Comparison of pancreatic fat content measured by different methods employing MR mDixon sequence

Objective To compare the reliability of different methods for measuring fat content of pancreas by MR modified Dixon(mDixon) Sequence and accurately evaluate pancreatic fat in as simple a way as possible. Methods This is a retrospective study, 64 patients were included in this study who underwent abdominal MR scan that contained the mDixon sequence from June 2019 to May 2020(Included 7 patients with type 2 diabetes and 4 patients with impaired glucose tolerance (IGT), they were admitted to hospital through the obesity clinic set up by endocrine department, all of them were initially diagnosed and untreated). All of the 64 patients were scanned in 3.0T MR (Philips Ingenia II) due to their condition, 10–34 slice pancreas images were obtained, which were different from each other. Three different methods of measurement were employed by two observers using Philips Intellispace Portal software: (1) All images (whole-pancreas) measurement, the whole-pancreatic fat fraction (wPFF) was calculated by software. (2) Interval slices measurement, that is half-pancreatic slices fat fraction (hPFF) measured in the same way, fat fraction obtained by the interlayer assay was calculated. (3) As usual, the fat content of pancreatic head, body and tail fat was measured respectively, and in order to improve credibility, we also measured head、 body and tail in every layer, and its average value was taken. The elapsed time of the above different measurement methods was recorded. Intra-group correlation coefficient (ICC) was used to analyze the consistency of the measured data within and between observers. T-tests and Friedman tests were applied to compare the difference of measured values among groups. Results No matter in normal person or diabetic or IGT, hPFF has shown good stability (ICChPFF = 0.988), and there was no significant difference compared with wPFF. But the average fat percentage composition of head, body and tail were significantly different from wPFF and hPFF (P < 0.01). At the same time, compared with normal person, pancreatic fat content in IGT and diabetic patients showed progressive significance(P<0.05). Conclusion The distribution of pancreatic fat is not uniform, the method of measuring half pancreas by interlayer data collection can reflect the fat content of the entire pancreas, this suggests that measuring 50% of the pancreas is sufficient, this method effectively saves time and effort without affecting the results, which may have a better clinical application prospect.

Computed Tomography-Estimated Pancreatic Steatosis is a Risk Factor for Carotid Plaque in Type 2 Diabetes Mellitus Patients: A Cross-Sectional Study

Background Pancreatic steatosis correlates with the thickness of arterial intima. However, the correlation between pancreatic steatosis and carotid atherosclerosis plaque, which better predict the prognosis of cardiovascular disease, is unclear. We aimed to explore potential effects of pancreatic fat content measured by computer tomography (CT) on carotid plaque in patients with type 2 diabetes mellitus (T2DM).Methods Patients with T2DM who underwent CT scan of the upper abdomen and ultrasound of the carotid artery were consecutively enrolled. Based on ultrasound results, the patients were divided into non-plaque group and plaque group, and the latter was categorized into hypoechoic plaque subgroup and non-hypoechoic plaque subgroup. The CT attenuation of pancreas and spleen were measured. Pancreas-to-spleen attenuation ratio (P/S) and difference between pancreatic and splenic attenuation (P-S) were calculated. The cut-off values of P/S and P-S were obtained using receiver operating characteristic (ROC) curves. Logistic regression models were used to evaluate association of P/S or P-S with carotid plaque or hypoechoic plaque.Results A total of 337 patients with T2DM were enrolled, including 101 cases (30.0%) in the non-plaque group, 146 cases (43.3%) in the hypoechoic plaque subgroup, and 90 cases (26.7%) in the non-hypoechoic plaque subgroup. P/S and P-S in plaque group were lower than those in non-plaque group, with a cut-off value of P/S and P-S as 0.72 and -13.33, respectively. After adjusting for risk factors, P/S and P-S correlated with carotid plaque [for low P/S: OR (95% CI): 3.15 (1.47-6.73), P=0.0031; for low P-S: OR (95% CI): 2.84 (1.42-5.66), P=0.0031] as well as carotid hypoechoic plaque [for low P/S: OR (95% CI): 1.82 (1.07-3.08), P=0.0259; for low P-S: OR (95% CI): 1.82 (1.09-3.02), P=0.021].Conclusions T2DM patients with carotid plaque have higher pancreatic fat content than those without. Pancreatic steatosis correlates with carotid plaque and hypoechoic plaque in T2DM patients.

Metabolomic Characteristics of Fatty Pancreas

Objective Pancreatic steatosis is associated with impaired beta cell function in patients with prediabetes. The pathomechanisms underlying this association still remain to be elucidated. Recent data show that adipocytes are situated within the pancreatic parenchyma and therefore give raise to hypothesize that pancreatic fat together with known and unknown metabolites such as hepatokines affect insulin secretion. Applying a targeted metabolomic approach we investigated possible circulating markers of pancreatic fat in order to better understand its role in the pathophysiology of impaired beta cell function. Methods We included 361 Caucasians, at increased risk of type 2 diabetes, from the Tübingen Family Study. All participants underwent a frequently sampled oral glucose tolerance test to assess insulin secretion and a magnetic resonance imaging to quantify pancreatic fat content, total body fat and visceral fat. Among the 152 subjects with prediabetes (IFG and/or IGT), two groups each with 20 individuals, having the lowest and highest pancreatic fat content were selected. The groups were matched for sex, age, BMI, total fat content, visceral fat content, liver fat content and insulin sensitivity. Metabolites were analyzed using the AbsoluteIDQ® p400 HR Kit by Biocrates. Results Pancreatic fat content of all 152 subjects with prediabetes was negatively associated with insulin secretion represented by AUCC-peptide 0–120/AUCGlucose 0–120 (p=0.04; β=− 3.24). Furthermore, pancreatic fat content was positively associated with BMI, total body and visceral fat (all p<0.005). Levels of aminoacids, biogenic amines and monosaccharides were similar between the groups with high/low pancreatic fat content (p>0.90). Also, levels of polar lipids such as lysophosphatidylcholines, phosphatidylcholines, sphingomyelins and ceramides did not differ significantly between the groups (p>0.90). Investigating the levels of neutral lipids such as aclycarnitines, diglycerides, triglycerides and cholesteryl esters also revealed no differences between the groups (p>0.90). Conclusion The amount of pancreatic fat is not associated with the metabolomic pattern in individuals with prediabetes. This might be due to the relatively low pancreatic fat content compared to the total amount of fat stored in other depots. The impact of pancreatic steatosis on insulin secretion might be mediated by paracrine effects which cannot be detected in the circulation.

Changes in Pancreatic Fat Content Following Diet-Induced Weight Loss

Background: Obesity can lead to ectopic pancreatic fat accumulation and increase the risk for type 2 diabetes. Smaller intervention trials have shown a decrease in pancreatic fat content (PFC) with weight loss, and we intended to investigate the effects of weight loss on PFC in a larger trial. Methods: Data from the HELENA-Trial, a randomized controlled trial (RCT) among 137 non-diabetic obese adults were used. The study cohort was classified into 4 quartiles based on weight change between baseline and 12 weeks post-intervention. Changes in PFC (baseline, 12 weeks and 50 weeks post-intervention) upon weight loss were analyzed by linear mixed models. Spearman’s coefficients were used to obtain correlations between anthropometric parameters, blood biochemical markers, and PFC. Results: At baseline, PFC only showed a significant correlation with visceral adipose tissue (VAT) (r = 0.41). Relative changes in PFC were significantly (p = 0.01) greater in Q4 (−30.8 ± 5.7%) than in Q1 (1.3 ± 6.7%). These differences remained similar after one year. However, when adjusting the statistical analyses for changes in VAT, the differences in PFC between Q1 and Q4 were no longer statistically significant. Conclusion: Weight loss is associated with a decrease in PFC. However, the reduction of PFC is not independent from reductions in VAT. Unlike VAT, PFC was not associated with metabolic biomarkers.