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.

Clinical and imaging findings associated with preservation of knee joint health over 8 years in individuals aged 65 and over: data from the OAI.

OBJECTIVE: While risk factors for osteoarthritis (OA) are well known, it is not well understood why certain individuals maintain high mobility and joint health throughout their life while others demonstrate OA at older ages. The purpose of this study was to assess which demographic, clinical and MRI quantitative and semi-quantitative factors are associated with preserving healthy knees in older individuals. METHODS: This study analyzed data from the OA Initiative (OAI) cohort of individuals at the age of 65 years or above. Participants without OA at baseline (BL) (Kellgren-Lawrence (KL) ≤ 1) were followed and classified as incident cases (KL ≥ 2 during follow-up; n = 115) and as non-incident (KL ≤ 1 over 96-month; n = 391). Associations between the predictor-variables sex, age, BMI, race, clinical scoring systems, T2 relaxation times and Whole-Organ Magnetic Resonance Imaging-Score (WORMS) readings at BL and the preservation of healthy knees (KL ≤ 1) during a 96-month follow-up period were assessed using logistic regression models. RESULTS: Obesity and presence of pain showed a significant inverse association with maintaining radiographically normal joints in patients aged 65 and above. T2 relaxation times of the lateral femur and tibia as well as the medial femur were also significantly associated with maintaining radiographically normal knee joints. Additionally, absence of lesions of the lateral meniscus and absence of cartilage lesions in the medial and patellofemoral compartments were significantly associated with maintaining healthy knee joints. CONCLUSION: Overall, this study provides protective clinical parameters as well as quantitative and semi-quantitative MR-imaging parameters associated with maintaining radiographically normal knee joints in an older population over 8 years.

Hyperostosis frontalis interna on fluorine-18 sodium fluoride PET/computed tomography of obese cancer patients: a potential mimicker of metastasis.

OBJECTIVE: The objective of this retrospective study was to identify the uptake patterns and suggest a quantitative method to detect hyperostosis frontalis interna (HFI) on fluorine-18 sodium fluoride ([ 18 F]NaF) PET/computed tomography (CT). METHODS: Between January 2019 and December 2021, patients who underwent [ 18 F]NaF PET/CT with a BMI of 30 and above, were included. Three nuclear medicine consultants reviewed the studies to determine the presence and identify the uptake patterns of HFI. Quantitative evaluation was performed on PET images using the total number of counts over the frontal bone and the ratio of counts between the frontal bone and iliac crest. RESULTS: A total of 105 out of 249 cases were included in this study. Among these scans, there were 67 positive HFI in [ 18 F]NaF PET scans representing 64% of the studied population. As for the [ 18 F]NaF PET uptake pattern, there were 53 with uniformly diffused and 14 with heterogeneous uptake pattern. There were 17 out of 67 with positive HFI in [ 18 F]NaF PET scans but negative CT scans. CONCLUSION: HFI is a common finding on [ 18 F]NaF PET in obese patients and is probably underdiagnosed. HFI may present with a heterogeneous and diffuse pattern of uptake on [ 18 F]NaF PET. The proposed quantitative analysis using the count ratios is in agreement with the visual evaluation of [ 18 F]NaF PET images regardless of the CT findings. Awareness of this condition and its scintigraphic patterns is warranted since it can have clinical significance and may mimic other pathologies including metastasis in cancer patients.

A PET/MRI study on the effect of obesity and NAFLD on hepatic [18F]FDG uptake.

PURPOSE: The potential limitations of hepatic [18F]FDG-PET imaging for individuals with obesity and excessive liver fat (NAFLD) are being investigated. In this study, we aim to determine the reliability of standardized uptake values (SUVs) focusing on adjustment for liver fat content (LFC) derived from DIXON images and the effects of whole-body normalizations. METHODS: Lean and with obesity volunteers who underwent [18F]FDG-PET/MRI were reviewed retrospectively. DIXON fat images were used to determine LFC and for adjustment of SUVmean. The hepatic SUVs (mean, fat adjusted mean and max) were normalized to body weight, lean body mass and body surface area. Blood samples were analysed for glucose, serological liver enzymes and lipoproteins for further correlation of [18F]FDG uptake. RESULTS: Out of 11 volunteers with obesity (M:8, F:3, BMI:30-39 kg/m2), 9 confirmed the presence of NAFLD (>5.6 % fat). 22 age-matched lean volunteers (M:10, F:11, BMI:19-26 kg/m2) were used as control group. Both SUVmean, before and after adjustment to LFC, did not provide any difference between lean and with obesity groups under BW, LBM and BSA. SUVmax BW showed a difference between groups (p = 0.05). SUVs were independent of levels of GPT, GOT, gGT, insulin, HOMA-IR, triglycerides, cholesterol and LDL. Volunteers with low HDL were clustered with an increased hepatic [18F]FDG uptake. CONCLUSION: Our method for adjustment of hepatic [18F]FDG-PET with DIXON fat images allows to achieve accurate results for individuals with NAFLD and obesity. For homogenic results, raw SUVmean should be combined with adjustment for liver fat, appropriate normalization and consideration of HDL levels.

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.

CT and MR utilization and morbidity metrics across Body Mass Index.

OBJECTIVE: Obesity is a high-morbidity chronic condition and risk factor for multiple diseases that necessitate imaging. This study assesses the relationship between BMI and same-year utilization of CT and MR imaging in a large healthcare population. METHODS: In this retrospective population-based study, all patients aged ≥18 years with a documented BMI in the multi-institutional Cosmos database were included. Cohorts were identified based on ≥1 documented BMI in 2021 within pre-defined ranges. For each cohort, we assessed the percentage of patients undergoing head, neck, chest, spine, or abdomen/pelvis CT and MR during the same year. Disease severity was quantified based on emergency department (ED) visits and mortality. RESULTS: In our population of 49.6 million patients, same-year CT and MR utilization was 14.5 ±0.01% and 6.0±0.01%, respectively. The underweight cohort had the highest CT (25.8±0.1%) and MR (8.01 ± 0.05) imaging utilization. At high extremes of BMI (>50 kg/m2), CT utilization mildly increased (18.4±0.1%), but MR utilization decreased (5.3±0.04%). While morbidity differences may explain some BMI-utilization relationships, lower MR utilization in the BMI>50 cohort contrasts with higher age-adjusted mortality (1.8±0.03%) and ED utilization (32.4±0.1%) in this cohort relative to normal weight (1.5±0.01% and 25.7±0.02%, respectively). CONCLUSION: Underweight patients had disproportionately high CT/MR utilization, and high extremes of BMI are associated with mildly higher CT and lower MR utilization than the normal weight cohort. The elevated mortality and ED utilization in severely obese patients contrasts with their lower MR imaging utilization. Our findings may assist public health efforts to accommodate obesity trends.

Evaluating Sex-specific Differences in Abdominal Fat Volume and Proton Density Fat Fraction at MRI Using Automated nnU-Net-based Segmentation.

Sex-specific abdominal organ volume and proton density fat fraction (PDFF) in people with obesity during a weight loss intervention was assessed with automated multiorgan segmentation of quantitative water-fat MRI. An nnU-Net architecture was employed for automatic segmentation of abdominal organs, including visceral and subcutaneous adipose tissue, liver, and psoas and erector spinae muscle, based on quantitative chemical shift-encoded MRI and using ground truth labels generated from participants of the Lifestyle Intervention (LION) study. Each organ's volume and fat content were examined in 127 participants (73 female and 54 male participants; body mass index, 30-39.9 kg/m2) and in 81 (54 female and 32 male participants) of these participants after an 8-week formula-based low-calorie diet. Dice scores ranging from 0.91 to 0.97 were achieved for the automatic segmentation. PDFF was found to be lower in visceral adipose tissue compared with subcutaneous adipose tissue in both male and female participants. Before intervention, female participants exhibited higher PDFF in subcutaneous adipose tissue (90.6% vs 89.7%; P < .001) and lower PDFF in liver (8.6% vs 13.3%; P < .001) and visceral adipose tissue (76.4% vs 81.3%; P < .001) compared with male participants. This relation persisted after intervention. As a response to caloric restriction, male participants lost significantly more visceral adipose tissue volume (1.76 L vs 0.91 L; P < .001) and showed a higher decrease in subcutaneous adipose tissue PDFF (2.7% vs 1.5%; P < .001) than female participants. Automated body composition analysis on quantitative water-fat MRI data provides new insights for understanding sex-specific metabolic response to caloric restriction and weight loss in people with obesity. Keywords: Obesity, Chemical Shift-encoded MRI, Abdominal Fat Volume, Proton Density Fat Fraction, nnU-Net ClinicalTrials.gov registration no. NCT04023942 Supplemental material is available for this article. Published under a CC BY 4.0 license.

Age and BMI have different effects on subcutaneous, visceral, liver, bone marrow, and muscle adiposity, as measured by CT and MRI.

OBJECTIVE: We analyzed quantitative computed tomography (CT) and chemical shift-encoded magnetic resonance imaging (MRI) data from a Chinese cohort to investigate the effects of BMI and aging on different adipose tissue (AT) depots. METHODS: In 400 healthy, community-dwelling individuals aged 22 to 83 years, we used MRI to quantify proton density fat fraction (PDFF) of the lumbar spine (L2-L4) bone marrow AT (BMAT), the psoas major and erector spinae (ES) muscles, and the liver. Abdominal total AT, visceral AT (VAT), and subcutaneous AT (SAT) areas were measured at the L2-L3 level using quantitative CT. Partial correlation analysis was used to evaluate the relationship of each AT variable with age and BMI. Multiple linear regression analysis was performed in which each AT variable was evaluated in turn as a function of age and the other five independent AT measurements. RESULTS: Of the 168 men, 29% had normal BMI (<24.0 kg/m2), 47% had overweight (24.0-27.9 kg/m2), and 24% had obesity (≥ 28.0 kg/m2). In the 232 women, the percentages were 46%, 32%, and 22%, respectively. Strong or very strong correlations with BMI were found for total AT, VAT, and SAT in both sexes. BMAT and ES PDFF was strongly correlated with age in women and moderately correlated in men. In both sexes, BMAT PDFF correlated only with age and not with any of the other AT depots. Psoas PDFF correlated only with ES PDFF and not with age or the other AT depots. Liver PDFF correlated with BMI and VAT and weakly with SAT in men. VAT and SAT correlated with age and each other in both sexes. CONCLUSIONS: Age and BMI are both associated with adiposity, but their effects differ depending on the type of AT.

Effect of Liraglutide in Different Abdominal Fat Layers Measured by Ultrasound: The Importance of Perirenal Fat Reduction.

INTRODUCTION: Ultrasonography (US) in patients with obesity allows us to measure different layers of abdominal fat (superficial subcutaneous, deep subcutaneous, preperitoneal, omental, and perirenal), not assessable by DEXA or CT scan. Omental and perirenal fat depots are considered predictors of metabolic complications. Liraglutide is particularly effective in reducing weight in patients with insulin-resistance, but its direct impact on each abdominal fat layer is unknown. METHODS: We measured, at the L4 level, all 5 abdominal fat depots in 860 patients with obesity (72.8% women, mean age 56.6 ± 1.5 years, BMI 34.4 ± 4.7 kg/m2, body fat 47 ± 2%, abdominal circumference 105.8 ± 3 cm), before and after 6 months of liraglutide treatment. Laboratory tests for glucose, insulin, and lipid profile were routinely done. T-student was used to compare intraindividual differences. RESULTS: Weight loss was 7.5 ± 2.8 kg (7.96% from baseline), with no differences by sex/age/BMI. Greater loss was observed in patients with higher dosages and NAFLD. All US-measured fat layers showed a significant reduction (p < 0.05) at 6th months. Preperitoneal fat showed a -26 ± 5.5% reduction and 46% of the patients went below metabolic syndrome (MS) risk cut-off values. Omental fat was reduced by -17.8 ± 5% (67% of the patients below MS risk) and perirenal fat by -22.4 ± 4.4% (56% of the patients below MS). Both omental and perirenal fat reduction correlated with total and LDL cholesterol. Higher perirenal fat reduction (-28%) was seen among patients with obesity and hypertension. Perirenal fat also correlated with blood pressure reduction. CONCLUSION: Liraglutide induces greater fat loss in the layers involved with MS. However, the maximal reduction is seen at perirenal fat, which has been recently related with hypertension and could play an important role in modulating kidney's expansion and intraglomerular pressure. US is a reproducible clinical tool to assess pathologic fat depots in patients living with obesity.

Velocity-selective arterial spin labeling perfusion measurements in 2nd trimester human placenta with varying BMI.

INTRODUCTION: Proper placental development is crucial to fetal health but is challenging to functionally assess non-invasively and is thus poorly characterized in populations. Body mass index (BMI) has been linked with adverse outcomes, but the causative mechanism is uncertain. Velocity-selective arterial spin labeling (VS-ASL) MRI provides a method to non-invasively measure placental perfusion with robustness to confounding transit time delays. In this study, we report on the measurement of perfusion in the human placenta in early pregnancy using velocity-selective arterial spin labeling (VS-ASL) MRI, comparing non-obese and obese participants. METHODS: Participants (N = 97) undergoing routine prenatal care were recruited and imaged with structural and VS-ASL perfusion MRI at 15 and 21 weeks gestation. Resulting perfusion images were analyzed with respect to obesity based on BMI, gestational age, and the presence of adverse outcomes. RESULTS: At 15 weeks gestation BMI was not associated with placental perfusion or perfusion heterogeneity. However, at 21 weeks gestation BMI was associated with higher placental perfusion (p < 0.01) and a decrease in perfusion heterogeneity (p < 0.05). In alignment with past studies, perfusion values were also higher at 21 weeks compared to 15 weeks gestation. In a small cohort of participants with adverse outcomes, at 21 weeks lower perfusion was observed compared to participants with uncomplicated pregnancies. DISCUSSION: These results suggest low placental perfusion in the early second trimester may not be the culpable factor driving associations of obesity with adverse outcomes.

Effect of weight loss on knee joint synovitis over 48 months and mediation by subcutaneous fat around the knee: data from the Osteoarthritis Initiative.

BACKGROUND: Obesity influences the development of osteoarthritis via low-grade inflammation. Progression of local inflammation (= synovitis) increased with weight gain in overweight and obese women compared to stable weight. Synovitis could be associated with subcutaneous fat (SCF) around the knee. Purpose of the study was to investigate the effect of weight loss on synovitis progression and to assess whether SCF around the knee mediates the relationship between weight loss and synovitis progression. METHODS: We included 234 overweight and obese participants (body mass index [BMI] ≥ 25 kg/m2) from the Osteoarthritis Initiative (OAI) with > 10% weight loss (n = 117) or stable overweight (< ± 3% change, n = 117) over 48 months matched for age and sex. In magnetic resonance imaging (MRI) at baseline and 48 months, effusion-synovitis and Hoffa-synovitis using the MRI Osteoarthritis Knee Score (MOAKS) and average joint-adjacent SCF (ajSCF) were assessed. Odds-ratios (ORs) for synovitis progression over 48 months (≥ 1 score increase) were calculated in logistic regression models adjusting for age, sex, baseline BMI, Physical Activity Scale for the Elderly (PASE), and baseline SCF measurements. Mediation of the effect of weight loss on synovitis progression by local SCF change was assessed. RESULTS: Odds for effusion-synovitis progression decreased with weight loss and ajSCF decrease (odds ratio [OR] = 0.61 and 0.56 per standard deviation [SD] change, 95% confidence interval [CI] 0.44, 0.83 and 0.40, 0.79, p = 0.002 and 0.001, respectively), whereas odds for Hoffa-synovitis progression increased with weight loss and ajSCF decrease (OR = 1.47 and 1.48, CI 1.05, 2.04 and 1.02, 2.13, p = 0.024 and 0.038, respectively). AjSCF decrease mediated 39% of the effect of weight loss on effusion-synovitis progression. CONCLUSIONS: Effusion-synovitis progression was slowed by weight loss and decrease in local subcutaneous fat. Hoffa-synovitis characterized by fluid in the infrapatellar fat pad increased at the same time, suggesting a decreasing fat pad rather than active synovitis. Decrease in local subcutaneous fat partially mediated the systemic effect of weight loss on synovitis.

A Learning Curve for First-Trimester Anatomy Ultrasound in Obese Patients.

OBJECTIVES: A recent randomized controlled trial of first-trimester anatomy ultrasound in obese women found some advantages to using this technique in this population, but some aspects of feasibility were not clear, such as whether first-trimester ultrasound can be brought outside of a research setting. The learning curve for first-trimester anatomy has been described in the general population, but a learning curve has not been described for this technique in obese patients. This study sought to describe a learning curve for first-trimester anatomy ultrasounds in obese patients with an operator familiar with the basics of first-trimester imaging. DESIGN: This was a secondary analysis of the EASE-O pilot randomized controlled trial (NCT04639973), which recruited 128 women with a BMI ≥35 kg/m2 and randomized them into two groups based on the timing of the first evaluation of fetal anatomy, to compare the completion rate of first- and second-trimester anatomy ultrasound. PARTICIPANTS: Pregnant women with a BMI ≥35 kg/m2 participated in the study. SETTING: Between January 2021 and February 2022, the study was conducted at maternal-fetal medicine clinics in Houston, TX, USA. METHODS: This secondary analysis evaluated data on the completion rate of first-trimester scans from the parent trial. Scans were grouped into bin sizes of 3, and prop_model for R version 4.2.0 for Windows was used to generate a learning curve across the first 60 scans. RESULTS: The parent study included 60 scans performed by one imager who had previously only done first-trimester scans in lean patients for limited anatomy. The probability of a complete scan increased over 60 scans from 0.38 to 0.69; 29 scans were required to reach the final probability, after which only marginal improvement followed. LIMITATIONS: The major limitation is the inclusion of only one operator for this curve. CONCLUSIONS: For an ultrasound operator with basic familiarity in first-trimester imaging, approximately 30 scans are needed to acquire a completion rate of 70% for detailed first-trimester anatomy in women with BMI ≥35 kg/m2. This can be used in education and training programs focused on imaging in the first trimester.

Correlation between magnetic resonance imaging proton density fat fraction (MRI-PDFF) and liver biopsy to assess hepatic steatosis in obesity.

Obesity is highly associated with Non-alcoholic fatty liver disease (NAFLD) and increased risk of liver cirrhosis and liver cancer-related death. We determined the diagnostic performance of the complex-based chemical shift technique MRI-PDFF for quantifying liver fat and its correlation with histopathologic findings in an obese population within 24 h before bariatric surgery. This was a prospective, cross-sectional, Institutional Review Board-approved study of PDFF-MRI of the liver and MRI-DIXON image volume before bariatric surgery. Liver tissues were obtained during bariatric surgery. The prevalence of NAFLD in the investigated cohort was as high as 94%. Histologic hepatic steatosis grades 0, 1, 2, and 3 were observed in 3 (6%), 25 (50%), 14 (28%), and 8 (16%) of 50 obese patients, respectively. The mean percentages of MRI-PDFF from the anterior and posterior right hepatic lobe and left lobe vs. isolate left hepatic lobe were 15.6% (standard deviation [SD], 9.28%) vs. 16.29% (SD, 9.25%). There was a strong correlation between the percentage of steatotic hepatocytes and MRI-PDFF in the left hepatic lobe (r = 0.82, p < 0.001) and the mean value (r = 0.78, p < 0.001). There was a strong correlation between MRI-derived subcutaneous adipose tissue volume and total body fat mass by dual-energy X-ray absorptiometry, especially at the L2-3 and L4 level (r = 0.85, p < 0.001). MRI-PDFF showed good performance in assessing hepatic steatosis and was an excellent noninvasive technique for monitoring hepatic steatosis in an obese population.

White adipose tissue distribution and amount are associated with increased white matter connectivity.

Obesity represents a significant public health concern and is linked to various comorbidities and cognitive impairments. Previous research indicates that elevated body mass index (BMI) is associated with structural changes in white matter (WM). However, a deeper characterization of body composition is required, especially considering the links between abdominal obesity and metabolic dysfunction. This study aims to enhance our understanding of the relationship between obesity and WM connectivity by directly assessing the amount and distribution of fat tissue. Whole-body magnetic resonance imaging (MRI) was employed to evaluate total adipose tissue (TAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT), while MR liver spectroscopy measured liver fat content in 63 normal-weight, overweight, and obese males. WM connectivity was quantified using microstructure-informed tractography. Connectome-based predictive modeling was used to predict body composition metrics based on WM connectomes. Our analysis revealed a positive dependency between BMI, TAT, SAT, and WM connectivity in brain regions involved in reward processing and appetite regulation, such as the insula, nucleus accumbens, and orbitofrontal cortex. Increased connectivity was also observed in cognitive control and inhibition networks, including the middle frontal gyrus and anterior cingulate cortex. No significant associations were found between WM connectivity and VAT or liver fat. Our findings suggest that altered neural communication between these brain regions may affect cognitive processes, emotional regulation, and reward perception in individuals with obesity, potentially contributing to weight gain. While our study did not identify a link between WM connectivity and VAT or liver fat, further investigation of the role of various fat depots and metabolic factors in brain networks is required to advance obesity prevention and treatment approaches.

Increased brain fractional perfusion in obesity using intravoxel incoherent motion (IVIM) MRI metrics.

OBJECTIVE: This research seeks to shed light on the associations between brain perfusion, cognitive function, and mental health in individuals with and without obesity. METHODS: In this study, we employed the noninvasive intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) technique to examine brain fractional perfusion (FP) in two groups: individuals with obesity (N = 72) and healthy controls (N = 66). Additionally, we investigated potential associations between FP, cognitive function, and depressive symptoms in the participants with and without obesity. Finally, artificial intelligence algorithms (Boruta analysis) were also used. RESULTS: Participants with obesity exhibited increased FP within dopaminergic brain circuits, particularly involving prefrontal cortex areas, anterior and posterior sections of the cingulate cortex, the right striatum, and the midbrain. Additionally, these individuals demonstrated lower working memory and higher depressive symptoms compared to the control group. Notably, higher FP in the inferior temporal and occipital cortices correlated with greater depressive symptoms, whereas increased FP in the right ventral caudate and the midbrain was associated with better working memory performance. A link between inflammatory and metabolic variables, with a particular emphasis on monocytes, and FP in obesity was also evidenced by Boruta analysis. CONCLUSIONS: Increased brain perfusion in individuals with obesity is associated with cognitive function and mental health through interaction with metabolic and inflammatory factors.

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.

Ultrasound-based measurement of central adiposity: Key considerations and guidelines.

Central adiposity, which is visceral and subcutaneous adiposity in the abdominal region, is a known risk factor for developing chronic cardiometabolic diseases. Central adiposity can be measured relatively inexpensively using ultrasound. Ultrasound has been shown to be precise and reliable, with measurement accuracy comparable to computed tomography and magnetic resonance. Despite the advantages conferred by ultrasound, widespread adoption has been hindered by lack of reliable standard operating procedures. To consolidate the literature and bring clarity to the use of ultrasound-derived measures of central adiposity, this review outlines (i) the [patho]physiological importance of central adiposity to cardiometabolic disease risk; (ii) an overview of the history and main technical aspects of ultrasound methodology; (iii) key measurement considerations, including transducer selection, subject preparation, image acquisition, image analysis, and operator training; and (iv) guidelines for standardized ultrasound protocols for measuring central adiposity.

Obesity is associated with alterations in anatomical connectivity of frontal-corpus callosum.

Obesity has been linked to abnormal frontal function, including the white matter fibers of anterior portion of the corpus callosum, which is crucial for information exchange within frontal cortex. However, alterations in white matter anatomical connectivity between corpus callosum and cortical regions in patients with obesity have not yet been investigated. Thus, we enrolled 72 obese and 60 age-/gender-matched normal weight participants who underwent clinical measurements and diffusion tensor imaging. Probabilistic tractography with connectivity-based classification was performed to segment the corpus callosum and quantify white matter anatomical connectivity between subregions of corpus callosum and cortical regions, and associations between corpus callosum-cortex white matter anatomical connectivity and clinical behaviors were also assessed. Relative to normal weight individuals, individuals with obesity exhibited significantly greater white matter anatomical connectivity of corpus callosum-orbitofrontal cortex, which was positively correlated with body mass index and self-reported disinhibition of eating behavior, and lower white matter anatomical connectivity of corpus callosum-prefrontal cortex, which was significantly negatively correlated with craving for high-calorie food cues. The findings show that alterations in white matter anatomical connectivity between corpus callosum and frontal regions involved in reward and executive control are associated with abnormal eating behaviors.

Adiposity influences on myocardial deformation: a cardiovascular magnetic resonance feature tracking study in people with overweight to obesity without established cardiovascular disease.

The objective of this study was to assess whether dietary-induced weight loss improves myocardial deformation in people with overweight to obesity without established cardiovascular disease applying cardiovascular magnetic resonance (CMR) with feature tracking (FT) based strain analysis. Ninety people with overweight to obesity without established cardiovascular disease (age 44.6 ± 9.3 years, body mass index (BMI) 32.6 ± 4 kg/m2) underwent CMR. We retrospectively quantified FT based strain and LA size and function at baseline and after a 6-month hypocaloric diet, with either low-carbohydrate or low-fat intake. The study cohort was compared to thirty-four healthy normal-weight controls (age 40.8 ± 16.0 years, BMI 22.5 ± 1.4 kg/m2). At baseline, the study cohort with overweight to obesity without established cardiovascular disease displayed significantly increased global circumferential strain (GCS), global radial strain (GRS) and LA size (all p < 0.0001 versus controls) but normal global longitudinal strain (GLS) and normal LA ejection fraction (all p > 0.05 versus controls). Dietary-induced weight loss led to a significant reduction in GCS, GRS and LA size irrespective of macronutrient composition (all p < 0.01). In a population with overweight to obesity without established cardiovascular disease subclinical myocardial changes can be detected applying CMR. After dietary-induced weight loss improvement of myocardial deformation could be shown. A potential clinical impact needs further studies.