Wang Meng, Luo Yanji, Cai Huasong, Xu Ling, Huang Mengqi, Li Chang, Dong Zhi, Li Zi-Ping, Feng Shi-Ting
Department of Radiology, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, China.
Faculty of Medicine and Dentistry, University of Western Australia, Perth, Australia.
Quant Imaging Med Surg. 2019 Jun;9(6):1076-1086. doi: 10.21037/qims.2019.06.01.
The correlation between visceral adipose tissue volume (VATV), hepatic proton-density fat fraction (PDFF), and pancreatic PDFF has been previously studied to predict the presence of type 2 diabetes mellitus (T2DM). This study investigated VATV quantitation in patients with T2DM, prediabetes, and normal glucose tolerance (NGT) using MRI to assess the roles of VATV, hepatic, and pancreatic PDFF in predicting the presence of T2DM.
Forty-eight patients with a new clinical diagnosis of T2DM (n=15), prediabetes (n=17), or NGT (n=16) were included and underwent abdominal magnetic resonance imaging (MRI) scanning with the iterative decomposition of water and fat with echo asymmetry and least square estimation image quantification (IDEAL-IQ) sequencing. VATV was obtained at the level of the 2 and 3 lumbar vertebral bodies (VATV L2 and VATV L3) where the sum of VATV L2 and VATV L3 (total VATV) were computed, respectively. Also, pancreatic and hepatic fat content was quantified by measuring the PDFF. The receiver operating characteristic (ROC) curve and binary logistics regression model analysis were employed to evaluate their ability to predict the presence of T2DM.
The VATV L2, VATV L3, and total VATV values of the T2DM group were significantly higher than the prediabetes and NGT groups (P<0.05). There was no statistically significant difference between the values of VATV L2, VATV L3, and total VATV between the prediabetes and NGT groups (P>0.05). The ROC curve showed the areas under the curve for VATV L2, VATV L3, total VATV, hepatic PDFF, and pancreatic PDFF were 0.76, 0.80, 0.80, 0.79, and 0.75, respectively, in predicting the presence of T2DM (P<0.01). The ROC curves of VATV L2, VATV L3, total VATV, hepatic PDFF, and pancreatic PDFF failed to predict the presence of prediabetes and NGT (P>0.05). The binary logistics regression model analysis revealed that only VATV L3 was independently associated with the incidence of T2DM (P=0.01 and OR =1.01). The sensitivity, specificity, and total accuracy were 80.00%, 88.20%, and 84.40%, respectively.
Compared with hepatic PDFF, pancreatic PDFF, VAVT L2, and total VATV, VAVT L3 was the better predictor of T2DM.
先前已对内脏脂肪组织体积（VATV）、肝脏质子密度脂肪分数（PDFF）和胰腺PDFF之间的相关性进行研究，以预测2型糖尿病（T2DM）的存在。本研究使用磁共振成像（MRI）对T2DM、糖尿病前期和糖耐量正常（NGT）患者的VATV进行定量分析，以评估VATV、肝脏和胰腺PDFF在预测T2DM存在方面的作用。
纳入48例新诊断为T2DM（n = 15）、糖尿病前期（n = 17）或NGT（n = 16）的患者，并采用具有回波不对称和最小二乘估计图像定量的水脂迭代分解（IDEAL - IQ）序列进行腹部磁共振成像（MRI）扫描。在第2和第3腰椎椎体水平获取VATV（VATV L2和VATV L3），分别计算VATV L2和VATV L3之和（总VATV）。此外，通过测量PDFF对胰腺和肝脏脂肪含量进行定量。采用受试者工作特征（ROC）曲线和二元逻辑回归模型分析来评估它们预测T2DM存在的能力。
T2DM组的VATV L2、VATV L3和总VATV值显著高于糖尿病前期和NGT组（P < 0.05）。糖尿病前期和NGT组之间的VATV L2、VATV L3和总VATV值无统计学显著差异（P > 0.05）。ROC曲线显示，在预测T2DM存在方面，VATV L2、VATV L3、总VATV、肝脏PDFF和胰腺PDFF的曲线下面积分别为0.76、0.80、0.80、0.79和0.75（P < 0.01）。VATV L2、VATV L3、总VATV、肝脏PDFF和胰腺PDFF的ROC曲线未能预测糖尿病前期和NGT的存在（P > 0.05）。二元逻辑回归模型分析显示，只有VATV L3与T2DM的发病率独立相关（P = 0.01，OR = 1.01）。敏感性、特异性和总准确率分别为80.00%、88.20%和84.40%。
与肝脏PDFF、胰腺PDFF、VAVT L2和总VATV相比，VAVT L3是T2DM更好的预测指标。
