Relationship Between Prepatellar Fat Thickness and Bone Mineral Density.

OBJECTIVE: To evaluate the relationship between bone mineral density (BMD) by measuring the prepatellar fat thickness with knee radiography and to gain a measurement method that has not been done before in the literature. STUDY DESIGN: Cross-sectional descriptive study. Place and Duration of the Study: Department of Physical Medicine and Rehabilitation, Training and Research Hospital, Sanliurfa, Turkiye, between January and June 2020. METHODOLOGY: Patients' age, body mass index (BMI) data, prepatellar fat thickness (mm), L1-L4 total, bone mineral density femoral neck, femur trochanter major, and femur total T scores were recorded. The relationships between these three groups (normal, osteopenia, osteoporosis) and between prepatellar fat tissue measurement were evaluated. One-way analysis of variance (ANOVA) and Post Hoc Tukey tests were used in the analysis. RESULTS:  A statistically significant difference was found in terms of trochanter major T score measurements (X2 = 20.435; p <0.001) and BMI (X2 = 66.535; p <0.001) measurements of prepatellar fat thickness measurement. A statistically significant difference was found between the three groups in terms of prepatellar fat thickness measurement, L1-4 T-score, femoral neck, and femur total values (p <0.001). CONCLUSION:  Prepatellar fat thickness in postmenopausal Turkish women was positively correlated with BMD; BMD increases as the prepatellar fat thickness increases. This explains that perapatellar fat thickness creates a mechanical load on the bones and causes an increase in BMD. KEY WORDS: Osteoporosis, Fat thickness, Bone mineral density.

Deep-Learning Based Automated Segmentation and Quantitative Volumetric Analysis of Orbital Muscle and Fat for Diagnosis of Thyroid Eye Disease.

Purpose: Thyroid eye disease (TED) is characterized by proliferation of orbital tissues and complicated by compressive optic neuropathy (CON). This study aims to utilize a deep-learning (DL)-based automated segmentation model to segment orbital muscle and fat volumes on computed tomography (CT) images and provide quantitative volumetric data and a machine learning (ML)-based classifier to distinguish between TED and TED with CON. Methods: Subjects with TED who underwent clinical evaluation and orbital CT imaging were included. Patients with clinical features of CON were classified as having severe TED, and those without were classified as having mild TED. Normal subjects were used for controls. A U-Net DL-model was used for automatic segmentation of orbital muscle and fat volumes from orbital CTs, and ensemble of Random Forest Classifiers were used for volumetric analysis of muscle and fat. Results: Two hundred eighty-one subjects were included in this study. Automatic segmentation of orbital tissues was performed. Dice coefficient was recorded to be 0.902 and 0.921 for muscle and fat volumes, respectively. Muscle volumes among normal, mild, and severe TED were found to be statistically different. A classification model utilizing volume data and limited patient data had an accuracy of 0.838 and an area under the curve (AUC) of 0.929 in predicting normal, mild TED, and severe TED. Conclusions: DL-based automated segmentation of orbital images for patients with TED was found to be accurate and efficient. An ML-based classification model using volumetrics and metadata led to high diagnostic accuracy in distinguishing TED and TED with CON. By enabling rapid and precise volumetric assessment, this may be a useful tool in future clinical studies.

Epicardial adipose tissue volume assessed by cardiac CT as a predictor of atrial fibrillation recurrence following catheter ablation.

INTRODUCTION: In patients with atrial fibrillation (AF), up to one third have recurrence after a first catheter ablation (CA). Epicardial adipose tissue (EAT) has been considered to be closely related to AF, with a potential role in its recurrence. We aimed to evaluate the association between the volume of EAT measured by cardiac computed tomography (CT) and AF recurrence after CA. METHODS: Consecutive AF patients underwent a standardized cardiac CT protocol for quantification of EAT, thoracic adipose volume (TAV) and left atrium (LA) volume before CA. An appropriate cut-off of EAT was determined and risk recurrence was estimated. RESULTS: 305 patients (63.6 % male, mean age 57.5 years, 28.2 % persistent AF) were followed for 24 months; 23 % had AF recurrence at 2-year mark, which was associated with higher EAT (p = 0.037) and LAV (p < 0.001). Persistent AF was associated with higher EAT volumes (p = 0.010), TAV (p = 0.003) and LA volumes (p < 0.001). EAT was predictive of AF recurrence (p = 0.044). After determining a cut-off of 92 cm3, survival analysis revealed that EAT volumes > 92 cm3 showed higher recurrence rates at earlier time points after the index ablation procedure (p = 0.006), with a HR of 1.95 (p = 0.008) of AF recurrence at 2-year. After multivariate adjustment, EAT > 92 cm3 remained predictive of AF recurrence (p = 0.028). CONCLUSION: The volume of EAT measured by cardiac CT can predict recurrence of AF after ablation, with a volume above 92 cm3 yielding almost twice the risk of arrhythmia recurrence in the first two years following CA. Higher EAT and TAV are also associated with persistent AF.

Correlation of epicardial adipose tissue and inflammatory indices in patients with STEMI and implications for atrial arrhythmias.

BACKGROUND: Epicardial adipose tissue(EAT) is associated with inflammation in previous studies but is unknown in patients with ST-segment elevation myocardial infarction(STEMI).This study investigated the correlation between epicardial fat and inflammatory cells obtained by cardiac magnetic resonance (CMR) and the effect on atrial arrhythmias in patients with STEMI. METHODS: This was a single-center, retrospective study. We consecutively selected patients who all completed CMR after Percutaneous Coronary Intervention (PCI) from January 2019 to December 2022 and then had regular follow-ups at 1, 3, 6, 9, and 12 months. The enrolled patients were grouped according to the presence or absence of atrial arrhythmia and divided into atrial and non-atrial arrhythmia groups. RESULTS: White blood cell, neutrophil, lymphocyte, C-reactive protein, EATV, LVES, LVED were higher in the atrial arrhythmia group than in the non-atrial arrhythmia group, and LVEF was lower than that in the non-atrial arrhythmia group (p < 0.05); EATV was significantly positively correlated with each inflammatory indices (white blood cell: r = 0.415 p < 0.001, neutrophil:r = 0.386 p < 0.001, lymphocyte:r = 0.354 p < 0.001, C-reactive protein:r = 0.414 p < 0.001); one-way logistic regression analysis showed that risk factors for atrial arrhythmias were age, heart rate, white blood cell, neutrophil, lymphocyte, C-reactive protein, EATV, LVES, LVED; multifactorial logistic regression analysis showed that neutrophil, lymphocyte, C-reactive protein, EATV, and LVES were independent risk factors for atrial arrhythmias; ROC analysis showed that the area under the curve (AUC) for neutrophil was 0.862; the AUC for lymphocyte was 1.95; and the AUC for C-reactive protein was 0.862. reactive protein was 0.852; AUC for LVES was 0.683; and AUC for EATV was 0.869. CONCLUSION: In patients with STEMI, EAT was significantly and positively correlated with inflammatory indices; neutrophil, lymphocyte, C-reactive protein, EATV, and LVES were independent risk factors for atrial arrhythmias and had good predictive value.

Hepatic steatosis modeling and MRI signal simulations for comparison of single- and dual-R2* models and estimation of fat fraction at 1.5T and 3T.

BACKGROUND AND OBJECTIVE: Magnetic resonance imaging (MRI) has emerged as a noninvasive clinical tool for assessment of hepatic steatosis. Multi-spectral fat-water MRI models, incorporating single or dual transverse relaxation decay rate(s) (R2*) have been proposed for accurate fat fraction (FF) estimation. However, it is still unclear whether single- or dual-R2* model accurately mimics in vivo signal decay for precise FF estimation and the impact of signal-to-noise ratio (SNR) on each model performance. Hence, this study aims to construct virtual steatosis models and synthesize MRI signals with different SNRs to systematically evaluate the accuracy of single- and dual-R2* models for FF and R2* estimations at 1.5T and 3.0T. METHODS: Realistic hepatic steatosis models encompassing clinical FF range (0-60 %) were created using morphological features of fat droplets (FDs) extracted from human liver biopsy samples. MRI signals were synthesized using Monte Carlo simulations for noise-free (SNRideal) and varying SNR conditions (5-100). Fat-water phantoms were scanned with different SNRs to validate simulation results. Fat water toolbox was used to calculate R2* and FF for both single- and dual-R2* models. The model accuracies in R2* and FF estimates were analyzed using linear regression, bias plot and heatmap analysis. RESULTS: The virtual steatosis model closely mimicked in vivo fat morphology and Monte Carlo simulation produced realistic MRI signals. For SNRideal and moderate-high SNRs, water R2* (R2*W) by dual-R2* and common R2* (R2*com) by single-R2* model showed an excellent agreement with slope close to unity (0.95-1.01) and R2 > 0.98 at both 1.5T and 3.0T. In simulations, the R2*com-FF and R2*W-FF relationships exhibited slopes similar to in vivo calibrations, confirming the accuracy of our virtual models. For SNRideal, fat R2* (R2*F) was similar to R2*W and dual-R2* model showed slightly higher accuracy in FF estimation. However, in the presence of noise, dual-R2* produced higher FF bias with decreasing SNR, while leading to only marginal improvement for high SNRs and in regions dominated by fat and water. In contrast, single-R2* model was robust and produced accurate FF estimations in simulations and phantom scans with clinical SNRs. CONCLUSION: Our study demonstrates the feasibility of creating virtual steatosis models and generating MRI signals that mimic in vivo morphology and signal behavior. The single-R2* model consistently produced lower FF bias for clinical SNRs across entire FF range compared to dual-R2* model, hence signifying that single-R2* model is optimal for assessing hepatic steatosis.

Elexacaftor/tezacaftor/ivacaftor influences body composition in adults with cystic fibrosis: a fully automated CT-based analysis.

A poor nutritional status is associated with worse pulmonary function and survival in people with cystic fibrosis (pwCF). CF transmembrane conductance regulator modulators can improve pulmonary function and body weight, but more data is needed to evaluate its effects on body composition. In this retrospective study, a pre-trained deep-learning network was used to perform a fully automated body composition analysis on chest CTs from 66 adult pwCF before and after receiving elexacaftor/tezacaftor/ivacaftor (ETI) therapy. Muscle and adipose tissues were quantified and divided by bone volume to obtain body size-adjusted ratios. After receiving ETI therapy, marked increases were observed in all adipose tissue ratios among pwCF, including the total adipose tissue ratio (+ 46.21%, p < 0.001). In contrast, only small, but statistically significant increases of the muscle ratio were measured in the overall study population (+ 1.63%, p = 0.008). Study participants who were initially categorized as underweight experienced more pronounced effects on total adipose tissue ratio (p = 0.002), while gains in muscle ratio were equally distributed across BMI categories (p = 0.832). Our findings suggest that ETI therapy primarily affects adipose tissues, not muscle tissue, in adults with CF. These effects are primarily observed among pwCF who were initially underweight. Our findings may have implications for the future nutritional management of pwCF.

Imaging and prognostic characterization of fat-containing hepatocellular carcinoma subtypes.

PURPOSE: Steatohepatitic hepatocellular carcinoma (SH-HCC) is characterized by intratumoral fat with > 50% inflammatory changes. However, intratumoral fat (with or without inflammation) can also be found in not-otherwise specified HCC (NOS-HCC). We compared the imaging features and outcome of resected HCC containing fat on pathology including SH-HCC (> 50% steatohepatitic component), NOS-HCC with < 50% steatohepatitic component (SH-NOS-HCC), and fatty NOS-HCC (no steatohepatitic component). MATERIAL AND METHODS: From September 2012 to June 2021, 94 patients underwent hepatic resection for fat-containing HCC on pathology. Imaging features and categories were assessed using LIRADS v2018. Fat quantification was performed on chemical-shift MRI. Recurrence-free and overall survival were estimated. RESULTS: Twenty-one patients (26%) had nonalcoholic steatohepatitis (NASH). The median intra-tumoral fat fraction was 8%, with differences between SH-HCC and SH-NOS-HCC (9.5% vs. 5% p = 0.03). There was no difference in major LI-RADS features between all groups; most tumors were classified as LR-4/5. A mosaic architecture on MRI was rare (7%) in SH-HCC, a fat in mass on CT was more frequently depicted (48%) in SH-HCC. A combination of NASH with no mosaic architecture on MRI or NASH with fat in mass on CT yielded excellent specificity for diagnosing SH-HCC (97.6% and 97.7%, respectively). The median recurrence-free and overall survival were 58 and 87 months, with no difference between groups (p = 0.18 and p = 0.69). CONCLUSION: In patients with NASH, an SH-HCC may be suspected in L4/LR-5 observations with no mosaic architecture at MRI or with fat in mass on CT. Oncological outcomes appear similar between fat-containing HCC subtypes.

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.

Coronary inflammation based on pericoronary adipose tissue attenuation in type 2 diabetic mellitus: effect of diabetes management.

BACKGROUND: Coronary inflammation plays crucial role in type 2 diabetes mellitus (T2DM) induced cardiovascular complications. Both glucose-lowering drug interventions (GLDIS) and glycemic control (GC) status potentially correlate coronary inflammation, as indicated by changes in pericoronary adipose tissue (PCAT) attenuation, and thus influence cardiovascular risk. This study evaluated the impact of GLDIS and GC status on PCAT attenuation in T2DM patients. METHODS: This retrospective study collected clinical data and coronary computed tomography angiography (CCTA) images of 1,342 patients, including 547 T2DM patients and 795 non-T2DM patients in two tertiary hospitals. T2DM patients were subgroup based on two criteria: (1) GC status: well: HbA1c < 7%, moderate: 7 ≤ HbA1c ≤ 9%, and poor: HbA1c > 9%; (2) GLDIS and non-GLDIS. PCAT attenuations of the left anterior descending artery (LAD-PCAT), left circumflex artery (LCX-PCAT), and right coronary artery (RCA-PCAT) were measured. Propensity matching (PSM) was used to cross compare PCAT attenuation of non-T2DM and all subgroups of T2DM patients. Linear regressions were conducted to evaluate the impact of GC status and GLDIS on PCAT attenuation in T2DM patients. RESULTS: Significant differences were observed in RCA-PCAT and LCX-PCAT between poor GC-T2DM and non-T2DM patients (LCX: - 68.75 ± 7.59 HU vs. - 71.93 ± 7.25 HU, p = 0.008; RCA: - 74.37 ± 8.44 HU vs. - 77.2 ± 7.42 HU, p = 0.026). Higher PCAT attenuation was observed in LAD-PCAT, LCX-PCAT, and RCA-PCAT in non-GLDIS T2DM patients compared with GLDIS T2DM patients (LAD: - 78.11 ± 8.01 HU vs. - 75.04 ± 8.26 HU, p = 0.022; LCX: - 71.10 ± 8.13 HU vs. - 68.31 ± 7.90 HU, p = 0.037; RCA: - 78.17 ± 8.64 HU vs. - 73.35 ± 9.32 HU, p = 0.001). In the linear regression, other than sex and duration of diabetes, both metformin and acarbose were found to be significantly associated with lower LAD-PCAT (metformin: ß coefficient = - 2.476, p=0.021; acarbose: ß coefficient = - 1.841, p = 0.031). CONCLUSION: Inadequate diabetes management, including poor GC and lack of GLDIS, may be associated with increased coronary artery inflammation in T2DM patients, as indicated by PCAT attenuation on CCTA, leading to increased cardiovascular risk. This finding could help healthcare providers identify T2DM patients with increased cardiovascular risk, develop improved cardiovascular management programs, and reduce subsequent cardiovascular related mortality.

Gestational diabetes mellitus early prediction by maternal body fat index: A cohort study.

OBJECTIVES: To compare the performance of maternal body fat index (BFI) assessed during the first 20+6 weeks among 138 pregnant women in an ultrasound outpatient clinic as a predictor of gestational diabetes mellitus (GDM) later in pregnancy. METHOD: Maternal visceral and subcutaneous fat was measured with a convex ultrasound probe placed in two locations on the maternal abdominal surface: the first in the mid-sagittal epigastric region, visualising epigastric fat, and the second 2cm above the maternal umbilical scar, visualising periumbilical fat. Ultrasound callipers measured the distance from dermal edge to the linea alba and after from the linea alba to the anterior hepatic surface (epigastric fat). Periumbilical fat was measured from the dermal edge to the linea alba and after from the linea alba to the anterior aortic surface. The BFI formula was [visceral adipose tissue (mm)×subcutaneous adipose tissue (mm)]/maternal height (cm). RESULTS: The best thresholds for predicting GDM outcome for epigastric and periumbilical BFI were 1.2 and 4.8, respectively. Odds ratio, sensitivity and specificity were 5.88 (95% CI 1.86-18.6), 80.9%, 58.0% for the epigastric site and 6.31 (95% CI 1.73-22.94), 84.2%, 54.2% for the periumbilical site. Pre-pregnancy body mass index compatible with adult obesity shows inadequate predictive performance for GDM outcome. Only epigastric BFI above 1.2 maintained statistical significance for GDM in the logistic regression analysis, when compared to periumbilical BFI above 4.8. CONCLUSION: Epigastric BFI above 1.2 during the first half of pregnancy may help identify women at risk of developing GDM later in pregnancy.

Association between metformin treatment and coronary artery inflammation based on pericoronary adipose tissue attenuation in type 2 diabetes mellitus patients.

Cardiovascular disease (CVD) is the leading cause of mortality in type 2 diabetes mellitus (T2DM) patients. The role of metformin in reducing cardiovascular events is well-established, but its effect on coronary artery inflammation in T2DM patients is still unclear. In this study, we evaluated 547 T2DM patients who underwent coronary computed tomography angiography (CCTA) at Wuhan Central Hospital. Using propensity score matching, we compared the attenuation of pericoronary adipose tissue (PCAT), an imaging marker of coronary artery inflammation, between patients treated with and without metformin. Multiple linear regression models were used to analyze the influence of metformin on PCAT attenuation. The results of the propensity-matched analysis showed that patients on metformin therapy had significantly lower PCAT attenuation, indicating reduced coronary inflammation. Specifically, the PCAT attenuation in the left anterior descending artery (LAD) and right coronary artery (RCA) was lower in the metformin group compared to the non-metformin group. Metformin use was independently associated with decreased LAD-PCAT attenuation in the multivariate regression analysis. The association of metformin with PCAT attenuation differed significantly in populations analyzed in subgroups of patients with obesity and chronic kidney disease. In conclusion, our study shows a preliminary signal that metformin therapy may be associated with decreased coronary artery inflammation in T2DM patients, as indicated by PCAT attenuation on CCTA. And this correlation may vary depending on the patient population. This initial finding suggests that PCAT attenuation could be potentially used as an imaging biomarker to monitor the anti-inflammatory effects of medication.

Association of epicardial adipose tissue with early structural and functional cardiac changes in Type 2 diabetes.

BACKGROUND: Dysregulated epicardial adipose tissue (EAT) may contribute to the development of heart failure in Type 2 diabetes (T2D). This study aimed to evaluate the associations between EAT volume and composition with imaging markers of subclinical cardiac dysfunction in people with T2D and no prevalent cardiovascular disease. METHODS: Prospective case-control study enrolling participants with and without T2D and no known cardiovascular disease. Two hundred and fifteen people with T2D (median age 63 years, 60 % male) and thirty-nine non-diabetics (median age 59 years, 62 % male) were included. Using computed tomography (CT), total EAT volume and mean CT attenuation, as well as, low attenuation (Hounsfield unit range -190 to -90) EAT volume were quantified by a deep learning method and volumes indexed to body surface area. Associations with cardiac magnetic resonance-derived left ventricular (LV) volumes and strain indices were assessed using linear regression. RESULTS: T2D participants had higher LV mass/volume ratio (median 0.89 g/mL [0.82-0.99] vs 0.79 g/mL [0.75-0.89]) and lower global longitudinal strain (GLS; 16.1 ± 2.3 % vs 17.2 ± 2.2 %). Total indexed EAT volume correlated inversely with mean CT attenuation. Low attenuation indexed EAT volume was 2-fold higher (18.8 cm3/m2 vs. 9.4 cm3/m2, p < 0.001) in T2D and independently associated with LV mass/volume ratio (ß = 0.002, p = 0.01) and GLS (ß = -0.03, p = 0.03). CONCLUSIONS: Higher EAT volumes seen in T2D are associated with a lower mean CT attenuation. Low attenuation indexed EAT volume is independently, but only weakly, associated with markers of subclinical cardiac dysfunction in T2D.

BODY FAT COMPOSITION IN PATIENTS WITH INFLAMMATORY BOWEL DISEASES: A COMPARATIVE STUDY BETWEEN SKINFOLDS AND ULTRASONOGRAPHY.

BACKGROUND: Inflammatory bowel diseases (IBD) are associated with important changes in nutritional status. OBJECTIVE: The aim of the study was to compare body fat composition between two anthropometric methods: skinfolds and ultrasonography, in patients with IBD. METHODS: Single-center cross-sectional study with IBD patients in remission or active disease. For the agreement analysis between the body fat assessment methods, the Bland Altman method was used. RESULTS: A total of 101 patients with IBD were included, 75 with Crohn's disease and 26 with ulcerative colitis. Approximately 56% of the patients with Crohn's disease and 65.4% of those with ulcerative colitis had a body fat composition above normal levels, with no significant difference between the diseases (P=0.63). The Bland-Altman concordance analysis showed that the methods for assessing the percentage of fat by the adipometer and ultrasound were not in full agreement (P=0.001), despite both presented good correlation (CC 0.961; P=0.000). CONCLUSION: The analysis of body fat percentage in patients with IBD was different between the skinfolds and ultrasound. Both methods can be used to assess the of body fat percentage of patients with IBD. However, monitoring of body fat sequentially and longitudinally should always be performed using the same method throughout the disease course. Prospective longitudinal studies are warranted to precisely define the role of these two methods of measuring body composition in patients with IBD. BACKGROUND: • Inflammatory bowel diseases are associated with changes in nutritional status. BACKGROUND: • Skinfolds measurements and ultrasound are valid methods for assessing body composition and body fat. BACKGROUND: • These methods despite comparable are not identical and are useful in clinical nutritional practices in IBD.

Correlations between the peripheral coronary fat attenuation index based on computed tomography images, high-risk plaque and degree of coronary artery stenosis in patients with coronary atherosclerosis.

BACKGROUND: Coronary artery disease can be quantified by measuring the fat attenuation index (FAI). OBJECTIVE: To explore the correlations between FAI, high-risk plaque and the degree of coronary artery stenosis. METHODS: The clinical data of patients with coronary atherosclerosis who underwent a coronary computed tomography (CT) angiography examination between July 2020 and June 2023 were selected for retrospective analysis. These patients were classified into a high-risk plaque group and non-high-risk plaque group according to the presence of CT high-risk plaque. The diagnostic value of FAI and FAI combined with the degree of stenosis was evaluated for CT high-risk plaque. RESULTS: Differences in age, body mass index, smoking history, FAI and the degree of stenosis between the two groups were statistically significant (all P< 0.05). The results of a binary logistic regression analysis revealed that FAI (odds ratio (OR): 1.131, 95% confidence interval (CI): 1.101-1.173, P< 0.001) and the degree of stenosis (OR: 1.021, 95% CI: 1.012-1.107, P< 0.001) were risk factors for high-risk plaque. CONCLUSION: The FAI can be used to monitor the inflammation level of the coronary artery; the higher the FAI is, the higher the risk of plaque and degree of stenosis.

Cardiovascular Significance and Genetics of Epicardial and Pericardial Adiposity.

Importance: Epicardial and pericardial adipose tissue (EPAT) has been associated with cardiovascular diseases such as atrial fibrillation or flutter (AF) and coronary artery disease (CAD), but studies have been limited in sample size or drawn from selected populations. It has been suggested that the association between EPAT and cardiovascular disease could be mediated by local or paracrine effects. Objective: To evaluate the association of EPAT with prevalent and incident cardiovascular disease and to elucidate the genetic basis of EPAT in a large population cohort. Design, Setting, and Participants: A deep learning model was trained to quantify EPAT area from 4-chamber magnetic resonance images using semantic segmentation. Cross-sectional and prospective cardiovascular disease associations were evaluated, controlling for sex and age. Prospective associations were additionally controlled for abdominal visceral adipose tissue (VAT) volumes. A genome-wide association study was performed, and a polygenic score (PGS) for EPAT was examined in independent FinnGen cohort study participants. Data analyses were conducted from March 2022 to December 2023. Exposures: The primary exposures were magnetic resonance imaging-derived continuous measurements of epicardial and pericardial adipose tissue area and visceral adipose tissue volume. Main Outcomes and Measures: Prevalent and incident CAD, AF, heart failure (HF), stroke, and type 2 diabetes (T2D). Results: After exclusions, this study included 44 475 participants (mean [SD] age, 64.1 [7.7] years; 22 972 female [51.7%]) from the UK Biobank. Cross-sectional and prospective cardiovascular disease associations were evaluated for a mean (SD) of 3.2 (1.5) years of follow-up. Prospective associations were additionally controlled for abdominal VAT volumes for 38 527 participants. A PGS for EPAT was examined in 453 733 independent FinnGen cohort study participants. EPAT was positively associated with male sex (ß = +0.78 SD in EPAT; P < 3 × 10-324), age (Pearson r = 0.15; P = 9.3 × 10-229), body mass index (Pearson r = 0.47; P < 3 × 10-324), and VAT (Pearson r = 0.72; P < 3 × 10-324). EPAT was more elevated in prevalent HF (ß = +0.46 SD units) and T2D (ß = +0.56) than in CAD (ß = +0.23) or AF (ß = +0.18). EPAT was associated with incident HF (hazard ratio [HR], 1.29 per +1 SD in EPAT; 95% CI, 1.17-1.43), T2D (HR, 1.63; 95% CI, 1.51-1.76), and CAD (HR, 1.19; 95% CI, 1.11-1.28). However, the associations were no longer significant when controlling for VAT. Seven genetic loci were identified for EPAT, implicating transcriptional regulators of adipocyte morphology and brown adipogenesis (EBF1, EBF2, and CEBPA) and regulators of visceral adiposity (WARS2 and TRIB2). The EPAT PGS was associated with T2D (odds ratio [OR], 1.06; 95% CI, 1.05-1.07; P =3.6 × 10-44), HF (OR, 1.05; 95% CI, 1.04-1.06; P =4.8 × 10-15), CAD (OR, 1.04; 95% CI, 1.03-1.05; P =1.4 × 10-17), AF (OR, 1.04; 95% CI, 1.03-1.06; P =7.6 × 10-12), and stroke in FinnGen (OR, 1.02; 95% CI, 1.01-1.03; P =3.5 × 10-3) per 1 SD in PGS. Conclusions and Relevance: Results of this cohort study suggest that epicardial and pericardial adiposity was associated with incident cardiovascular diseases, but this may largely reflect a metabolically unhealthy adiposity phenotype similar to abdominal visceral adiposity.

Intra-pancreatic fat is associated with continuous glucose monitoring metrics.

AIM: To investigate the relationship of fat in the pancreas with time spent in different glycaemic ranges. METHODS: Abdominal magnetic resonance imaging at 3.0 Tesla was used to quantify fat in the pancreas as both continuous [i.e. intra-pancreatic fat deposition (IPFD)] and binary (i.e. fatty change of the pancreas vs. normal pancreas) variables. Dexcom G6 devices were used to collect continuous glucose monitoring data every 5 min over a continuous 7-day period. Time above range (TAR), time in range (TIR) and time below range were computed. Statistical models were built to adjust for age, sex, body composition, and other covariates in linear regression analysis and analysis of covariance. RESULTS: In total, 38 individuals were studied. IPFD was significantly associated with TAR (p = .036) and TIR (p = .042) after adjustment for covariates. For every 1% increase in IPFD, there was a 0.3 unit increase in TAR and a decrease in TIR. Individuals with fatty change of the pancreas, when compared with those with normal pancreas, had significantly higher TAR (p = .034) and lower TIR (p = .047) after adjustment for covariates. Neither IPFD (p = .805) nor fatty change of the pancreas (p = .555) was associated with time below range after adjustment for covariates. CONCLUSION: Increased fat in the pancreas is associated with excessive glycaemic variability. Fatty change of the pancreas may contribute to heightening the risk of cardiovascular diseases.

The Association of Body Composition Parameters Measured by Computed Tomography with Cancer Stage, Prognosis, and Survival in Patients with Renal Cell Carcinoma.

OBJECTIVE: This study aims to investigate the association of preoperative body composition parameters, measured by computed tomography in patients undergoing surgery for renal cell carcinoma, with its stage and to survey the relationship with postoperative hospitalization duration and survival. METHODS: Demographic data, pathology results, cancer stages, and hospitalization duration of 104 patients undergoing surgery at the urology clinic due to renal cell carcinoma between 2019 and 2023 were analyzed retrospectively. On computed tomography scans acquired during diagnosis, visceral adipose tissue, subcutaneous adipose tissue, total adipose tissue, and skeletal muscle area were measured. The ratios of body composition parameters were computed. RESULTS: When the correlation between survival time and body composition in deceased patients was analysed, a moderate but significant correlation was observed between skeletal muscle area value and total adipose tissue / skeletal muscle area ratio (r=0.630, p=0.001; r=0.598, p=0.002). A significant and strong correlation was observed between total adipose tissue value and survival (r=0.704, p<0.001). Subcutaneous adipose tissue / skeletal muscle area was found to be an independent risk factor associated with mortality, and a ratio of 0.98 or less increased the mortality risk approximately 16-fold. CONCLUSION: The relationship between body composition parameters measured by computed tomography, which can be easily evaluated pre-treatment, and mortality, postoperative recovery and length of hospital stay can be evaluated, giving clinicians an idea about the potential difficulties that patients may encounter during the treatment process. For this purpose, the subcutaneous adipose tissue / skeletal muscle area ratio is the most helpful parameter that can be used.

Effects of high-intensity training on fatty infiltration in paraspinal muscles in elderly males with osteosarcopenia - the randomized controlled FrOST study.

BACKGROUND: Osteosarcopenia is a common geriatric syndrome with an increasing prevalence with age, leading to secondary diseases and complex consequences such as falls and fractures, as well as higher mortality and frailty rates. There is a great need for prevention and treatment strategies. METHODS: In this analysis, we used magnetic resonance imaging (MRI) data from the randomised controlled FrOST trial, which enrolled community-dwelling osteosarcopenic men aged > 72 years randomly allocated to 16 months of twice-weekly high-intensity resistance training (HIRT) or a non-training control group. MR Dixon imaging was used to quantify the effects of HIRT on muscle fat infiltration in the paraspinal muscles, determined as changes in muscle tissue, fat faction and intermuscular adipose tissue (IMAT) in the erector spinae and psoas major muscles. Intention-to-treat analysis with multiple imputation was used to analyse the data set. RESULTS: After 16 months of intervention, 15 men from the HIRT and 16 men from the CG were included in the MRI analysis. In summary, no positive effects on the fat infiltration of the erector spinae and psoas major muscles were observed. CONCLUSIONS: The previously reported positive effects on lumbar spine bone mineral density (BMD) suggest that mechanotransduction induces tropic effects on bone, but that fat infiltration of the erector spinae and psoas major muscles are either irreversible or, for some unknown reason, resistant to exercise. Because of the beneficial effects on spinal BMD, HIRT is still recommended in osteosarcopenic older men, but further research is needed to confirm appropriate age-specific training exercises for the paraspinal muscles. The potential of different MRI sequences to quantify degenerative and metabolic changes in various muscle groups must be better characterized. TRIAL REGISTRATIONS: FrOST was approved by the University Ethics Committee of the Friedrich-Alexander University of Erlangen-Nürnberg (number 67_15b and 4464b) and the Federal Office for Radiation Projection (BfS, number Z 5-2,246,212 - 2017-002). Furthermore, it fully complies with the Declaration of Helsinki and is registered at ClinicalTrials.gov: NCT03453463 (05/03/2018). JAMA 310:2191-2194, 2013.

Differentiation of acute coronary syndrome with radiomics of pericoronary adipose tissue.

OBJECTIVE: To assess the potential values of radiomics signatures of pericoronary adipose tissue (PCAT) in identifying patients with acute coronary syndrome (ACS). METHODS: In total, 149, 227, and 244 patients were clinically diagnosed with ACS, chronic coronary syndrome (CCS), and without coronary artery disease (CAD), respectively, and were retrospectively analysed and randomly divided into training and testing cohorts at a 2:1 ratio. From the PCATs of the proximal left anterior descending branch, left circumflex branch, and right coronary artery (RCA), the pericoronary fat attenuation index (FAI) value and radiomics signatures were calculated, among which features closely related to ACS were screened out. The ACS differentiation models AC1, AC2, AC3, AN1, AN2, and AN3 were constructed based on the FAI value of RCA and the final screened out first-order and texture features, respectively. RESULTS: The FAI values were all higher in patients with ACS than in those with CCS and no CAD (all P < .05). For the identification of ACS and CCS, the area-under-the-curve (AUC) values of AC1, AC2, and AC3 were 0.92, 0.94, and 0.91 and 0.91, 0.86, and 0.88 in the training and testing cohorts, respectively. For the identification of ACS and no CAD, the AUC values of AN1, AN2, and AN3 were 0.95, 0.94, and 0.94 and 0.93, 0.87, and 0.89 in the training and testing cohorts, respectively. CONCLUSIONS: Identification models constructed based on the radiomics signatures of PCAT are expected to be an effective tool for identifying patients with ACS. ADVANCES IN KNOWLEDGE: The radiomics signatures of PCAT and FAI values are expected to differentiate between patients with ACS, CCS and those without CAD on imaging.