This study was undertaken to determine the accuracy of pancreatic MR imaging by proton density fat fraction measurements with the iterative decomposition of water and fat with the echo asymmetry and least-squares estimation quantitation (IDEAL-IQ) sequences, and to explore changes of pancreatic fat content in a diabetic animal model. We found that estimation of pancreatic fat content by pulse sequence imaging is accurate and reproducible across readers. Further, greater pancreatic fat infiltration was observed in diabetic animals and it is related to the level of fasting blood glucose, which supports its use as a biomarker for diabetes risk.
Methods
In this prospective study, 13 Bama Mini-pigs ( closed colony animals, 7 females, 6 males; median age, 2 weeks) were randomly assigned to diabetes (n=7) or control (n=6) groups. Starting in the fifth month, Pigs in the diabetic group received high fat/high sugar feed, combined with multiple low dose streptozotocin injections. At the end of fiteenth month, biochemical changes were evaluated by our clinical lab, all pigs underwent axial MR imaging with the IDEAL-IQ sequence to measurePFF, PFC of fresh pancreatic parenchyma was measured by the Soxhlet extraction method, pancreatic fat distribution was observed by histopathology, then compared them with Mann-Whitney U-test between the diabetes and control group. Correlations of PFF and PFC, fasting blood glucose (GLU) and serum insulin (INS) were calculated by Spearman correlation coefficient. Single-measure intraclass correlation coefficient (ICC) was used to assess interreader agreement.Conclusions
Pancreatic fat infiltration is ever-increasing during the progression of type T2DM pigs. And MRI with the IDEAL-IQ sequence can be used to monitor pancreatic fat fractions in diabetic pigs as a non-invasive method.1. Hollingsworth KG, Al-Mrabeh A, Steven S. Pancreatic triacylglycerol distribution in type 2 diabetes. Diabetologia 58 (11) (2015) 2676-2678.
2. Zhou J, Li ML, Zhang DD, et al. The correlation between pancreatic steatosis and metabolic syndrome in a Chinese population. Pancreatology 16 (4) (2016) 578-583.
3. Gerst F, Wagner R, Kaiser G, et al. Metabolic crosstalk between fatty pancreas and fatty liver: effects on local inflammation and insulin secretion. Diabetologia 60 (11) (2017) 2240-2251.
4. Kusmartseva I, Beery M, Philips T, et al. Hospital time prior to death and pancreas histopathology: implications for future studies. Diabetologia 68 (8) (2017) 308-312.
5.Solimena M, Schulte AM, Marselli L, et al. Systems biology of the IMIDIA biobank from organ donors and pancreatectomised patients defines a novel transcriptomic signature of islets from individuals with type 2 diabetes. Diabetologia (Suppl 4) (2017) 1-17.
6. Kühn JP, Berthold F, Mayerle J, et al. Pancreatic Steatosis Demonstrated at MR Imaging in the General Population: Clinical Relevance. Radiology 276 (1) (2015) 129-136.
7. Heber SD, Hetterich H, Lorbeer R, et al. Pancreatic fat content by magnetic resonance imaging in subjects with prediabetes, diabetes, and controls from a general population without cardiovascular disease. PLoS One 12 (5) (2017) e0177154.