Muscle Changes Detected with Diffusion-Tensor Imaging after Long-Distance Running

Published Online:Oct 3 2014https://doi.org/10.1148/radiol.14140702

Abstract

We developed a feasible method for diffusion-tensor imaging (DTI) measurements of the upper legs that includes frequently injured muscles, such as hamstrings, in one imaging session; our study also revealed changes in DTI parameters that over time were not revealed by qualitative T2-weighted MR imaging with fat suppression.

Purpose

To develop a protocol for diffusion-tensor imaging (DTI) of the complete upper legs and to demonstrate feasibility of detection of subclinical sports-related muscle changes in athletes after strenuous exercise, which remain undetected by using conventional T2-weighted magnetic resonance (MR) imaging with fat suppression.

Materials and Methods

The research was approved by the institutional ethics committee review board, and the volunteers provided written consent before the study. Five male amateur long-distance runners underwent an MR examination (DTI, T1-weighted MR imaging, and T2-weighted MR imaging with fat suppression) of both upper legs 1 week before, 2 days after, and 3 weeks after they participated in a marathon. The tensor eigenvalues (λ₁, λ₂, and λ₃), the mean diffusivity, and the fractional anisotropy (FA) were derived from the DTI data. Data per muscle from the three time-points were compared by using a two-way mixed-design analysis of variance with a Bonferroni posthoc test.

Results

The DTI protocol allowed imaging of both complete upper legs with adequate signal-to-noise ratio and within a 20-minute imaging time. After the marathon, T2-weighted MR imaging revealed grade 1 muscle strains in nine of the 180 investigated muscles. The three eigenvalues, mean diffusivity, and FA were significantly increased (P < .05) in the biceps femoris muscle 2 days after running. Mean diffusivity and eigenvalues λ₁ and λ₂ were significantly (P < .05) increased in the semitendinosus and gracilis muscles 2 days after the marathon.

Conclusion

A feasible method for DTI measurements of the upper legs was developed that fully included frequently injured muscles, such as hamstrings, in one single imaging session. This study also revealed changes in DTI parameters that over time were not revealed by qualitative T2-weighted MR imaging with fat suppression.

Online supplemental material is available for this article.

References

1. Taunton JE, Ryan MB, Clement DB, McKenzie DC, Lloyd-Smith DR, Zumbo BD. A retrospective case-control analysis of 2002 running injuries. Br J Sports Med 2002;36(2):95–101. Crossref, Medline, Google Scholar
2. van Gent RN, Siem D, van Middelkoop M, van Os AG, Bierma-Zeinstra SM, Koes BW. Incidence and determinants of lower extremity running injuries in long distance runners: a systematic review. Br J Sports Med 2007;41(8):469–480; discussion 480. Crossref, Medline, Google Scholar
3. Heiderscheit BC, Sherry MA, Silder A, Chumanov ES, Thelen DG. Hamstring strain injuries: recommendations for diagnosis, rehabilitation, and injury prevention. J Orthop Sports Phys Ther 2010;40(2):67–81. Crossref, Medline, Google Scholar
4. Mueller-Wohlfahrt H-W, Haensel L, Mithoefer K, et al. Terminology and classification of muscle injuries in sport: the Munich consensus statement. Br J Sports Med 2013;47(6):342–350. Crossref, Medline, Google Scholar
5. Connell DA, Schneider-Kolsky ME, Hoving JL, et al. Longitudinal study comparing sonographic and MRI assessments of acute and healing hamstring injuries. AJR Am J Roentgenol 2004;183(4):975–984. Crossref, Medline, Google Scholar
6. Reurink G, Goudswaard GJ, Tol JL, et al. MRI observations at return to play of clinically recovered hamstring injuries. Br J Sports Med 2013 Nov 19. [Epub ahead of print] Google Scholar
7. Le Bihan D, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 1986;161(2):401–407. Link, Google Scholar
8. Pierpaoli C, Basser PJ. Toward a quantitative assessment of diffusion anisotropy. Magn Reson Med 1996;36(6):893–906. Crossref, Medline, Google Scholar
9. Van Donkelaar CC, Kretzers LJ, Bovendeerd PH, et al. Diffusion tensor imaging in biomechanical studies of skeletal muscle function. J Anat 1999;194(Pt 1):79–88. Crossref, Medline, Google Scholar
10. Yanagisawa O, Kurihara T, Kobayashi N, Fukubayashi T. Strenuous resistance exercise effects on magnetic resonance diffusion parameters and muscle-tendon function in human skeletal muscle. J Magn Reson Imaging 2011;34(4):887–894. Crossref, Medline, Google Scholar
11. Ababneh ZQ, Ababneh R, Maier SE, et al. On the correlation between T(2) and tissue diffusion coefficients in exercised muscle: quantitative measurements at 3T within the tibialis anterior. MAGMA 2008;21(4):273–278. Crossref, Medline, Google Scholar
12. Deux JF, Malzy P, Paragios N, et al. Assessment of calf muscle contraction by diffusion tensor imaging. Eur Radiol 2008;18(10):2303–2310. Crossref, Medline, Google Scholar
13. Lansdown DA, Ding Z, Wadington M, Hornberger JL, Damon BM. Quantitative diffusion tensor MRI-based fiber tracking of human skeletal muscle. J Appl Physiol (1985) 2007;103(2):673–681. Crossref, Google Scholar
14. Okamoto Y, Kunimatsu A, Kono T, Kujiraoka Y, Sonobe J, Minami M. Gender differences in MR muscle tractography. Magn Reson Med Sci 2010;9(3):111–118. Crossref, Medline, Google Scholar
15. Galbán CJ, Maderwald S, Stock F, Ladd ME. Age-related changes in skeletal muscle as detected by diffusion tensor magnetic resonance imaging. J Gerontol A Biol Sci Med Sci 2007;62(4):453–458. Crossref, Medline, Google Scholar
16. Kaufman L, Kramer DM, Crooks LE, Ortendahl DA. Measuring signal-to-noise ratios in MR imaging. Radiology 1989;173(1):265–267. Link, Google Scholar
17. Froeling M, Nederveen AJ, Heijtel DF, et al. Diffusion-tensor MRI reveals the complex muscle architecture of the human forearm. J Magn Reson Imaging 2012;36(1):237–248. Crossref, Medline, Google Scholar
18. Froeling M, Strijkers GJ, Nollet F, de Visser M, Nicolay K, Nederveen AJ. Automated muscle fat segmentation in DTI data of post-polio patients based on parameter distirbutions [abstr]. In: Proceedings of the Twentieth Meeting of the International Society for Magnetic Resonance in Medicine. Berkeley, Calif: International Society for Magnetic Resonance in Medicine, 2012; 3264. Google Scholar
19. Koay CG, Chang LC, Carew JD, Pierpaoli C, Basser PJ. A unifying theoretical and algorithmic framework for least squares methods of estimation in diffusion tensor imaging. J Magn Reson 2006;182(1):115–125. Crossref, Medline, Google Scholar
20. Koay CG, Carew JD, Alexander AL, Basser PJ, Meyerand ME. Investigation of anomalous estimates of tensor-derived quantities in diffusion tensor imaging. Magn Reson Med 2006;55(4):930–936. Crossref, Medline, Google Scholar
21. Le Bihan D, Mangin JF, Poupon C, et al. Diffusion tensor imaging: concepts and applications. J Magn Reson Imaging 2001;13(4):534–546. Crossref, Medline, Google Scholar
22. Froeling M, Nederveen AJ, Nicolay K, Strijkers GJ. DTI of human skeletal muscle: the effects of diffusion encoding parameters, signal-to-noise ratio and T2 on tensor indices and fiber tracts. NMR Biomed 2013;26(11):1339–1352. Crossref, Medline, Google Scholar
23. Froeling M, Oudeman J, van den Berg S, et al. Reproducibility of diffusion tensor imaging in human forearm muscles at 3.0 T in a clinical setting. Magn Reson Med 2010;64(4):1182–1190. Crossref, Medline, Google Scholar
24. Heemskerk AM, Sinha TK, Wilson KJ, Ding Z, Damon BM. Repeatability of DTI-based skeletal muscle fiber tracking. NMR Biomed 2010;23(3):294–303. Crossref, Medline, Google Scholar
25. Damon BM. Effects of image noise in muscle diffusion tensor (DT)-MRI assessed using numerical simulations. Magn Reson Med 2008;60(4):934–944. Crossref, Medline, Google Scholar
26. Sinha S, Sinha U. Reproducibility analysis of diffusion tensor indices and fiber architecture of human calf muscles in vivo at 1.5 Tesla in neutral and plantarflexed ankle positions at rest. J Magn Reson Imaging 2011;34(1):107–119. Crossref, Medline, Google Scholar
27. Schenk P, Siebert T, Hiepe P, et al. Determination of three-dimensional muscle architectures: validation of the DTI-based fiber tractography method by manual digitization. J Anat 2013;223(1):61–68. Crossref, Medline, Google Scholar
28. Nakai R, Azuma T, Sudo M, Urayama S, Takizawa O, Tsutsumi S. MRI analysis of structural changes in skeletal muscles and surrounding tissues following long-term walking exercise with training equipment. J Appl Physiol (1985) 2008;105(3):958–963. Crossref, Google Scholar
29. Zaraiskaya T, Kumbhare D, Noseworthy MD. Diffusion tensor imaging in evaluation of human skeletal muscle injury. J Magn Reson Imaging 2006;24(2):402–408. Crossref, Medline, Google Scholar
30. Sigmund EE, Sui D, Ukpebor O, et al. Stimulated echo diffusion tensor imaging and SPAIR T2 -weighted imaging in chronic exertional compartment syndrome of the lower leg muscles. J Magn Reson Imaging 2013;38(5):1073–1082. Crossref, Medline, Google Scholar
31. Sigmund EE, Novikov DS, Sui D, et al. Time-dependent diffusion in skeletal muscle with the random permeable barrier model (RPBM): application to normal controls and chronic exertional compartment syndrome patients. NMR Biomed 2014;27(5):519–528. Crossref, Medline, Google Scholar

Article History

Received May 7, 2014; revision requested June 10; revision received July 7; accepted July 16; final version accepted July 24.
Published online: Oct 03 2014
Published in print: Feb 2015

Vol. 274, No. 2

Supplemental Material

Abbreviations

Abbreviations:
DTI	diffusion-tensor imaging
FA	fractional anisotropy

Metrics

Altmetric Score

PDF download