Automated Assessment of Whole-Body Adipose Tissue Depots From Continuously Moving Bed MRI: A Feasibility Study
Automated Assessment of Whole-Body Adipose Tissue Depots From Continuously Moving Bed MRI: A Feasibility Study
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DOI：
10.1002/jmri.21820
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发表时间：
2009-07-01
影响因子：
4.4
通讯作者：
Boernert, Peter
中科院分区：
文献类型：
--
作者：
Kullberg, Joel;Johansson, Lars;Boernert, Peter
目的：提出一种从全身MRI数据集中分割内脏、皮下和脂肪组织库（VAT， SAT， TAT）的自动算法，并研究VAT分割的准确性和所有库评估的可重复性。材料和方法：使用1.5 Testa临床MRI扫描仪和三维（3D）多梯度回波序列（分辨率：2.1 x 2.1 x 8 mm(3)，采集时间：5分钟15秒）对24名志愿者进行重复测量。重建脂肪和水的图像。并进行全自动分割。增值税参考的手动分割是由经验丰富的操作员执行的。结果：增值税自动评定与人工评定之间存在强相关（R = 0.999）。自动化结果低估了增值税4.7 +/- 4.4%。对于真阳性和假阳性分数，准确率分别为88±4.5%和7.6±5.7%。重复测量前的变异系数分别为：2.32% +/- 2.61%、2.25% +/- 2.10%和1.01% +/- 0.74%。结论：自动增值与人工增值结果相关性强。对所有仓库的评估具有高度的可重复性。所提出的获取和后处理技术可能在肥胖相关研究中有用。
Purpose: 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.Materials and Methods: Repeated measurements were performed on 24 volunteer subjects using a 1.5 Testa 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.Results: 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 front the repeated measurements were: 2.32% +/- 2.61%, 2.25% +/- 2.10%, and 1.01% +/- 0.74% for VAT, SAT, and TAT, respectively.Conclusion: 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.