (WC) measurements were also obtained.

RESULTS

Waist circumference and body mass index were both strongly correlated with MRI, although WC was the best anthropometric covariate. Per cent fat (%fat) variables had the strongest correlation and did best in regression models. DXA %VF (GE CoreScan) and DXA android %fat and total body %fat accounted for 65% to 74% of the variation in MRI VF.

CONCLUSION

Waist circumference predicted MRI VF almost as well as DXA estimates in this population, and a combination of WC and DXA fat improves the predictability of VF. DXA VF estimate was improved by the addition of WC; however, DXA android %fat with WC was better at predicting MRI VF.

Adaptive changes in pancreas post Roux-en-Y gastric bypass induced weight loss

BACKGROUND

Obesity has been shown to trigger adaptive increases in pancreas parenchymal and fat volume. Consecutively, pancreatic steatosis may lead to beta-cell dysfunction. However, it is not known whether the pancreatic tissue components decrease with weight loss and pancreatic steatosis is reversible following Roux-en-Y gastric bypass (RYGB). Therefore, the objective of the study was to investigate the effects of RYGB-induced weight loss on pancreatic volume and glucose homeostasis.

METHODS

Eleven patients were recruited in the Obesity Centre of the University Medical Centre Hamburg-Eppendorf. Before and 6 months after RYGB, total GLP-1 levels were measured during oral glucose tolerance test. To assess changes in visceral adipose tissue and pancreatic volume, MRI was performed. Measures of glucose homeostasis and insulin indices were assessed. Fractional beta-cell area was estimated by correlation with the C-peptide-to-glucose ratio; beta-cell mass was calculated by the product of beta-cell area and pancreas parenchymal weight.

RESULTS

Pancreas volume decreased from 83.8 (75.7-92.0) to 70.5 (58.8-82.3) cm³ (mean [95% CI], P = .001). The decrease in total volume was associated with a significant decrease in fat volume. Fasting insulin and C-peptide were lower post RYGB. HOMA-IR levels decreased, whereas insulin sensitivity increased (P = .03). This was consistent with a reduction in the estimated beta-cell area and mass.

CONCLUSIONS

Following RYGB, pancreatic volume and steatosis adaptively decreased to "normal" levels with accompanying improvement in glucose homeostasis. Moreover, obesity-driven beta-cell expansion seems to be reversible; however, future studies must define a method to more accurately estimate functional beta-cell mass to increase our understanding of glucose homeostasis after RYGB.

Effects of daily consumption of the probiotic Bifidobacterium animalis subsp. lactis CECT 8145 on anthropometric adiposity biomarkers in abdominally obese subjects: a randomized controlled trial

Background

The effects of probiotic Bifidobacterium animalis subsp. lactis CECT 8145 (Ba8145) and those of its heat-killed form (h-k Ba8145) on human anthropometric adiposity biomarkers are unknown.

Objective

To assess the effect of Ba8145 and h-k Ba8145 ingestion on anthropometric adiposity biomarkers.

Design

Randomized, parallel, double-blind, placebo-controlled trial with abdominally obese individuals. Participants (n = 135) consumed 1 capsule/day containing 10¹⁰ colony forming unit (CFU) of Ba8145, 10¹⁰ CFU of h-k Ba8145, or placebo (maltodextrin) for 3 months.

Results

Ba8145 ingestion decreased waist circumference, waist circumference/height ratio, and Conicity index (P < 0.05) versus its baseline. Changes versus the placebo group reached significance (P < 0.05) after the h-k Ba8145 treatment. Ba8145 decreased the body mass index compared with baseline and placebo group (P < 0.05). The decrease in visceral fat area after Ba8145 treatments reached significance (P < 0.05) only after h-k Ba8145. When analyses by gender were performed, significance remained only for women. Diastolic blood pressure and HOMA index decreased (P < 0.05) after h-k Ba8145. Gut microbiome analyses showed an increase in Akkermansia spp. after Ba8145 treatment, particularly in the live form, which was inversely related to weight (P = 0.003).

Conclusions

In abdominally obese individuals, consumption of Ba8145, both as viable and mainly as heat-killed cells, improves anthropometric adiposity biomarkers, particularly in women. An increase in the gut Akkermansia genus appears as a possible mechanism involved. Our results support Ba8145 probiotic as a complementary strategy in obesity management.

Dicomflex: A novel framework for efficient deployment of image analysis tools in radiological research

Objective

Medical image processing tools in research are often developed from scratch without the use of predefined software structures, which potentially makes them less reliable and difficult to maintain. The objective here was to present and evaluate a novel framework (Dicomflex) for the deployment of tools with a uniform workflow, commonly encountered in medical image analysis.

Materials and methods

The object-oriented code was developed using Matlab. Dicomflex applications follow the common workflow of image-slice selection, user interaction, image processing, result visualization and progression to next slice. The framework consists of three important classes that host functionality, two configuration files and a front end that displays images, graphs and resulting data.

Results

So far, three different research tools have been created under the new framework. In comparison with previous Matlab analysis tools used at our institution, users of Dicomflex tools subjectively considered the learning phase to be shorter and handling to be simpler and more intuitive. They also highlighted the benefit and comfort of the standardized interface and predefined workflow. The framework-inherent handling of software versions was considered highly beneficial for maintenance as well as data and software management at different project stages. The clear separation of framework-related and unrelated code allows for a fast and more direct design of new tools in well-defined steps. The flexibility of the framework translates to a wide range of image processing tasks, such as segmentation, region-of-interest (ROI) analyses or computation of functional parameter maps, but is limited to 2D datasets.

Conclusion

Potential medical applications include the assessment of cardiac performance, detection of cerebrovascular disease or characterization of cancerous lesions. Dicomflex tools share a similar workflow and host the pertinent functions only. This may be relevant for many image processing needs in radiological research, where quick software deployment and reliability of results is essential.

The role of visceral and subcutaneous adipose tissue measurements and their ratio by magnetic resonance imaging in subjects with prediabetes, diabetes and healthy controls from a general population without cardiovascular disease

OBJECTIVE

To study the relationship of area- and volumetric-based visceral and subcutaneous adipose tissue (VAT and SAT) by MRI and their ratio in subjects with impaired glucose metabolism from the general population.

METHODS

Subjects from a population-based cohort with established prediabetes, diabetes and healthy controls without prior cardiovascular diseases underwent 3 T MRI. VAT and SAT were assessed as total volume and area on a single slice, and their ratio (VAT/SAT) was calculated. Clinical covariates and cardiovascular risk factors, such as hypertension and glycemic state were assessed in standardized fashion. Univariate and adjusted analyses were conducted.

RESULTS

Among 384 subjects (age: 56.2 ± 9.2 years, 58.1% male) with complete MRI data available, volumetric and single-slice VAT, SAT and VAT/SAT ratio were strongly correlated (all >r = 0.89). Similarly, VAT/SAT_volume ratio was strongly correlated with VAT_volume but not with SAT (r = 0.72 and r = -0.21, respectively). Significant higher levels of VAT, SAT and VAT/SAT ratio were found in subjects with impaired glucose metabolism (all p ≤ 0.01). After adjustment for potential cardiovascular confounders, VAT_volume and VAT/SAT_volume ratio remained significantly higher in subjects with impaired glucose metabolism (VAT_volume = 6.9 ± 2.5 l and 3.4 ± 2.3 l; VAT/SAT_volume ratio = 0.82 ± 0.34 l and 0.49 ± 0.29 l in patients with diabetes and controls, respectively, all p < 0.02), whereas the association for SAT_volume attenuated. Additionally, there was a decreasing effect of glycemic status on VAT/SAT_volume ratio with increasing body mass index and waist circumference (p < 0.05).

CONCLUSIONS

VAT_volume and VAT/SAT_volume ratio are associated with impaired glucose metabolism, independent of cardiovascular risk factors or MRI-based quantification technique, with a decreasing effect of VAT/SAT_volume ratio in obese subjects. Advances in knowledge: Quantification of VAT_volume and VAT/SAT_volume ratio by MRI represents a reproducable biomarker associated with cardiometabolic risk factors in subjects with impaired glucose metabolism, while the association of VAT/SAT_volume ratio with glycemic state is attenuated in obese subjects.

Automatic Measurement of the Total Visceral Adipose Tissue From Computed Tomography Images by Using a Multi-Atlas Segmentation Method

BACKGROUND

The visceral adipose tissue (VAT) volume is a predictive and/or prognostic factor for many cancers. The objective of our study was to develop an automatic measurement of the whole VAT volume using a multi-atlas segmentation (MAS) method from a computed tomography.

METHODS

A total of 31 sets of whole-body computed tomography volume data were used. The reference VAT volume was defined on the basis of manual segmentation (VATMANUAL). We developed an algorithm, which measured automatically the VAT volumes using a MAS based on a nonrigid volume registration algorithm coupled with a selective and iterative method for performance level estimation (SIMPLE), called VATMAS_SIMPLE. The results were evaluated using intraclass correlation coefficient and dice similarity coefficients.

RESULTS

The intraclass correlation coefficient of VATMAS_SIMPLE was excellent, at 0.976 (confidence interval, 0.943-0.989) (P < 0.001). The dice similarity coefficient of VATMAS_SIMPLE was also good, at 0.905 (SD, 0.076).

CONCLUSIONS

This newly developed algorithm based on a MAS can measure accurately the whole abdominopelvic VAT.

Equation to estimate visceral adipose tissue volume based on anthropometry for workplace health checkup in Japanese abdominally obese men

The purpose of this study was to develop a new equation model for predicting abdominal visceral adipose tissue (VAT) volume using anthropometric values for workplace health checkup and to clarify the association between metabolic risk factors and measured and predicted VAT volumes. Two hundred sixty male workers (200 for derivation group and 60 for validation group) participated in the cross-sectional study. The anthropometric variables and VAT volume were measured with 24 consecutive magnetic resonance images. Measurements in the validation group also included metabolic risk factors, i.e. blood pressure, HDL cholesterol, triglyceride, fasting glucose and HbA1c. Using multiple regression analyses for the derivation group, we determined the best prediction equation for abdominal VAT volume with a variance of 47% as follows: 47.03 age+117.79 BMI+74.18 waist circumference -8,792.7. In our validation group, the correlation coefficient between the measured and predicted VAT volumes was 0.74 (p<0.01). Furthermore, blood pressure, fasting glucose and HbA1c correlated with both measured and predicted VAT volumes. This study suggests that the equation model has potential to assess VAT accumulation levels in workers health checkup where CT and MRI are not available.

Visceral Adiposity Predicts Severity of Acute Pancreatitis

OBJECTIVES

The aim of this study was to determine the association of visceral adiposity with severe outcomes in acute pancreatitis (AP).

METHODS

This retrospective study included consecutive patients with AP admitted to a tertiary care hospital between January 2010 and January 2015 who underwent a computed tomography scan. The visceral adipose tissue (VAT) volume was estimated using the method of Linder and colleagues. Multivariable logistic regression analysis was conducted to assess VAT as a predictor of severe AP compared with other validated predictors of severity.

RESULTS

Five hundred and seventy four patients were admitted during the study period, of which 252 had a computed tomography scan available. Patients with severe AP had a larger VAT area compared with those with mild or moderate AP (mean: 184.9 cm vs 79.9 cm, P = 0.006). Patients who developed multisystem organ failure or had acute necrotic collections had a larger VAT area than those who did not (150.6 cm vs 91.0 cm, P = 0.004 and 174.0 cm vs 91.9 cm, P = 0.003, respectively). Visceral adipose tissue area demonstrated superior discrimination of severe AP compared with other severity predictors.

CONCLUSIONS

Increased VAT area is a strong predictor of severe pancreatitis, necrosis, and multisystem organ failure.

Chest Fat Quantification via CT Based on Standardized Anatomy Space in Adult Lung Transplant Candidates

Purpose

Overweight and underweight conditions are considered relative contraindications to lung transplantation due to their association with excess mortality. Yet, recent work suggests that body mass index (BMI) does not accurately reflect adipose tissue mass in adults with advanced lung diseases. Alternative and more accurate measures of adiposity are needed. Chest fat estimation by routine computed tomography (CT) imaging may therefore be important for identifying high-risk lung transplant candidates. In this paper, an approach to chest fat quantification and quality assessment based on a recently formulated concept of standardized anatomic space (SAS) is presented. The goal of the paper is to seek answers to several key questions related to chest fat quantity and quality assessment based on a single slice CT (whether in the chest, abdomen, or thigh) versus a volumetric CT, which have not been addressed in the literature.

Methods

Unenhanced chest CT image data sets from 40 adult lung transplant candidates (age 58 ± 12 yrs and BMI 26.4 ± 4.3 kg/m²), 16 with chronic obstructive pulmonary disease (COPD), 16 with idiopathic pulmonary fibrosis (IPF), and the remainder with other conditions were analyzed together with a single slice acquired for each patient at the L5 vertebral level and mid-thigh level. The thoracic body region and the interface between subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) in the chest were consistently defined in all patients and delineated using Live Wire tools. The SAT and VAT components of chest were then segmented guided by this interface. The SAS approach was used to identify the corresponding anatomic slices in each chest CT study, and SAT and VAT areas in each slice as well as their whole volumes were quantified. Similarly, the SAT and VAT components were segmented in the abdomen and thigh slices. Key parameters of the attenuation (Hounsfield unit (HU) distributions) were determined from each chest slice and from the whole chest volume separately for SAT and VAT components. The same parameters were also computed from the single abdominal and thigh slices. The ability of the slice at each anatomic location in the chest (and abdomen and thigh) to act as a marker of the measures derived from the whole chest volume was assessed via Pearson correlation coefficient (PCC) analysis.

Results

The SAS approach correctly identified slice locations in different subjects in terms of vertebral levels. PCC between chest fat volume and chest slice fat area was maximal at the T8 level for SAT (0.97) and at the T7 level for VAT (0.86), and was modest between chest fat volume and abdominal slice fat area for SAT and VAT (0.73 and 0.75, respectively). However, correlation was weak for chest fat volume and thigh slice fat area for SAT and VAT (0.52 and 0.37, respectively), and for chest fat volume for SAT and VAT and BMI (0.65 and 0.28, respectively). These same single slice locations with maximal PCC were found for SAT and VAT within both COPD and IPF groups. Most of the attenuation properties derived from the whole chest volume and single best chest slice for VAT (but not for SAT) were significantly different between COPD and IPF groups.

Conclusions

This study demonstrates a new way of optimally selecting slices whose measurements may be used as markers of similar measurements made on the whole chest volume. The results suggest that one or two slices imaged at T7 and T8 vertebral levels may be enough to estimate reliably the total SAT and VAT components of chest fat and the quality of chest fat as determined by attenuation distributions in the entire chest volume.

Automated quantification of abdominal adiposity by magnetic resonance imaging

OBJECTIVES

To develop a fully-automated algorithm to process axial magnetic resonance imaging (MRI) slices for quantifying abdominal visceral, subcutaneous and total adipose tissues, i.e., VAT, SAT, and TAT, without human intervention or prior knowledge.

MATERIALS AND METHODS

Fat regions in single MRI slice or sequence (20 slices) were identified with image processing techniques including region-growing, inhomogeneity correction, fuzzy c-means clustering, and active contours segmentation. The MR images of 85 subjects (60 males and 25 females), whose body mass index (BMI) values ranged from 19.96 to 40.35 kg/m2 , were analyzed using the fully-automated algorithm-the automatic method developed in the research and the widely used semi-automated software (sliceOmatic® Tomovision, Inc.)-the reference method.

RESULTS

The proposed automated method showed good performance against the reference method to quantify adipose tissues in both single umbilical slice and MRI sequence. The square of the Pearson correlation coefficients (R2 ) based on the results generated from the two methods for VAT/SAT/TAT were 0.977/0.998/0.997 for single slice data and 0.995/0.999/0.999 for volumetric data. The intra-class correlation of visceral adipose tissue (VAT) between the three operators was 0.939 in the reference method, which was improved to 0.999 in the automatic method. The adipose tissue measurements in the slice at Lumbar 3 vertebra have the highest correlation with the total fat volumes across the entire abdomen.

CONCLUSION

The fully-automated algorithm presented in the paper provides an accurate and reliable assessment of abdominal fat without human intervention. Am. J. Hum. Biol. 28:757-766, 2016. © 2016Wiley Periodicals, Inc.

The role of MRI in understanding the underlying mechanisms in obesity associated diseases

Obesity and its possible association with diseases including diabetes and cardiovascular diseases have been studied for decades for its impact on healthcare. Recent studies clearly indicate the need for developing accurate and reproducible methodologies for assessing body fat content and distribution. Body fat distribution plays a significant role in developing an insight in the underlying mechanisms in which adipose tissue is linked with various diseases. Among imaging technologies including computerized axial tomography (CAT or CT), magnetic resonance imaging (MRI), and magnetic resonance spectroscopy (MRS), MRI and MRS seem to be the best emerging techniques and together are being considered as the gold standard for body fat content and distribution. This paper reviews studies up to the present time involving different methodologies of these two emerging technologies and presents the basic concepts of MRI and MRS with required novel image analysis techniques in accurate, quantitative, and direct assessment of body fat content and distribution. This article is part of a Special Issue entitled: Oxidative Stress and Mitochondrial Quality in Diabetes/Obesity and Critical Illness Spectrum of Diseases - edited by P. Hemachandra Reddy.

Age and gender specific estimation of visceral adipose tissue amounts from radiological images in morbidly obese patients

Image-based quantifications of visceral adipose tissue (VAT) volumes from segmented VAT areas are increasingly considered for risk assessment in obese patients. The goal of this study was to determine the power of partial VAT areas to predict total VAT volume in morbidly obese patients (BMI > 40 kg/m²) as a function of gender, age and anatomical landmarks. 130 morbidly obese patients (mean BMI 46.5 kg/m²; 94 females) underwent IRB-approved MRI. Total VAT volumes were predicted from segmented VAT areas (of single or five adjacent slices) at common axial landmark levels and compared with the measured ones (V_VAT-T, about 40 slices between diaphragm and pelvic floor). Standard deviations σ₁ and σ₅ of the respective VAT volume differences served as measures of agreement. Mean V_VAT-T was 4.9 L for females and 8.1 L for males. Best predictions were found at intervertebral spaces L3-L4 for females (σ₅ = 688 ml, σ₁ = 832 ml) and L1-L2 for males (σ₅ = 846 ml, σ₁ = 992 ml), irrespective of age. In conclusion, VAT volumes in morbidly obese patients can be reliably predicted by multiplying the segmented VAT area at a gender-specific lumbar reference level with a fixed scaling factor and effective slice thickness.

Emerging Technologies and their Applications in Lipid Compartment Measurement

Non-Communicable diseases (NCDs), including obesity, are emerging as the major health concern of the 21st century. Excess adiposity and related NCD metabolic disturbances have stimulated development of new lipid compartment measurement technologies to help us to understand cellular energy exchange, to refine phenotypes, and to develop predictive markers of adverse clinical outcomes. Recent advances now allow quantification of multiple intracellular lipid and adipose tissue compartments that can be evaluated across the human lifespan. With magnetic resonance methods leading the way, newer approaches will give molecular structural and metabolic information beyond the laboratory in real-world settings. The union between these new technologies and the growing NCD population is creating an exciting interface in advancing our understanding of chronic disease mechanisms.

Segmentation and quantification of adipose tissue by magnetic resonance imaging

In this brief review, introductory concepts in animal and human adipose tissue segmentation using proton magnetic resonance imaging (MRI) and computed tomography are summarized in the context of obesity research. Adipose tissue segmentation and quantification using spin relaxation-based (e.g., T1-weighted, T2-weighted), relaxometry-based (e.g., T1-, T2-, T2*-mapping), chemical-shift selective, and chemical-shift encoded water-fat MRI pulse sequences are briefly discussed. The continuing interest to classify subcutaneous and visceral adipose tissue depots into smaller sub-depot compartments is mentioned. The use of a single slice, a stack of slices across a limited anatomical region, or a whole body protocol is considered. Common image post-processing steps and emerging atlas-based automated segmentation techniques are noted. Finally, the article identifies some directions of future research, including a discussion on the growing topic of brown adipose tissue and related segmentation considerations.