European Radiology

, Volume 29, Issue 2, pp 599–608 | Cite as

Association of paraspinal muscle water–fat MRI-based measurements with isometric strength measurements

  • Sarah SchlaegerEmail author
  • Stephanie Inhuber
  • Alexander Rohrmeier
  • Michael Dieckmeyer
  • Friedemann Freitag
  • Elisabeth Klupp
  • Dominik Weidlich
  • Georg Feuerriegel
  • Florian Kreuzpointner
  • Ansgar Schwirtz
  • Ernst J. Rummeny
  • Claus Zimmer
  • Jan S. Kirschke
  • Dimitrios C. Karampinos
  • Thomas Baum



Chemical shift encoding-based water–fat MRI derived proton density fat fraction (PDFF) of the paraspinal muscles has been emerging as a surrogate marker in subjects with sarcopenia, lower back pain, injuries and neuromuscular disorders. The present study investigates the performance of paraspinal muscle PDFF and cross-sectional area (CSA) in predicting isometric muscle strength.


Twenty-six healthy subjects (57.7% women; age: 30 ± 6 years) underwent 3T axial MRI of the lumbar spine using a six-echo 3D spoiled gradient echo sequence for chemical shift encoding-based water–fat separation. Erector spinae and psoas muscles were segmented bilaterally from L2 level to L5 level to determine CSA and PDFF. Muscle flexion and extension maximum isometric torque values [Nm] at the back were measured with an isokinetic dynamometer.


Significant correlations between CSA and muscle strength measurements were observed for erector spinae muscle CSA (r = 0.40; p = 0.044) and psoas muscle CSA (r = 0.61; p = 0.001) with relative flexion strength. Erector spinae muscle PDFF correlated significantly with relative muscle strength (extension: r = -0.51; p = 0.008; flexion: r = -0.54; p = 0.005). Erector spinae muscle PDFF, but not CSA, remained a statistically significant (p < 0.05) predictor of relative extensor strength in multivariate regression models (R2adj = 0.34; p = 0.002).


PDFF measurements improved the prediction of paraspinal muscle strength beyond CSA. Therefore, chemical shift encoding-based water–fat MRI may be used to detect subtle changes in the paraspinal muscle composition.

Key Points

• We investigated the association of paraspinal muscle fat fraction based on chemical shift encoding-based water–fat MRI with isometric strength measurements in healthy subjects.

• Erector spinae muscle PDFF correlated significantly with relative muscle strength.

• PDFF measurements improved prediction of paraspinal muscle strength beyond CSA.


Magnetic resonance imaging Paraspinal muscle Muscle strength 



Body mass index


Cross-sectional area


Left erector spinae muscles


Right erector spinae muscles


International Physical Activity Questionnaire


Lower back pain


Muscle fat infiltration


Maximum voluntary isometric contraction


Neuromuscular diseases


Proton density fat fraction


Left psoas muscle


Right psoas muscle


Root mean square coefficients of variation


Regions of interest



This study has received funding by Philips Healthcare, the German Research Foundation (DFG-SFB824/A9) and TUM Faculty of Medicine KKF grant H01.

Compliance with ethical standards


The scientific guarantor of this publication is Thomas Baum, MD.

Conflict of interest

The authors of this manuscript declare relationships with the following companies: Philips Healthcare.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was obtained from all subjects in this study.

Ethical approval

Institutional Review Board approval was obtained.


• Prospective

• Cross-sectional study

• Performed at one institution


  1. 1.
    Hicks GE, Simonsick EM, Harris TB et al (2005) Cross-sectional associations between trunk muscle composition, back pain, and physical function in the health, aging and body composition study. J Gerontol A Biol Sci Med Sci 60:882–887CrossRefGoogle Scholar
  2. 2.
    Fisher MJ, Meyer RA, Adams GR, Foley JM, Potchen EJ (1990) Direct relationship between proton T2 and exercise intensity in skeletal muscle MR images. Invest Radiol 25:480–485CrossRefGoogle Scholar
  3. 3.
    Shellock FG, Fukunaga T, Mink JH, Edgerton VR (1991) Acute effects of exercise on MR imaging of skeletal muscle: concentric vs eccentric actions. AJR Am J Roentgenol 156:765–768CrossRefGoogle Scholar
  4. 4.
    Takahashi H, Kuno S, Miyamoto T et al (1994) Changes in magnetic resonance images in human skeletal muscle after eccentric exercise. Eur J Appl Physiol Occup Physiol 69:408–413CrossRefGoogle Scholar
  5. 5.
    Mendez-Villanueva A, Suarez-Arrones L, Rodas G et al (2016) MRI-Based Regional Muscle Use during Hamstring Strengthening Exercises in Elite Soccer Players. PLoS One 11:e0161356CrossRefGoogle Scholar
  6. 6.
    Crawford RJ, Filli L, Elliott JM et al (2016) Age- and Level-Dependence of Fatty Infiltration in Lumbar Paravertebral Muscles of Healthy Volunteers. AJNR Am J Neuroradiol 37:742–748CrossRefGoogle Scholar
  7. 7.
    Dahlqvist JR, Vissing CR, Hedermann G, Thomsen C, Vissing J (2017) Fat Replacement of Paraspinal Muscles with Aging in Healthy Adults. Med Sci Sports Exerc 49:595–601CrossRefGoogle Scholar
  8. 8.
    Heymsfield SB, Gonzalez MC, Lu J, Jia G, Zheng J (2015) Skeletal muscle mass and quality: evolution of modern measurement concepts in the context of sarcopenia. Proc Nutr Soc 74:355–366CrossRefGoogle Scholar
  9. 9.
    Karampinos DC, Baum T, Nardo L et al (2012) Characterization of the regional distribution of skeletal muscle adipose tissue in type 2 diabetes using chemical shift-based water/fat separation. J Magn Reson Imaging 35:899–907CrossRefGoogle Scholar
  10. 10.
    Kjaer P, Bendix T, Sorensen JS, Korsholm L, Leboeuf-Yde C (2007) Are MRI-defined fat infiltrations in the multifidus muscles associated with low back pain? BMC Med 5:2–2CrossRefGoogle Scholar
  11. 11.
    Teichtahl AJ, Urquhart DM, Wang Y et al (2015) Fat infiltration of paraspinal muscles is associated with low back pain, disability, and structural abnormalities in community-based adults. Spine J 15:1593–1601CrossRefGoogle Scholar
  12. 12.
    D'Hooge R, Cagnie B, Crombez G, Vanderstraeten G, Dolphens M, Danneels L (2012) Increased intramuscular fatty infiltration without differences in lumbar muscle cross-sectional area during remission of unilateral recurrent low back pain. Man Ther 17:584–588CrossRefGoogle Scholar
  13. 13.
    Fischer MA, Nanz D, Shimakawa A et al (2013) Quantification of muscle fat in patients with low back pain: comparison of multi-echo MR imaging with single-voxel MR spectroscopy. Radiology 266:555–563CrossRefGoogle Scholar
  14. 14.
    Elliott JM, Courtney DM, Rademaker A, Pinto D, Sterling MM, Parrish TB (2015) The Rapid and Progressive Degeneration of the Cervical Multifidus in Whiplash: An MRI Study of Fatty Infiltration. Spine (Phila Pa 1976) 40:E694–E700CrossRefGoogle Scholar
  15. 15.
    Maly MR, Calder KM, Macintyre NJ, Beattie KA (2013) Relationship of intermuscular fat volume in the thigh with knee extensor strength and physical performance in women at risk of or with knee osteoarthritis. Arthritis Care Res (Hoboken) 65:44–52CrossRefGoogle Scholar
  16. 16.
    Sun D, Liu P, Cheng J, Ma Z, Liu J, Qin T (2017) Correlation between intervertebral disc degeneration, paraspinal muscle atrophy, and lumbar facet joints degeneration in patients with lumbar disc herniation. BMC Musculoskelet Disord 18:167CrossRefGoogle Scholar
  17. 17.
    Janssen BH, Voet NBM, Nabuurs CI et al (2014) Distinct Disease Phases in Muscles of Facioscapulohumeral Dystrophy Patients Identified by MR Detected Fat Infiltration. PLoS One 9:e85416CrossRefGoogle Scholar
  18. 18.
    Dahlqvist JR, Vissing CR, Thomsen C, Vissing J (2014) Severe paraspinal muscle involvement in facioscapulohumeral muscular dystrophy. Neurology 83:1178–1183CrossRefGoogle Scholar
  19. 19.
    D'Aprile P, Tarantino A, Jinkins JR, Brindicci D (2007) The value of fat saturation sequences and contrast medium administration in MRI of degenerative disease of the posterior/perispinal elements of the lumbosacral spine. Eur Radiol 17:523–531CrossRefGoogle Scholar
  20. 20.
    Kumar Y, Hayashi D (2016) Role of magnetic resonance imaging in acute spinal trauma: a pictorial review. BMC Musculoskelet Disord 17:310CrossRefGoogle Scholar
  21. 21.
    Crawford RJ, Cornwall J, Abbott R, Elliott JM (2017) Manually defining regions of interest when quantifying paravertebral muscles fatty infiltration from axial magnetic resonance imaging: a proposed method for the lumbar spine with anatomical cross-reference. BMC Musculoskelet Disord 18:25CrossRefGoogle Scholar
  22. 22.
    Smith AC, Parrish TB, Abbott R et al (2014) Muscle-fat MRI: 1.5 Tesla and 3.0 Tesla versus histology. Muscle Nerve 50:170–176CrossRefGoogle Scholar
  23. 23.
    Hadar H, Gadoth N, Heifetz M (1983) Fatty replacement of lower paraspinal muscles: normal and neuromuscular disorders. AJR Am J Roentgenol 141:895–898CrossRefGoogle Scholar
  24. 24.
    Doherty TJ (2003) Invited review: Aging and sarcopenia. J Appl Physiol (1985) 95:1717–1727CrossRefGoogle Scholar
  25. 25.
    Fortin M, Macedo LG (2013) Multifidus and paraspinal muscle group cross-sectional areas of patients with low back pain and control patients: a systematic review with a focus on blinding. Phys Ther 93:873–888CrossRefGoogle Scholar
  26. 26.
    Fortin M, Videman T, Gibbons LE, Battie MC (2014) Paraspinal muscle morphology and composition: a 15-yr longitudinal magnetic resonance imaging study. Med Sci Sports Exerc 46:893–901CrossRefGoogle Scholar
  27. 27.
    Valentin S, Licka T, Elliott J (2015) Age and side-related morphometric MRI evaluation of trunk muscles in people without back pain. Man Ther 20:90–95CrossRefGoogle Scholar
  28. 28.
    Fortin M, Yuan Y, Battié MC (2013) Factors Associated With Paraspinal Muscle Asymmetry in Size and Composition in a General Population Sample of Men. Phys Ther 93:1540–1550CrossRefGoogle Scholar
  29. 29.
    Shahidi B, Parra CL, Berry DB et al (2017) Contribution of Lumbar Spine Pathology and Age to Paraspinal Muscle Size and Fatty Infiltration. Spine (Phila Pa 1976) 42:616–623CrossRefGoogle Scholar
  30. 30.
    Goodpaster BH, Carlson CL, Visser M et al (2001) Attenuation of skeletal muscle and strength in the elderly: The Health ABC Study. J Appl Physiol (1985) 90:2157–2165CrossRefGoogle Scholar
  31. 31.
    Goodpaster BH, Park SW, Harris TB et al (2006) The loss of skeletal muscle strength, mass, and quality in older adults: the health, aging and body composition study. J Gerontol A Biol Sci Med Sci 61:1059–1064CrossRefGoogle Scholar
  32. 32.
    Baum T, Inhuber S, Dieckmeyer M et al (2016) Association of quadriceps muscle fat with isometric strength measurements in healthy males using chemical shift encoding-based water-fat magnetic resonance imaging. J Comput Assist Tomogr 40:447–451CrossRefGoogle Scholar
  33. 33.
    Stark T, Walker B, Phillips JK, Fejer R, Beck R (2011) Hand-held dynamometry correlation with the gold standard isokinetic dynamometry: a systematic review. Pm r 3:472–479CrossRefGoogle Scholar
  34. 34.
    Moreau CE, Green BN, Johnson CD, Moreau SR (2001) Isometric back extension endurance tests: a review of the literature. J Manipulative Physiol Ther 24:110–122CrossRefGoogle Scholar
  35. 35.
    Guedes DP, Lopes CC, Guedes JERP (2005) Reprodutibilidade e validade do Questionário Internacional de Atividade Física em adolescentes. Revista Brasileira de Medicina do Esporte 11:151–158CrossRefGoogle Scholar
  36. 36.
    Kurtze N, Rangul V, Hustvedt BE (2008) Reliability and validity of the international physical activity questionnaire in the Nord-Trondelag health study (HUNT) population of men. BMC Med Res Methodol 8:63CrossRefGoogle Scholar
  37. 37.
    Karampinos DC, Yu H, Shimakawa A, Link TM, Majumdar S (2011) T1-corrected fat quantification using chemical shift-based water/fat separation: application to skeletal muscle. Magn Reson Med 66:1312–1326CrossRefGoogle Scholar
  38. 38.
    Gluer CC, Blake G, Lu Y, Blunt BA, Jergas M, Genant HK (1995) Accurate assessment of precision errors: how to measure the reproducibility of bone densitometry techniques. Osteoporos Int 5:262–270CrossRefGoogle Scholar
  39. 39.
    Roth R, Donath L, Kurz E, Zahner L, Faude O (2017) Absolute and relative reliability of isokinetic and isometric trunk strength testing using the IsoMed-2000 dynamometer. Phys Ther Sport 24:26–31CrossRefGoogle Scholar
  40. 40.
    Miller AEJ, MacDougall JD, Tarnopolsky MA, Sale DG (1993) Gender differences in strength and muscle fiber characteristics. Eur J Appl Physiol Occup Physiol 66:254–262CrossRefGoogle Scholar
  41. 41.
    Horvath JJ, Austin SL, Case LE et al (2015) Correlation between quantitative whole-body muscle magnetic resonance imaging and clinical muscle weakness in pompe disease. Muscle Nerve 51:722–730CrossRefGoogle Scholar
  42. 42.
    Willis TA, Hollingsworth KG, Coombs A et al (2013) Quantitative Muscle MRI as an Assessment Tool for Monitoring Disease Progression in LGMD2I: A Multicentre Longitudinal Study. PLoS One 8:e70993CrossRefGoogle Scholar
  43. 43.
    Willis TA, Hollingsworth KG, Coombs A et al (2014) Quantitative Magnetic Resonance Imaging in Limb-Girdle Muscular Dystrophy 2I: A Multinational Cross-Sectional Study. PLoS One 9:e90377CrossRefGoogle Scholar
  44. 44.
    Kumar D, Karampinos DC, MacLeod TD et al (2014) Quadriceps intramuscular fat fraction rather than muscle size is associated with knee osteoarthritis. Osteoarthritis Cartilage 22:226–234CrossRefGoogle Scholar
  45. 45.
    Colloca CJ, Hinrichs RN (2005) The biomechanical and clinical significance of the lumbar erector spinae flexion-relaxation phenomenon: a review of literature. J Manipulative Physiol Ther 28:623–631CrossRefGoogle Scholar

Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  • Sarah Schlaeger
    • 1
    • 2
    Email author
  • Stephanie Inhuber
    • 3
  • Alexander Rohrmeier
    • 1
  • Michael Dieckmeyer
    • 2
  • Friedemann Freitag
    • 2
  • Elisabeth Klupp
    • 1
  • Dominik Weidlich
    • 2
  • Georg Feuerriegel
    • 1
  • Florian Kreuzpointner
    • 3
  • Ansgar Schwirtz
    • 3
  • Ernst J. Rummeny
    • 2
  • Claus Zimmer
    • 1
  • Jan S. Kirschke
    • 1
  • Dimitrios C. Karampinos
    • 2
  • Thomas Baum
    • 1
  1. 1.Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der IsarTechnical University of MunichMunichGermany
  2. 2.Department of Diagnostic and Interventional Radiology, Klinikum rechts der IsarTechnical University of MunichMunichGermany
  3. 3.Department of Sport and Health SciencesTechnical University of MunichMunichGermany

Personalised recommendations