Kullberg Joel, Johansson Lars, Ahlström Håkan, Courivaud Frederic, Koken Peter, Eggers Holger, Börnert Peter
Department of Radiology, Uppsala University, Uppsala, Sweden.
J Magn Reson Imaging. 2009 Jul;30(1):185-93. doi: 10.1002/jmri.21820.
To present an automated algorithm for segmentation of visceral, subcutaneous, and total volumes of adipose tissue depots (VAT, SAT, TAT) from whole-body MRI data sets and to investigate the VAT segmentation accuracy and the reproducibility of all depot assessments.
Repeated measurements were performed on 24 volunteer subjects using a 1.5 Tesla clinical MRI scanner and a three-dimensional (3D) multi-gradient-echo sequence (resolution: 2.1 x 2.1 x 8 mm(3), acquisition time: 5 min 15 s). Fat and water images were reconstructed, and fully automated segmentation was performed. Manual segmentation of the VAT reference was performed by an experienced operator.
Strong correlation (R = 0.999) was found between the automated and manual VAT assessments. The automated results underestimated VAT with 4.7 +/- 4.4%. The accuracy was 88 +/- 4.5% and 7.6 +/- 5.7% for true positive and false positive fractions, respectively. Coefficients of variation from the repeated measurements were: 2.32 % +/- 2.61%, 2.25% +/- 2.10%, and 1.01% +/- 0.74% for VAT, SAT, and TAT, respectively.
Automated and manual VAT results correlated strongly. The assessments of all depots were highly reproducible. The acquisition and postprocessing techniques presented are likely useful in obesity related studies.
提出一种自动算法，用于从全身MRI数据集中分割内脏、皮下及脂肪组织库的总体积（内脏脂肪组织、皮下脂肪组织、总脂肪组织），并研究内脏脂肪组织分割的准确性以及所有脂肪库评估的可重复性。
使用1.5特斯拉临床MRI扫描仪和三维（3D）多梯度回波序列（分辨率：2.1×2.1×8 mm³，采集时间：5分15秒）对24名志愿者进行重复测量。重建脂肪和水图像，并进行全自动分割。由经验丰富的操作人员对手动分割的内脏脂肪组织参考值进行操作。
自动和手动评估内脏脂肪组织之间存在强相关性（R = 0.999）。自动评估结果低估内脏脂肪组织4.7±4.4%。真阳性率和假阳性率的准确率分别为88±4.5%和7.6±5.7%。重复测量的变异系数分别为：内脏脂肪组织2.32%±2.61%、皮下脂肪组织2.25%±2.10%、总脂肪组织1.01%±0.74%。
自动和手动评估内脏脂肪组织的结果相关性很强。所有脂肪库的评估具有高度可重复性。所介绍的采集和后处理技术可能对肥胖相关研究有用。
