European Radiology

, Volume 28, Issue 5, pp 1801–1808 | Cite as

Peripheral nerve diffusion tensor imaging (DTI): normal values and demographic determinants in a cohort of 60 healthy individuals

  • Moritz Kronlage
  • Véronique Schwehr
  • Daniel Schwarz
  • Tim Godel
  • Lorenz Uhlmann
  • Sabine Heiland
  • Martin Bendszus
  • Philipp Bäumer
Neuro
  • 215 Downloads

Abstract

Objective

To identify demographic determinants of peripheral nerve diffusion tensor imaging (DTI) and to establish normal values for fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD).

Methods

Sixty subjects were examined at 3 Tesla by single-shot DTI. FA, AD, RD, and MD were collected for the sciatic, tibial, median, ulnar, and radial nerve and were correlated with demographic variables.

Results

Mean FA of all nerves declined with increasing age (r = −0.77), which could be explained by RD increasing (r = 0.56) and AD declining (r = −0.40) with age. Moreover, FA was inversely associated with height (r = −0.28), weight (r = −0.38) and BMI (r = −0.35). Although FA tended to be lower in men than women (p = 0.052), this difference became completely negligible after adjustment to body weight. A multiple linear regression model for FA was calculated with age and weight as predictors (defined by backward variable selection), yielding an R 2 = 0.71 and providing a correction formula to adjust FA for age and weight.

Conclusion

Peripheral nerve DTI parameters depend on demographic variables. The most important determinants age and weight should be considered in all studies employing peripheral nerve DTI.

Key points

• Peripheral nerve diffusion tensor imaging (DTI) parameters depend on demographic variables.

• Fractional anisotropy (FA) declines with increasing age and weight.

• Gender does not systematically affect peripheral nerve DTI.

• The formula presented here allows adjustment of FA for demographic variables.

Keywords

Diffusion tensor imaging Magnetic resonance imaging Peripheral nervous system Aging Reference values 

Notes

Acknowledgements

We are grateful to Thorsten Feiweier from Siemens Healthcare for providing the work-in-progress package which included the DTI sequence that we used for imaging. This study was supported by the Deutsche Forschungsgemeinschaft (SFB 1118).

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Dr. Moritz Kronlage.

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

One of the authors (Dr. Lorenz Uhlmann) has significant statistical expertise.

Informed consent

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

Ethical approval

Institutional review board approval was obtained.

Study subjects or cohorts overlap

Normal values of nerve calibre and T2 relaxometry in the same cohort were published separately in               Kronlage M, Schwehr V, Schwarz D et al (2017) Normal Values and Demographic Determinants of Nerve Caliber and T2 Relaxometry in 60 healthy individuals. Clin Neuroradiol. [Epub ahead of print]                         Eighteen of 60 subjects were used in a control group for

1. Kronlage M, Pitarokoili K, Schwarz D et al (2017) Diffusion tensor imaging in chronic inflammatory demyelinating polyneuropathy: diagnostic accuracy and correlation with electrophysiology. Invest Radiol 52:701–7

2. Kronlage M, Baumer P, Pitarokoili K et al (2017) Large coverage MR neurography in CIDP: diagnostic accuracy and electrophysiological correlation. J Neurol 264:1434–43

Methodology

prospective

cross-sectional study/observational

performed at one institution

References

  1. 1.
    Filler AG, Howe FA, Hayes CE et al (1993) Magnetic resonance neurography. Lancet 341:659–661CrossRefPubMedGoogle Scholar
  2. 2.
    Pham M, Baumer T, Bendszus M (2014) Peripheral nerves and plexus: imaging by MR-neurography and high-resolution ultrasound. Curr Opin Neurol 27:370–379CrossRefPubMedGoogle Scholar
  3. 3.
    Heckel A, Weiler M, Xia A et al (2015) Peripheral nerve diffusion tensor imaging: assessment of axon and myelin sheath integrity. PLoS One 10:e0130833CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Guggenberger R, Markovic D, Eppenberger P et al (2012) Assessment of median nerve with MR neurography by using diffusion-tensor imaging: normative and pathologic diffusion values. Radiology 265:194–203CrossRefPubMedGoogle Scholar
  5. 5.
    Hiltunen J, Kirveskari E, Numminen J et al (2012) Pre- and post-operative diffusion tensor imaging of the median nerve in carpal tunnel syndrome. Eur Radiol 22:1310–1319CrossRefPubMedGoogle Scholar
  6. 6.
    Hiltunen J, Suortti T, Arvela S et al (2005) Diffusion tensor imaging and tractography of distal peripheral nerves at 3 T. Clin Neurophysiol 116:2315–2323CrossRefPubMedGoogle Scholar
  7. 7.
    Haakma W, Jongbloed BA, Froeling M et al (2017) MRI shows thickening and altered diffusion in the median and ulnar nerves in multifocal motor neuropathy. Eur Radiol 27:2216–2224CrossRefPubMedGoogle Scholar
  8. 8.
    Wu C, Wang G, Zhao Y et al (2017) Assessment of tibial and common peroneal nerves in diabetic peripheral neuropathy by diffusion tensor imaging: a case control study. Eur Radiol 27:3523–3531CrossRefPubMedGoogle Scholar
  9. 9.
    Breitenseher JB, Kranz G, Hold A et al (2015) MR neurography of ulnar nerve entrapment at the cubital tunnel: a diffusion tensor imaging study. Eur Radiol 25:1911–1918CrossRefPubMedGoogle Scholar
  10. 10.
    Jengojan S, Kovar F, Breitenseher J et al (2015) Acute radial nerve entrapment at the spiral groove: detection by DTI-based neurography. Eur Radiol 25:1678–1683CrossRefPubMedGoogle Scholar
  11. 11.
    Kronlage M, Pitarokoili K, Schwarz D et al (2017) Diffusion tensor imaging in chronic inflammatory demyelinating polyneuropathy: diagnostic accuracy and correlation with electrophysiology. Invest Radiol 52:701–707CrossRefPubMedGoogle Scholar
  12. 12.
    Chhabra A, Madhuranthakam AJ, Andreisek G (2017) Magnetic resonance neurography: current perspectives and literature review. Eur Radiol.  https://doi.org/10.1007/s00330-017-4976-8
  13. 13.
    Basser PJ, Mattiello J, LeBihan D (1994) MR diffusion tensor spectroscopy and imaging. Biophys J 66:259–267CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Basser PJ, Mattiello J, LeBihan D (1994) Estimation of the effective self-diffusion tensor from the NMR spin echo. J Magn Reson B 103:247–254CrossRefPubMedGoogle Scholar
  15. 15.
    Mori S, Zhang J (2006) Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron 51:527–539CrossRefPubMedGoogle Scholar
  16. 16.
    O'Donnell LJ, Westin CF (2011) An introduction to diffusion tensor image analysis. Neurosurg Clin N Am 22:185–196 viiiCrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Hagmann P, Jonasson L, Maeder P et al (2006) Understanding diffusion MR imaging techniques: from scalar diffusion-weighted imaging to diffusion tensor imaging and beyond. Radiographics 26:S205–S223CrossRefPubMedGoogle Scholar
  18. 18.
    Kasprian G, Amann G, Panotopoulos J et al (2015) Peripheral nerve tractography in soft tissue tumors: a preliminary 3-tesla diffusion tensor magnetic resonance imaging study. Muscle Nerve 51:338–345CrossRefPubMedGoogle Scholar
  19. 19.
    Kakuda T, Fukuda H, Tanitame K et al (2011) Diffusion tensor imaging of peripheral nerve in patients with chronic inflammatory demyelinating polyradiculoneuropathy: a feasibility study. Neuroradiology 53:955–960CrossRefPubMedGoogle Scholar
  20. 20.
    Simon NG, Lagopoulos J, Paling S et al (2017) Peripheral nerve diffusion tensor imaging as a measure of disease progression in ALS. J Neurol 264:882–890CrossRefPubMedGoogle Scholar
  21. 21.
    Breckwoldt MO, Stock C, Xia A et al (2015) Diffusion tensor imaging adds diagnostic accuracy in magnetic resonance neurography. Invest Radiol 50:498–504CrossRefPubMedGoogle Scholar
  22. 22.
    Moriyama H, Amano K, Itoh M et al (2007) Morphometric aspects of peripheral nerves in adults and the elderly. J Peripher Nerv Syst 12:205–209CrossRefPubMedGoogle Scholar
  23. 23.
    Ugrenovic S, Jovanovic I, Vasovic L et al (2016) Morphometric analysis of the diameter and g-ratio of the myelinated nerve fibers of the human sciatic nerve during the aging process. Anat Sci Int 91:238–245CrossRefPubMedGoogle Scholar
  24. 24.
    Dorfman LJ, Bosley TM (1979) Age-related changes in peripheral and central nerve conduction in man. Neurology 29:38–44CrossRefPubMedGoogle Scholar
  25. 25.
    Matsumoto H, Konoma Y, Shimizu T et al (2012) Aging influences central motor conduction less than peripheral motor conduction: a transcranial magnetic stimulation study. Muscle Nerve 46:932–936CrossRefPubMedGoogle Scholar
  26. 26.
    Cartwright MS, Passmore LV, Yoon JS et al (2008) Cross-sectional area reference values for nerve ultrasonography. Muscle Nerve 37:566–571CrossRefPubMedGoogle Scholar
  27. 27.
    Kabakci N, Gurses B, Firat Z et al (2007) Diffusion tensor imaging and tractography of median nerve: normative diffusion values. AJR Am J Roentgenol 189:923–927CrossRefPubMedGoogle Scholar
  28. 28.
    Tanitame K, Iwakado Y, Akiyama Y et al (2012) Effect of age on the fractional anisotropy (FA) value of peripheral nerves and clinical significance of the age-corrected FA value for evaluating polyneuropathies. Neuroradiology 54:815–821CrossRefPubMedGoogle Scholar
  29. 29.
    Franco CD (2012) Connective tissues associated with peripheral nerves. Reg Anesth Pain Med 37:363–365CrossRefPubMedGoogle Scholar
  30. 30.
    Song SK, Sun SW, Ramsbottom MJ et al (2002) Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water. Neuroimage 17:1429–1436CrossRefPubMedGoogle Scholar
  31. 31.
    Song SK, Sun SW, Ju WK et al (2003) Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. Neuroimage 20:1714–1722CrossRefPubMedGoogle Scholar
  32. 32.
    Mac Donald CL, Dikranian K, Bayly P et al (2007) Diffusion tensor imaging reliably detects experimental traumatic axonal injury and indicates approximate time of injury. J Neurosci 27:11869–11876CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Lin M, He H, Schifitto G, Zhong J (2016) Simulation of changes in diffusion related to different pathologies at cellular level after traumatic brain injury. Magn Reson Med 76:290–300CrossRefPubMedGoogle Scholar
  34. 34.
    Jacobs JM, Love S (1985) Qualitative and quantitative morphology of human sural nerve at different ages. Brain 108:897–924CrossRefPubMedGoogle Scholar
  35. 35.
    Stetson DS, Albers JW, Silverstein BA, Wolfe RA (1992) Effects of age, sex, and anthropometric factors on nerve conduction measures. Muscle Nerve 15:1095–1104CrossRefPubMedGoogle Scholar
  36. 36.
    Rivner MH, Swift TR, Malik K (2001) Influence of age and height on nerve conduction. Muscle Nerve 24:1134–1141CrossRefPubMedGoogle Scholar
  37. 37.
    Kurokawa K, Mimori Y, Tanaka E et al (1999) Age-related change in peripheral nerve conduction: compound muscle action potential duration and dispersion. Gerontology 45:168–173CrossRefPubMedGoogle Scholar
  38. 38.
    Awang MS, Abdullah JM, Abdullah MR et al (2006) Nerve conduction study among healthy malays. The influence of age, height and body mass index on median, ulnar, common peroneal and sural nerves. Malays J Med Sci 13:19–23PubMedPubMedCentralGoogle Scholar
  39. 39.
    Filli L, Piccirelli M, Kenkel D et al (2016) Accelerated magnetic resonance diffusion tensor imaging of the median nerve using simultaneous multi-slice echo planar imaging with blipped CAIPIRINHA. Eur Radiol 26:1921–1928CrossRefPubMedGoogle Scholar
  40. 40.
    Fox RJ, Sakaie K, Lee JC et al (2012) A validation study of multicenter diffusion tensor imaging: reliability of fractional anisotropy and diffusivity values. AJNR Am J Neuroradiol 33:695–700CrossRefPubMedGoogle Scholar
  41. 41.
    Manoliu A, Ho M, Nanz D et al (2016) Diffusion tensor imaging of lumbar nerve roots: comparison between fast readout-segmented and selective-excitation acquisitions. Invest Radiol 51:499–504CrossRefPubMedGoogle Scholar

Copyright information

© European Society of Radiology 2017

Authors and Affiliations

  1. 1.Department of NeuroradiologyHeidelberg University HospitalHeidelbergGermany
  2. 2.Institute for medical biometry and informaticsHeidelberg UniversityHeidelbergGermany
  3. 3.Department of RadiologyGerman Cancer Research CenterHeidelbergGermany

Personalised recommendations