Department of Radiology, Uppsala University, Uppsala, Sweden.
J Magn Reson Imaging. 2010 Jul;32(1):204-10. doi: 10.1002/jmri.22193.
To develop and validate a method for rapid acquisition and automated processing of magnetic resonance (MR) images for analysis of abdominal adipose tissue distribution in children.
The study included 21 (10 girls, 11 boys) healthy 5-year-old children. Rapid water and fat MR imaging (6 sec) was performed using a 2-point-Dixon technique on a 1.5T MR scanner using an 8-channel cardiac coil. An automated image processing algorithm was developed for automated segmentation of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT), respectively. The results from the fully automated analysis were compared to those from a semiautomated analysis, performed by three operators, from the same images.
The automated analysis was seen to give results with strong correlation to the reference measurements (r >or= 0.997); however, the SAT volume was underestimated by 9.4 +/- 3.8%. The accuracy of the automated segmentation of VAT and SAT (TP: true positive, FP: false positive, mean +/- SD, %) was TP: 83.6 +/- 8.5, FP: 12.7 +/- 6.8; and TP: 89.9 +/- 3.6, FP: 0.7 +/- 0.3, respectively.
A method for rapid imaging and fully automated postprocessing of abdominal adipose tissue distribution is presented. The method allows robust and time-efficient measurement of adipose tissue distribution in young children.
开发并验证一种用于快速获取和自动处理磁共振(MR)图像的方法,以分析儿童腹部脂肪组织分布。
本研究纳入 21 名(10 名女孩,11 名男孩)健康 5 岁儿童。使用两点 Dixon 技术在 1.5T MR 扫描仪上进行快速水脂 MR 成像(6 秒),使用 8 通道心脏线圈。开发了一种自动图像处理算法,用于分别自动分割内脏脂肪组织(VAT)和皮下脂肪组织(SAT)。将全自动分析的结果与来自相同图像的三位操作员进行的半自动分析的结果进行比较。
全自动分析的结果与参考测量值具有很强的相关性(r≥0.997);然而,SAT 体积低估了 9.4±3.8%。VAT 和 SAT 的自动分割准确性(TP:真阳性,FP:假阳性,平均值±SD,%)分别为 TP:83.6±8.5,FP:12.7±6.8;和 TP:89.9±3.6,FP:0.7±0.3。
提出了一种用于快速成像和腹部脂肪组织分布全自动后处理的方法。该方法可用于对幼儿的脂肪组织分布进行稳健、高效的测量。