Lower limb skeletal muscle mass: development of dual-energy X-ray absorptiometry prediction model
Lower limb skeletal muscle mass: development of dual-energy X-ray absorptiometry prediction model
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DOI：
10.1152/jappl.2000.89.4.1380
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发表时间：
2000-10-01
影响因子：
3.3
通讯作者：
Heymsfield, SB
中科院分区：
文献类型：
--
作者：
Shih, R;Wang, ZM;Heymsfield, SB
虽然磁共振成像（MRI）可以准确测量下肢骨骼肌（SM）质量，但这种方法复杂且成本高昂。一种潜在的实用替代方案是使用双能 X 射线吸收测定法 (DXA) 来估计下肢 SM。本研究的目的是开发和验证 DXA-SM 预测方程。选择相同的标志（即坐骨结节的下缘）来将下肢与躯干分开。采用MRI测量下肢SM，采用DXA测量下肢去脂软组织。共有 207 名成年人（104 名男性和 103 名女性）接受了评估[年龄 43 +/- 16 (SD) 岁，体重指数 (BMI) 24.6 +/- 3.7 kg/m(2)]。下肢 SM 与下肢无脂肪软组织之间观察到强相关性（R-2 = 0.89，P < 0.001）；年龄和 BMI 是较小但重要的 SM 预测变量。在交叉验证样本中，对于两个不同的建议预测方程，MRI 测量的 SM 质量和 DXA 预测的 SM 质量之间的差异很小（-0.006 +/- 1.07 和 -0.016 +/- 1.05 kg），一个使用无脂肪软组织，另一个添加年龄和 BMI 作为预测变量。 DXA 测量的下肢无脂肪软组织以及其他容易获得的测量方法可用于可靠地预测下肢骨骼肌质量。
Although magnetic resonance imaging (MRI) can accurately measure lower limb skeletal muscle (SM) mass, this method is complex and costly. A potential practical alternative is to estimate lower limb SM with dual-energy X-ray absorptiometry (DXA). The aim of the present study was to develop and validate DXA-SM prediction equations. Identical landmarks (i.e., inferior border of the ischial tuberosity) were selected for separating lower limb from trunk. Lower limb SM was measured by MRI, and lower limb fat-free soft tissue was measured by DXA. A total of 207 adults (104 men and 103 women) were evaluated [age 43 +/- 16 (SD) yr, body mass index (BMI) 24.6 +/- 3.7 kg/m(2)]. Strong correlations were observed between lower limb SM and lower limb fat-free soft tissue (R-2 = 0.89, P < 0.001); age and BMI were small but significant SM predictor variables. In the cross-validation sample, the differences between MRI-measured and DXA-predicted SM mass were small (-0.006 +/- 1.07 and -0.016 +/- 1.05 kg) for two different proposed prediction equations, one with fat-free soft tissue and the other with added age and BMI as predictor variables. DXA-measured lower limb fat-free soft tissue, along with other easily acquired measures, can be used to reliably predict lower limb skeletal muscle mass.