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棕色和白色脂肪组织的磁共振特性。

MR properties of brown and white adipose tissues.

机构信息

Department of Radiology, University of California, San Diego, San Diego, California, USA.

出版信息

J Magn Reson Imaging. 2011 Aug;34(2):468-73. doi: 10.1002/jmri.22623.

Abstract

PURPOSE

To explore the MR signatures of brown adipose tissue (BAT) compared with white adipose tissue (WAT) using single-voxel MR spectroscopy.

MATERIALS AND METHODS

(1) H MR STEAM spectra were acquired from a 3 Tesla clinical whole body scanner from seven excised murine adipose tissue samples of BAT (n=4) and WAT (n=3). Spectra were acquired at multiple echo times (TEs) and inversion times (TIs) to measure the T1, T2, and T2-corrected peak areas. A theoretical triglyceride model characterized the fat in terms of number of double bonds (ndb) and number of methylene-interrupted double bonds (nmidb).

RESULTS

Negligible differences between WAT and BAT were seen in the T1 and T2 of fat and the T2 of water. However, the water fraction in BAT was higher (48.5%) compared with WAT (7.1%) and the T1 of water was lower in BAT (618 ms) compared with WAT (1053 ms). The fat spectrum also differed, indicating lower levels of unsaturated triglycerides in BAT (ndb=2.7, nmidb=0.7) compared with WAT (ndb=3.3, nmidb=1.0).

CONCLUSION

We have demonstrated that there are several key MR-based signatures of BAT and WAT that may allow differentiation on MR imaging.

摘要

目的

使用单体素磁共振波谱法探讨棕色脂肪组织(BAT)与白色脂肪组织(WAT)的磁共振特征。

材料与方法

(1)在一台 3 特斯拉临床全身扫描仪上从 7 个切除的 BAT(n=4)和 WAT(n=3)鼠脂肪组织样本中获取 H 磁共振 STEAM 光谱。在多个回波时间(TE)和反转时间(TI)下采集光谱,以测量 T1、T2 和 T2 校正后的峰面积。一个理论甘油三酯模型根据双键数量(ndb)和中双键数量(nmidb)对脂肪进行了特征描述。

结果

WAT 和 BAT 的脂肪 T1 和 T2 以及水 T2 之间几乎没有差异。然而,BAT 中的水分数较高(48.5%),而 WAT 中较低(7.1%),BAT 中的水 T1 也较低(618ms),而 WAT 中较高(1053ms)。脂肪光谱也存在差异,表明 BAT 中的不饱和甘油三酯水平较低(ndb=2.7,nmidb=0.7),而 WAT 中较高(ndb=3.3,nmidb=1.0)。

结论

我们已经证明,BAT 和 WAT 存在一些关键的基于磁共振的特征,这些特征可能可以在磁共振成像上进行区分。

相似文献

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MR properties of brown and white adipose tissues.棕色和白色脂肪组织的磁共振特性。
J Magn Reson Imaging. 2011 Aug;34(2):468-73. doi: 10.1002/jmri.22623.

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