利用无创MRI定量内脏腹部脂肪组织体积预测2型糖尿病。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2019-05-30 DOI:10.21037/QIMS.2019.06.01
Meng Wang, Yanji Luo, H. Cai, Ling Xu, Mengqi Huang, Chang Li, Z. Dong, Ziping Li, S. Feng
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VATV was obtained at the level of the 2nd and 3rd 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.\n\n\nResults\nThe 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). 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引用次数: 10

摘要

背景:内脏脂肪组织体积(VATV)、肝脏质子密度脂肪分数(PDFF)和胰腺PDFF之间的相关性已经被研究用于预测2型糖尿病(T2DM)的存在。本研究利用MRI对T2DM、糖尿病前期和正常糖耐量(NGT)患者的VATV定量进行了研究,以评估VATV、肝脏和胰腺PDFF在预测T2DM存在中的作用。方法48例临床新诊断为T2DM (n=15)、糖尿病前期(n=17)或NGT (n=16)的患者行腹部磁共振成像(MRI)扫描,采用回声不对称迭代分解和最小二乘估计图像量化(idel - iq)测序。在第2和第3腰椎椎体(VATV L2和VATV L3)水平获得VATV,分别计算VATV L2和VATV L3(总VATV)的总和。同时,通过测量PDFF来量化胰腺和肝脏脂肪含量。采用受试者工作特征(ROC)曲线和二元logistic回归模型分析评估其预测T2DM存在的能力。结果T2DM组VATV L2、VATV L3及总VATV值均显著高于糖尿病前期和NGT组(P0.05)。ROC曲线显示,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,预测T2DM的存在(P0.05)。二元logistic回归模型分析显示,只有VATV L3与T2DM发病率独立相关(P=0.01, OR =1.01)。灵敏度为80.00%,特异度为88.20%,总准确率为84.40%。结论与肝脏PDFF、胰腺PDFF、VAVT L2和总VATV相比,VAVT L3能更好地预测T2DM。
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Prediction of type 2 diabetes mellitus using noninvasive MRI quantitation of visceral abdominal adiposity tissue volume.
Background 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. Methods 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 2nd and 3rd 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. Results 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. Conclusions Compared with hepatic PDFF, pancreatic PDFF, VAVT L2, and total VATV, VAVT L3 was the better predictor of T2DM.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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