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Quantification of Organ Fat Deposits in Patients with Type 2 Diabetes Mellitus by Magnetic Resonance Imaging / 中国医学影像学杂志
Chinese Journal of Medical Imaging ; (12): 509-512, 2017.
Article in Chinese | WPRIM | ID: wpr-615288
ABSTRACT
Purpose Lipotoxicity plays an important role in the progression of diabetes and its complications,and the gold standards for organs' lipid quantification are biopsy or histochemical staining,which are invasive and have their own limitations.Thus,our research was to identify the difference in organ lipid deposition between type 2 diabetic patients and healthy volunteers by using noninvasive three-point T2* corrected Dixon imaging.Materials and Methods Sixty-five type 2 diabetic patients and 34 healthy volunteers were included in this study.All participants underwent three-echo Dixon with 3.0T MR imager.Dixon imaging parameters [hepatic fat fraction (HFF),splenic fat fraction (SFF),pancreatic fat fraction (PFF)] were collected.All of the MRI parameters were compared.The relationship between HFF,SFF,PFF and BMI,age were analyzed.Results The hepatic and splenic lipid percentage in diabetic group [HFF=(5.4±4.3)%;SFF=(3.7± 1.4)%] was significantly higher than healthy volunteers group [HFF=(2.9± 1.3)%;SFF=(3.0± 0.9)%;P<0.05,respectively].However,there was no significant difference in pancreatic fat fraction between diabetic and healthy groups (P>0.05).There were positive correlations between HFF,SFF,PFF and BMI (r=0.379,0.305 and 0.306,P<0.05).Moreover,only the positive correlation between pancreatic fat fraction and age were observed (r=0.261,P<0.05).Conclusion The three-point T2* corrected Dixon revealed the abnormalities of hepar and spleen lipid accumulation in diabetic patients.Thus,the three-point Dixon imaging may potentially aid in evaluating the lipid deposition of abdominal organs.

Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Medical Imaging Year: 2017 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Medical Imaging Year: 2017 Type: Article