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

Liron S. McCauley; Mina P. Ghatas; Ryan M. Sumrell; Christopher M. Cirnigliaro; Steven C. Kirshblum; William A. Bauman; Ashraf S. Gorgey

doi:10.1016/j.jocd.2018.12.003

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

Liron S. McCauley
, Mina P. Ghatas
, Ryan M. Sumrell
, Christopher M. Cirnigliaro
, Steven C. Kirshblum
, William A. Bauman
, Ashraf S. Gorgey

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

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_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 cm³). A predicted mean DXA-VAT_ANDROID-VOL of 995.2 cm³ was estimated as the population-specific 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.

Original language	English
Pages (from-to)	63-72
Number of pages	10
Journal	Journal of Clinical Densitometry
Volume	23
Issue number	1
DOIs	https://doi.org/10.1016/j.jocd.2018.12.003
State	Published - 1 Jan 2020

Keywords

Dual energy X-ray absorptiometry
magnetic resonance imaging
spinal cord injury
visceral adipose tissue

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10.1016/j.jocd.2018.12.003

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McCauley, L. S., Ghatas, M. P., Sumrell, R. M., Cirnigliaro, C. M., Kirshblum, S. C., Bauman, W. A., & Gorgey, A. S. (2020). 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. Journal of Clinical Densitometry, 23(1), 63-72. https://doi.org/10.1016/j.jocd.2018.12.003

@article{c4e40f6c1e4b46a88862eb8d68f89d20,

title = "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",

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 {\textquotedblleft}gold{\textquotedblright} 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-VATANDROID-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-VATANDROID-VOL, MRI-SATANDROID-VOL) and total trunk (MRI-VATANDROID-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-VATANDROID-VOL predicted 92\% of the variance in MRI-VATANDROID-VOL (SEE = 252.5, p < 0.0005) and 85\% of the variance in MRI-VATTRUNK-VOL (SEE = 1526.9, p < 0.0005). DXA-SATANDROID-VOL predicted 81.5\% of the variance in MRI-SATANDROID-VOL (SEE = 458.2, p < 0.0005). Bland-Altman analysis revealed a high level of agreement between MRI-VATANDROID-VOL and DXA-VATANDROID-VOL (mean bias = 58.45 cm3). A predicted mean DXA-VATANDROID-VOL of 995.2 cm3 was estimated as the population-specific cut-off point for high levels of VAT. Conclusion: DXA-VATANDROID-VOL may accurately predict MRI-VATANDROID-VOL in persons with SCI. The ability of DXA to detect VAT changes in longitudinal studies in persons with SCI should be performed.",

keywords = "Dual energy X-ray absorptiometry, magnetic resonance imaging, spinal cord injury, visceral adipose tissue",

author = "McCauley, \{Liron S.\} and Ghatas, \{Mina P.\} and Sumrell, \{Ryan M.\} and Cirnigliaro, \{Christopher M.\} and Kirshblum, \{Steven C.\} and Bauman, \{William A.\} and Gorgey, \{Ashraf S.\}",

note = "Publisher Copyright: {\textcopyright} 2018 The International Society for Clinical Densitometry",

year = "2020",

month = jan,

day = "1",

doi = "10.1016/j.jocd.2018.12.003",

language = "English",

volume = "23",

pages = "63--72",

journal = "Journal of Clinical Densitometry",

issn = "1094-6950",

publisher = "Elsevier Inc.",

number = "1",

}

McCauley, LS, Ghatas, MP, Sumrell, RM, Cirnigliaro, CM, Kirshblum, SC, Bauman, WA & Gorgey, AS 2020, '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', Journal of Clinical Densitometry, vol. 23, no. 1, pp. 63-72. https://doi.org/10.1016/j.jocd.2018.12.003

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. / McCauley, Liron S.; Ghatas, Mina P.; Sumrell, Ryan M. et al.
In: Journal of Clinical Densitometry, Vol. 23, No. 1, 01.01.2020, p. 63-72.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Measurement of Visceral Adipose Tissue in Persons With Spinal Cord Injury by Magnetic Resonance Imaging and Dual X-Ray Absorptiometry

T2 - Generation and Application of a Predictive Equation

AU - McCauley, Liron S.

AU - Ghatas, Mina P.

AU - Sumrell, Ryan M.

AU - Cirnigliaro, Christopher M.

AU - Kirshblum, Steven C.

AU - Bauman, William A.

AU - Gorgey, Ashraf S.

PY - 2020/1/1

Y1 - 2020/1/1

N2 - 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-VATANDROID-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-VATANDROID-VOL, MRI-SATANDROID-VOL) and total trunk (MRI-VATANDROID-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-VATANDROID-VOL predicted 92% of the variance in MRI-VATANDROID-VOL (SEE = 252.5, p < 0.0005) and 85% of the variance in MRI-VATTRUNK-VOL (SEE = 1526.9, p < 0.0005). DXA-SATANDROID-VOL predicted 81.5% of the variance in MRI-SATANDROID-VOL (SEE = 458.2, p < 0.0005). Bland-Altman analysis revealed a high level of agreement between MRI-VATANDROID-VOL and DXA-VATANDROID-VOL (mean bias = 58.45 cm3). A predicted mean DXA-VATANDROID-VOL of 995.2 cm3 was estimated as the population-specific cut-off point for high levels of VAT. Conclusion: DXA-VATANDROID-VOL may accurately predict MRI-VATANDROID-VOL in persons with SCI. The ability of DXA to detect VAT changes in longitudinal studies in persons with SCI should be performed.

AB - 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-VATANDROID-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-VATANDROID-VOL, MRI-SATANDROID-VOL) and total trunk (MRI-VATANDROID-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-VATANDROID-VOL predicted 92% of the variance in MRI-VATANDROID-VOL (SEE = 252.5, p < 0.0005) and 85% of the variance in MRI-VATTRUNK-VOL (SEE = 1526.9, p < 0.0005). DXA-SATANDROID-VOL predicted 81.5% of the variance in MRI-SATANDROID-VOL (SEE = 458.2, p < 0.0005). Bland-Altman analysis revealed a high level of agreement between MRI-VATANDROID-VOL and DXA-VATANDROID-VOL (mean bias = 58.45 cm3). A predicted mean DXA-VATANDROID-VOL of 995.2 cm3 was estimated as the population-specific cut-off point for high levels of VAT. Conclusion: DXA-VATANDROID-VOL may accurately predict MRI-VATANDROID-VOL in persons with SCI. The ability of DXA to detect VAT changes in longitudinal studies in persons with SCI should be performed.

KW - Dual energy X-ray absorptiometry

KW - magnetic resonance imaging

KW - spinal cord injury

KW - visceral adipose tissue

UR - https://www.scopus.com/pages/publications/85059608389

U2 - 10.1016/j.jocd.2018.12.003

DO - 10.1016/j.jocd.2018.12.003

M3 - Article

C2 - 30638769

AN - SCOPUS:85059608389

SN - 1094-6950

VL - 23

SP - 63

EP - 72

JO - Journal of Clinical Densitometry

JF - Journal of Clinical Densitometry

IS - 1

ER -

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

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