PMID- 31367561
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20220409
IS  - 2223-4292 (Print)
IS  - 2223-4306 (Electronic)
IS  - 2223-4306 (Linking)
VI  - 9
IP  - 6
DP  - 2019 Jun
TI  - Prediction of type 2 diabetes mellitus using noninvasive MRI quantitation of 
      visceral abdominal adiposity tissue volume.
PG  - 1076-1086
LID - 10.21037/qims.2019.06.01 [doi]
AB  - 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 2(nd) and 3(rd) 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.
FAU - Wang, Meng
AU  - Wang M
AD  - Department of Radiology, the First Affiliated Hospital, Sun Yat-Sen University, 
      Guangzhou 510080, China.
FAU - Luo, Yanji
AU  - Luo Y
AD  - Department of Radiology, the First Affiliated Hospital, Sun Yat-Sen University, 
      Guangzhou 510080, China.
FAU - Cai, Huasong
AU  - Cai H
AD  - Department of Radiology, the First Affiliated Hospital, Sun Yat-Sen University, 
      Guangzhou 510080, China.
FAU - Xu, Ling
AU  - Xu L
AD  - Faculty of Medicine and Dentistry, University of Western Australia, Perth, 
      Australia.
FAU - Huang, Mengqi
AU  - Huang M
AD  - Department of Radiology, the First Affiliated Hospital, Sun Yat-Sen University, 
      Guangzhou 510080, China.
FAU - Li, Chang
AU  - Li C
AD  - Department of Radiology, the First Affiliated Hospital, Sun Yat-Sen University, 
      Guangzhou 510080, China.
FAU - Dong, Zhi
AU  - Dong Z
AD  - Department of Radiology, the First Affiliated Hospital, Sun Yat-Sen University, 
      Guangzhou 510080, China.
FAU - Li, Zi-Ping
AU  - Li ZP
AD  - Department of Radiology, the First Affiliated Hospital, Sun Yat-Sen University, 
      Guangzhou 510080, China.
FAU - Feng, Shi-Ting
AU  - Feng ST
AD  - Department of Radiology, the First Affiliated Hospital, Sun Yat-Sen University, 
      Guangzhou 510080, China.
LA  - eng
PT  - Journal Article
PL  - China
TA  - Quant Imaging Med Surg
JT  - Quantitative imaging in medicine and surgery
JID - 101577942
PMC - PMC6629551
OTO - NOTNLM
OT  - Type 2 diabetes mellitus (T2DM)
OT  - magnetic resonance imaging (MRI)
OT  - quantitation
OT  - visceral adipose tissue volume (VATV)
COIS- Conflicts of interest: The authors have no conflicts of interest to declare.
EDAT- 2019/08/02 06:00
MHDA- 2019/08/02 06:01
PMCR- 2019/06/01
CRDT- 2019/08/02 06:00
PHST- 2019/08/02 06:00 [entrez]
PHST- 2019/08/02 06:00 [pubmed]
PHST- 2019/08/02 06:01 [medline]
PHST- 2019/06/01 00:00 [pmc-release]
AID - qims-09-06-1076 [pii]
AID - 10.21037/qims.2019.06.01 [doi]
PST - ppublish
SO  - Quant Imaging Med Surg. 2019 Jun;9(6):1076-1086. doi: 10.21037/qims.2019.06.01.