Links between ectopic and abdominal fat and systemic inflammation: New insights from the SHIP-Trend study

Assessment of body composition and prediction of infectious pancreatic necrosis via non-contrast CT radiomics and deep learning

Aim

The current study aims to delineate subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), the sacrospinalis muscle, and all abdominal musculature at the L3-L5 vertebral level from non-contrast computed tomography (CT) imagery using deep learning algorithms. Subsequently, radiomic features are collected from these segmented images and subjected to medical interpretation.

Materials and methods

This retrospective analysis includes a cohort of 315 patients diagnosed with acute necrotizing pancreatitis (ANP) who had undergone comprehensive whole-abdomen CT scans. The no new net (nnU-Net) architecture was adopted for the imagery segmentation, while Python scripts were employed to derive radiomic features from the segmented non-contrast CT images. In light of the intrinsic medical relevance of specific features, two categories were selected for analysis: first-order statistics and morphological characteristics. A correlation analysis was conducted, and statistically significant features were subjected to medical scrutiny.

Results

With respect to VAT, skewness (p = 0.004) and uniformity (p = 0.036) emerged as statistically significant; for SAT, significant features included skewness (p = 0.023), maximum two-dimensional (2D) diameter slice (p = 0.020), and maximum three-dimensional (3D) diameter (p = 0.044); for the abdominal muscles, statistically significant metrics were the interquartile range (IQR; p = 0.023), mean absolute deviation (p = 0.039), robust mean absolute deviation (p = 0.015), elongation (p = 0.025), sphericity (p = 0.010), and surface volume ratio (p = 0.014); and for the sacrospinalis muscle, significant indices comprised the IQR (p = 0.018), mean absolute deviation (p = 0.049), robust mean absolute deviation (p = 0.025), skewness (p = 0.008), maximum 2D diameter slice (p = 0.008), maximum 3D diameter (p = 0.005), sphericity (p = 0.011), and surface volume ratio (p = 0.005).

Conclusion

Diminished localized deposition of VAT and SAT, homogeneity in the VAT and SAT density, augmented SAT volume, and a dispersed and heterogeneous distribution of abdominal muscle density are identified as risk factors for infectious pancreatic necrosis (IPN).

Pancreatic fat infiltration is associated with risk of vertebral fracture in older patients with type 2 diabetes: A longitudinal multicenter study

AIMS

Patients with type 2diabetesmellitus (T2DM) have high fracture risk. This study explored the associations between pancreatic computed tomography (CT) attenuation, a marker of pancreatic fat, and risk of vertebral fracture in T2DM patients.

METHODS

A total of 1486 T2DM patients who aged 50 years and older and without preexisting vertebral fractures during 2019-2023 at our institutions were followed up untilJanuary 2024. CT attenuation of the pancreas, bone and spleen were measured. Pancreatic attenuation/spleen attenuation ratio (P/S) was calculated. Vertebral fractures were evaluated on spine CT images according to Genant's semiquantitative scoring system.

RESULTS

A total of 135 cases of vertebral fracture were identified during 26 months of follow-up and 270 patients without vertebral fracture were matched. Pancreatic CT attenuation and the P/S ratio were negatively associated with the risk of vertebral fracture (adjusted hazard ratio (aHR) = 0.97, 95 %confidence interval (CI): 0.96-0.99; aHR = 0.26, 95 %CI: 0.12-0.58). Addition of pancreatic attenuation or P/S ratio improved the performance of bone attenuation-based model (area under the curve = 0.72-0.763 vs 0.63-0.728).

CONCLUSION

Pancreatic fat infiltration is an associated factor for vertebral fracture in T2DM patients. Addition of pancreatic fat infiltration improved the predictive performance of the bone-based model.

Association of Asymmetric and Symmetric Dimethylarginine with Inflammation in the Population-Based Study of Health in Pomerania

The amino acids arginine (Arg), asymmetric (ADMA) and symmetric dimethylarginine (SDMA) are related to nitric oxide (NO) metabolism and potential markers of two different disease entities: cardiovascular disease such as atherosclerosis and systemic inflammation in critically ill patients with sepsis. Although very different in their pathophysiological genesis, both entities involve the functional integrity of blood vessels. In this context, large population-based data associating NO metabolites with proinflammatory markers, e.g., white blood cell count (WBC), high-sensitivity C-reactive protein (hsCRP), and fibrinogen, or cytokines are sparse. We investigated the association of Arg, ADMA and SDMA with WBC, hsCRP, and fibrinogen in 3556 participants of the Study of Health in Pomerania (SHIP)-TREND study. Furthermore, in a subcohort of 456 subjects, 31 inflammatory markers and cytokines were analyzed. We identified Arg and SDMA to be positively associated with hsCRP (β coefficient 0.010, standard error (SE) 0.002 and 0.298, 0.137, respectively) as well as fibrinogen (β 5.23 × 10-3, SE 4.75 × 10-4 and 0.083, 0.031, respectively). ADMA was not associated with WBC, hsCRP, or fibrinogen. Furthermore, in the subcohort, Arg was inversely related to a proliferation-inducing ligand (APRIL). SDMA was positively associated with osteocalcin, tumor necrosis factor receptor 1 and 2, and soluble cluster of differentiation 30. Our findings provide new insights into the involvement of Arg, ADMA, and SDMA in subclinical inflammation in the general population.

Fatty change of the pancreas: the Pandora's box of pancreatology

Prevention of common diseases of the pancreas or interception of their progression is as attractive in theory as it is elusive in practice. The fundamental challenge has been an incomplete understanding of targets coupled with a multitude of intertwined factors that are associated with the development of pancreatic diseases. Evidence over the past decade has shown unique morphological features, distinctive biomarkers, and complex relationships of intrapancreatic fat deposition. Fatty change of the pancreas has also been shown to affect at least 16% of the global population. This knowledge has solidified the pivotal role of fatty change of the pancreas in acute pancreatitis, chronic pancreatitis, pancreatic cancer, and diabetes. The pancreatic diseases originating from intrapancreatic fat (PANDORA) hypothesis advanced in this Personal View cuts across traditional disciplinary boundaries with a view to tackling these diseases. New holistic understanding of pancreatic diseases is well positioned to propel pancreatology through lasting research breakthroughs and clinical advances.

Association between body fat distribution and kidney stones: Evidence from a US population

Objectives

We aimed to evaluate the relationship between the proportion of Android to Gynoid ratio and the incidence of kidney stones among US adults.

Methods

Participants aged 20-59 years from the 2011-2018 National Health and Nutrition Examination Survey (NHANES) database were selected to assess the association between Android to Gynoid ratio and kidney stone prevalence using logistic regression analysis, subgroup analysis and calculation of dose-response curves.

Results

This study ultimately included 10858 participants, of whom 859 self-reported a history of kidney stones. And after adjusting for all confounders, an increased Android to Gynoid ratio was associated with an increased prevalence of kidney stones (OR=2.75, 95% CI:1.62-4.88). And subgroup analysis showed an increased prevalence of kidney stones in women (OR=3.55, 95% CI: 1.54-8.22), non-diabetic (OR=2.59, 95% CI: 1.45-4.60), 60 > age ≥ 40 years (OR=3.51, 95% CI: 1.83-6.71), Mexican-American (OR=4.35, 95% CI: 1.40- 13.53) and white (OR=3.86, 95% CI: 1.82-8.18) groups, there was a significant positive association between A/G ratio and kidney stones. In contrast, in the hypertensive subgroup, the A/G ratio was associated with kidney stones in all groups.

Conclusions

Higher Android to Gynoid ratio is associated with a high prevalence of kidney stone disease.