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

被引:10
作者
McCauley, Liron S. [1 ]
Ghatas, Mina P. [1 ]
Sumrell, Ryan M. [1 ]
Cirnigliaro, Christopher M. [3 ]
Kirshblum, Steven C. [6 ,7 ]
Bauman, William A. [3 ,4 ,5 ]
Gorgey, Ashraf S. [1 ,2 ]
机构
[1] Hunter Holmes McGuire VA Med Ctr, Spinal Cord Injury & Disorders, 1201 Broad Rock Blvd, Richmond, VA 23249 USA
[2] Virginia Commonwealth Univ, Phys Med & Rehabil, Richmond, VA USA
[3] James J Peters Vet Affairs Med Ctr, Dept Vet Affairs, Rehabil Res & Dev Serv, Natl Ctr Med Consequences Spinal Cord Injury, Bronx, NY USA
[4] Icahn Sch Med Mt Sinai, Dept Med, New York, NY 10029 USA
[5] Icahn Sch Med Mt Sinai, Dept Rehabil Med, New York, NY 10029 USA
[6] Kessler Inst Rehabil, W Orange, NJ USA
[7] Rutgers New Jersey Med Sch, Dept Phys Med & Rehabil, Newark, NJ USA
关键词
Dual energy X-ray absorptiometry; magnetic resonance imaging; spinal cord injury; visceral adipose tissue; BODY-MASS INDEX; QUANTIFICATION; FAT; ASSOCIATIONS; INDIVIDUALS; OBESITY; RISK; MEN; MRI; CT;
D O I
10.1016/j.jocd.2018.12.003
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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(ANDROID-VOL)) 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(ANDROID-VOL), MRI-SAT(ANDROID-VOL)) and total trunk (MRI-VAT(ANDROID-VOL)). 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(ANDROID-VOL )predicted 92% of the variance in MRI-VAT(ANDROID-VOL) (SEE = 252.5, p < 0.0005) and 85% of the variance in MRI-VAT(TRUNK-VOL) (SEE = 1526.9, p < 0.0005). DXA-SAT(ANDROID-VOL) predicted 81.5% of the variance in MRI-SAT(ANDROID-VOL) (SEE = 458.2, p < 0.0005). Bland-Altman analysis revealed a high level of agreement between MRI-VAT(ANDROID-VOL) and DXA-VAT(ANDROID-VOL) (mean bias = 58.45 cm(3)). A predicted mean DXA-VAT(ANDROID-VOL) of 995.2 cm(3) was estimated as the population-spe- cific cut-off point for high levels of VAT. Conclusion: DXA-VAT(ANDROID-VOL) may accurately predict MRI-VAT(ANDROID-VOL) in persons with SCI. The ability of DXA to detect VAT changes in longitudinal studies in persons with SCI should be performed.
引用
收藏
页码:63 / 72
页数:10
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