Department of Nuclear Medicine, Henri Becquerel Cancer Center, Rouen, France.
LITIS-QuantIF-EA4108, University of Rouen, Rouen, France.
J Digit Imaging. 2019 Apr;32(2):241-250. doi: 10.1007/s10278-019-00178-3.
Anthropometric parameters like muscle body mass (MBM), fat body mass (FBM), lean body mass (LBM), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) are used in oncology. Our aim was to develop and evaluate the software Anthropometer3D measuring these anthropometric parameters on the CT of PET/CT. This software performs a multi-atlas segmentation of CT of PET/CT with extrapolation coefficients for the body parts beyond the usual acquisition range (from the ischia to the eyes). The multi-atlas database is composed of 30 truncated CTs manually segmented to isolate three types of voxels (muscle, fat, and visceral fat). To evaluate Anthropomer3D, a leave-one-out cross-validation was performed to measure MBM, FBM, LBM, VAT, and SAT. The reference standard was based on the manual segmentation of the corresponding whole-body CT. A manual segmentation of one CT slice at level L3 was also used. Correlations were analyzed using Dice coefficient, intra-class coefficient correlation (ICC), and Bland-Altman plot. The population was heterogeneous (sex ratio 1:1; mean age 57 years old [min 23; max 74]; mean BMI 27 kg/m [min 18; max 40]). Dice coefficients between reference standard and Anthropometer3D were excellent (mean+/-SD): muscle 0.95 ± 0.02, fat 1.00 ± 0.01, and visceral fat 0.97 ± 0.02. The ICC was almost perfect (minimal value of 95% CI of 0.97). All Bland-Altman plot values (mean difference, 95% CI and slopes) were better for Anthropometer3D compared to L3 level segmentation. Anthropometer3D allows multiple anthropometric measurements based on an automatic multi-slice segmentation. It is more precise than estimates using L3 level segmentation.
在肿瘤学中使用人体测量参数,如肌肉量(MBM)、脂肪量(FBM)、去脂体重(LBM)、内脏脂肪组织(VAT)和皮下脂肪组织(SAT)。我们的目的是开发和评估软件 Anthropometer3D,以便在 PET/CT 的 CT 上测量这些人体测量参数。该软件对超出常规采集范围(从坐骨到眼睛)的身体部位进行多图谱 CT 分割,具有外推系数。多图谱数据库由 30 个截断 CT 组成,这些 CT 是手动分割的,以分离三种类型的体素(肌肉、脂肪和内脏脂肪)。为了评估 Anthropomer3D,我们进行了一次留一交叉验证,以测量 MBM、FBM、LBM、VAT 和 SAT。参考标准基于相应的全身 CT 的手动分割。还使用了一个 CT 切片的手动分割在 L3 水平。使用 Dice 系数、组内相关系数相关性(ICC)和 Bland-Altman 图分析相关性。该人群存在异质性(性别比 1:1;平均年龄 57 岁[最小 23;最大 74];平均 BMI 27 kg/m[最小 18;最大 40])。参考标准和 Anthropometer3D 之间的 Dice 系数非常好(平均值+/-标准差):肌肉 0.95±0.02、脂肪 1.00±0.01 和内脏脂肪 0.97±0.02。ICC 接近完美(最小 95%CI 值为 0.97)。与 L3 水平分割相比,所有 Bland-Altman 图值(平均差值、95%CI 和斜率)都对 Anthropometer3D 更好。Anthropometer3D 允许基于自动多切片分割进行多种人体测量。它比使用 L3 水平分割的估计更精确。