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磁共振成像和双能 X 射线吸收法测量脊髓损伤患者内脏脂肪组织:预测方程的建立和应用。

Measurement of Visceral Adipose Tissue in Persons With Spinal Cord Injury by Magnetic Resonance Imaging and Dual X-Ray Absorptiometry: Generation and Application of a Predictive Equation.

机构信息

Spinal Cord Injury and Disorders Hunter Holmes McGuire VA Medical Center, Richmond, VA, USA.

Department of Veterans Affairs Rehabilitation Research & Development Service National Center for the Medical Consequences of Spinal Cord Injury, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA.

出版信息

J Clin Densitom. 2020 Jan-Mar;23(1):63-72. doi: 10.1016/j.jocd.2018.12.003. Epub 2018 Dec 15.

Abstract

PURPOSE

Dual energy X-ray absorptiometry (DXA) and magnetic resonance imaging (MRI) permits quantification of visceral adipose tissue (VAT). However, DXA has not been validated against MRI in persons with chronic spinal cord injury (SCI). A predictive equation was generated from the measurement of VAT by MRI, a "gold" standard to quantitate VAT, compared to that of DXA, a method with several practical advantages.

METHOD

DXA and MRI scans were performed in 27 participants with SCI. MRI multiaxial images were captured for VAT analysis. DXA-VAT was quantified at the android region (DXA-VAT) using enCore software. Android regions of DXA and MRI were matched using android height. Volumes of multiaxial MRI-VAT and subcutaneous adipose tissue (SAT) were quantified for the android region (MRI-VAT, MRI-SAT) and total trunk (MRI-VAT). Linear regression analysis was used to establish the proposed predication equations. The prediction equations were then applied to an independent sample that consisted of 98 participants with SCI. Bland-Altman analysis was used to determine the limits of agreement.

RESULTS

DXA-VAT predicted 92% of the variance in MRI-VAT (SEE = 252.5, p < 0.0005) and 85% of the variance in MRI-VAT (SEE = 1526.9, p < 0.0005). DXA-SAT predicted 81.5% of the variance in MRI-SAT (SEE = 458.2, p < 0.0005). Bland-Altman analysis revealed a high level of agreement between MRI-VAT and DXA-VAT (mean bias = 58.45 cm). A predicted mean DXA-VAT of 995.2 cm was estimated as the population-specific cut-off point for high levels of VAT.

CONCLUSION

DXA-VAT may accurately predict MRI-VAT in persons with SCI. The ability of DXA to detect VAT changes in longitudinal studies in persons with SCI should be performed.

摘要

目的

双能 X 射线吸收法(DXA)和磁共振成像(MRI)可定量测量内脏脂肪组织(VAT)。然而,DXA 尚未在慢性脊髓损伤(SCI)患者中与 MRI 进行验证。本研究通过 MRI 测量 VAT 生成预测方程,MRI 是定量 VAT 的“金标准”,而 DXA 则具有多种实际优势。

方法

对 27 名 SCI 患者进行 DXA 和 MRI 扫描。对 MRI 多轴图像进行 VAT 分析。使用 enCore 软件在 Android 区域定量 DXA-VAT(DXA-VAT)。使用 Android 高度匹配 DXA 和 MRI 的 Android 区域。对 Android 区域(MRI-VAT、MRI-SAT)和整个躯干(MRI-VAT)定量测量多轴 MRI-VAT 和皮下脂肪组织(SAT)的体积。线性回归分析用于建立预测方程。然后将预测方程应用于包含 98 名 SCI 患者的独立样本。Bland-Altman 分析用于确定一致性界限。

结果

DXA-VAT 预测了 MRI-VAT 方差的 92%(SEE=252.5,p<0.0005)和 MRI-VAT 方差的 85%(SEE=1526.9,p<0.0005)。DXA-SAT 预测了 MRI-SAT 方差的 81.5%(SEE=458.2,p<0.0005)。Bland-Altman 分析显示 MRI-VAT 和 DXA-VAT 之间具有高度一致性(平均偏差=58.45 cm)。预测的 DXA-VAT 平均值为 995.2 cm,被估计为该人群中 VAT 水平升高的特定切点。

结论

DXA-VAT 可准确预测 SCI 患者的 MRI-VAT。应在 SCI 患者的纵向研究中评估 DXA 检测 VAT 变化的能力。

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