| Project/Area Number |
26461809
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Research Field |
Radiation science
|
|---|
| Research Institution | Kurume University |
|---|
Principal Investigator |
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
藤本 公則 久留米大学, 医学部, 教授 (00199366)
安陪 等思 久留米大学, 医学部, 教授 (90167940)
|
|---|
| Co-Investigator(Renkei-kenkyūsha) |
KAWAGUCHI Takumi 久留米大学, 医学部, 講師 (00320177)
|
|---|
| Project Period (FY) |
2014-04-01 – 2018-03-31
|
| Project Status |
Completed (Fiscal Year 2017)
|
| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2016: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2015: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2014: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
|
|---|
| Keywords | 異所性脂肪 / 非アルコール性脂肪性肝疾患 / MRI / PDFF / 糖尿病 / 非アルコール性脂肪肝炎 / 異所性脂肪組織 / IDEAL-IQ / Fat fraction / 非アルコール性脂肪肝疾患 / 画像診断 |
|---|
| Outline of Final Research Achievements |
The aim of this study was to investigate the association between the ectopic fat tissue of skeletal muscle, liver, and pancreas in non-alcoholic fatty liver disease (NAFLD) patients by proton density fat fraction (PDFF) using 3T MRI. There were statistically significant differences in PDFF measurements of skeletal muscle, liver, and pancreas among three groups. With the PDFF measurements of skeletal muscle, there was statistically significant difference between NAFLD with DM group and NAFLD without DM group. For predicting NAFLD with DM, ROC analysis revealed that muscle-FF was the most useful parameter (AUC=0.83) and at a cutoff-value of 4 and over, sensitivity, specificity, PPV and NPV were 82%, 75%, 70%, and 86%, respectively. There was a close association between the ectopic fat tissue of skeletal muscle that was quantified by 3T MRI-PDFF and co-morbid diabetes mellitus of NAFLD. Evaluation of ectopic fat tissue by 3T MRI-PDFF can be used to predict the advance of fat metabolism.
|
