Skip to main content

Advertisement

Log in

Diffusion tensor imaging of the human thigh: consideration of DTI-based fiber tracking stop criteria

  • Research Article
  • Published:
Magnetic Resonance Materials in Physics, Biology and Medicine Aims and scope Submit manuscript

Abstract

Objectives

To consider the tract-based analysis of DTI parameters in human muscle by assessing different fiber tracking stop criteria settings on diffusion parameters.

Materials and methods

30 healthy volunteers underwent a 3 T MRI. Diffusion-weighted images were acquired to perform DTI and fiber tracking analysis for six thigh muscles. Whole thigh muscles were evaluated by fiber tractography using different fiber tracking stop parameters [FA (0.01–0.15) to (0.4–0.99); angle 10°–30°, step size 0.75 mm, 1.5 mm, 3 mm]. Diffusion and tractography-derived parameters per stop criterion were compared using a repeated measure ANOVA including Bonferroni-corrected post hoc tests.

Results

We found significant differences in all examined diffusion parameters between different stop criteria (main effect p < 0.001). We showed different influence of tracking parameters on diffusion parameters in examined muscles (main effect p ≤ 0.001).

Conclusions

Statistically significant differences in fiber tracking results using different stop criteria were shown. Fiber tracking stop criteria do have an important influence on study results and should be considered in the development of study protocols and comparison of studies. We recommend a FA minimum of 0.10 and a step size lower than voxel size, e.g., a half with a constant ratio between step size and angle of 10°/mm.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Oudeman J, Nederveen AJ, Strijkers GJ et al (2016) Techniques and applications of skeletal muscle diffusion tensor imaging: a review. J Magn Reson Imaging 43(4):773–788. https://doi.org/10.1002/jmri.25016

    Article  PubMed  Google Scholar 

  2. Berry DB, Regner B, Galinsky V et al (2018) Relationships between tissue microstructure and the diffusion tensor in simulated skeletal muscle. Magn Reson Med 80(1):317–329. https://doi.org/10.1002/mrm.26993

    Article  PubMed  Google Scholar 

  3. Ha D-H, Choi S, Kang E-J et al (2015) Diffusion tensor imaging and T2 mapping in early denervated skeletal muscle in rats. J Magn Reson Imaging 42(3):617–623. https://doi.org/10.1002/jmri.24818

    Article  PubMed  Google Scholar 

  4. Ai T, Yu K, Gao L et al (2014) Diffusion tensor imaging in evaluation of thigh muscles in patients with polymyositis and dermatomyositis. Br J Radiol 87(1043):20140261. https://doi.org/10.1259/bjr.20140261

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Edalati M, Hastings MK, Sorensen CJ et al (2018) Diffusion tensor imaging of the calf muscles in subjects with and without diabetes mellitus. J Magn Reson Imaging. https://doi.org/10.1002/jmri.26286

    Article  PubMed  PubMed Central  Google Scholar 

  6. Giraudo C, Motyka S, Weber M et al (2018) Normalized STEAM-based diffusion tensor imaging provides a robust assessment of muscle tears in football players: preliminary results of a new approach to evaluate muscle injuries. Eur Radiol 28(7):2882–2889. https://doi.org/10.1007/s00330-017-5218-9

    Article  PubMed  PubMed Central  Google Scholar 

  7. Zaraiskaya T, Kumbhare D, Noseworthy MD (2006) Diffusion tensor imaging in evaluation of human skeletal muscle injury. J Magn Reson Imaging 24(2):402–408. https://doi.org/10.1002/jmri.20651

    Article  PubMed  Google Scholar 

  8. Hooijmans MT, Damon BM, Froeling M et al (2015) Evaluation of skeletal muscle DTI in patients with duchenne muscular dystrophy. NMR Biomed 28(11):1589–1597. https://doi.org/10.1002/nbm.3427

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Li GD, Liang YY, Xu P et al (2016) Diffusion-tensor imaging of thigh muscles in duchenne muscular dystrophy: correlation of apparent diffusion coefficient and fractional anisotropy values with fatty infiltration. AJR Am J Roentgenol 206(4):867–870. https://doi.org/10.2214/AJR.15.15028

    Article  PubMed  Google Scholar 

  10. Froeling M, Oudeman J, Strijkers GJ et al (2015) Muscle changes detected with diffusion-tensor imaging after long-distance running. Radiology 274(2):548–562. https://doi.org/10.1148/radiol.14140702

    Article  PubMed  Google Scholar 

  11. Sigmund EE, Baete SH, Luo T et al (2018) MRI assessment of the thigh musculature in dermatomyositis and healthy subjects using diffusion tensor imaging, intravoxel incoherent motion and dynamic DTI. Eur Radiol. https://doi.org/10.1007/s00330-018-5458-3

    Article  PubMed  Google Scholar 

  12. Arrigoni F, de Luca A, Velardo D et al (2018) Multiparametric quantitative MRI assessment of thigh muscles in limb-girdle muscular dystrophy 2A and 2B. Muscle Nerve 58(4):550–558. https://doi.org/10.1002/mus.26189

    Article  PubMed  Google Scholar 

  13. Froeling M, Nederveen AJ, Nicolay K et al (2013) 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 26(11):1339–1352. https://doi.org/10.1002/nbm.2959

    Article  PubMed  Google Scholar 

  14. Damon BM, Ding Z, Anderson AW et al (2002) Validation of diffusion tensor MRI-based muscle fiber tracking. Magn Reson Med 48(1):97–104. https://doi.org/10.1002/mrm.10198

    Article  PubMed  Google Scholar 

  15. Budzik J-F, Balbi V, Verclytte S et al (2014) Diffusion tensor imaging in musculoskeletal disorders. Radiographics 34(3):E56–72. https://doi.org/10.1148/rg.343125062

    Article  PubMed  Google Scholar 

  16. Heemskerk AM, Sinha TK, Wilson KJ et al (2009) Quantitative assessment of DTI-based muscle fiber tracking and optimal tracking parameters. Magn Reson Med 61(2):467–472. https://doi.org/10.1002/mrm.21819

    Article  PubMed  PubMed Central  Google Scholar 

  17. Damon BM, Buck AKW, Ding Z (2011) Diffusion-tensor MRI based skeletal muscle fiber tracking. Imaging Med 3(6):675–687. https://doi.org/10.2217/iim.11.60

    Article  PubMed  PubMed Central  Google Scholar 

  18. Budzik JF, Le Thuc V, Demondion X et al (2007) In vivo MR tractography of thigh muscles using diffusion imaging: initial results. Eur Radiol 17(12):3079–3085. https://doi.org/10.1007/s00330-007-0713-z

    Article  CAS  PubMed  Google Scholar 

  19. Schlaffke L, Rehmann R, Froeling M et al (2017) Diffusion tensor imaging of the human calf: variation of inter- and intramuscle-specific diffusion parameters. J Magn Reson Imaging 46(4):1137–1148. https://doi.org/10.1002/jmri.25650

    Article  PubMed  Google Scholar 

  20. Tax CMW, Otte WM, Viergever MA et al (2015) REKINDLE: robust extraction of kurtosis INDices with linear estimation. Magn Reson Med 73(2):794–808. https://doi.org/10.1002/mrm.25165

    Article  PubMed  Google Scholar 

  21. Leemans A, Jeurissen B, Sijbers J, Jones DK (2009) ExploreDTI: a graphical toolbox for processing, analyzing, and visualizing diffusion MR data. Proc Int Soc Mag Reson Med 17:3537

    Google Scholar 

  22. Froeling M, Tax CMW, Vos SB et al (2017) "MASSIVE" brain dataset: multiple acquisitions for standardization of structural imaging validation and evaluation. Magn Reson Med 77(5):1797–1809. https://doi.org/10.1002/mrm.26259

    Article  CAS  PubMed  Google Scholar 

  23. Basser PJ, Pajevic S, Pierpaoli C et al (2000) In vivo fiber tractography using DT-MRI data. Magn Reson Med 44(4):625–632. https://doi.org/10.1002/1522-2594(200010)44:4%3c625:AID-MRM17%3e3.0.CO;2-O

    Article  CAS  PubMed  Google Scholar 

  24. Leemans A, Jones DK (2009) The B-matrix must be rotated when correcting for subject motion in DTI data. Magn Reson Med 61(6):1336–1349. https://doi.org/10.1002/mrm.21890

    Article  PubMed  Google Scholar 

  25. Giraudo C, Motyka S, Weber M et al (2018) Diffusion tensor imaging of healthy skeletal muscles: a comparison between 7 T and 3 T. Investig Radiol. https://doi.org/10.1097/RLI.0000000000000508

    Article  Google Scholar 

  26. Mazzoli V, Oudeman J, Nicolay K et al (2016) Assessment of passive muscle elongation using diffusion tensor MRI: correlation between fiber length and diffusion coefficients. NMR Biomed 29(12):1813–1824. https://doi.org/10.1002/nbm.3661

    Article  CAS  PubMed  Google Scholar 

  27. Ponrartana S, Ramos-Platt L, Wren TAL et al (2015) Effectiveness of diffusion tensor imaging in assessing disease severity in Duchenne muscular dystrophy: preliminary study. Pediatr Radiol 45(4):582–589. https://doi.org/10.1007/s00247-014-3187-6

    Article  PubMed  Google Scholar 

  28. Froeling M, Oudeman J, van den Berg S et al (2010) Reproducibility of diffusion tensor imaging in human forearm muscles at 3.0 T in a clinical setting. Magn Reson Med 64(4):1182–1190. https://doi.org/10.1002/mrm.22477

    Article  PubMed  Google Scholar 

  29. Kälin PS, Huber FA, Hamie QM et al (2018) Quantitative MRI of visually intact rotator cuff muscles by multiecho dixon-based fat quantification and diffusion tensor imaging. J Magn Reson Imaging. https://doi.org/10.1002/jmri.26223

    Article  PubMed  Google Scholar 

  30. Zijta FM, Lakeman MME, Froeling M et al (2012) Evaluation of the female pelvic floor in pelvic organ prolapse using 3.0-Tesla diffusion tensor imaging and fibre tractography. Eur Radiol 22(12):2806–2813. https://doi.org/10.1007/s00330-012-2548-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Zifan A, Reisert M, Sinha S et al (2018) Connectivity of the superficial muscles of the human perineum: a diffusion tensor imaging-based global tractography study. Sci Rep 8(1):17867. https://doi.org/10.1038/s41598-018-36099-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Rousset P, Delmas V, Buy J-N et al (2012) In vivo visualization of the levator ani muscle subdivisions using MR fiber tractography with diffusion tensor imaging. J Anat 221(3):221–228. https://doi.org/10.1111/j.1469-7580.2012.01538.x

    Article  PubMed  PubMed Central  Google Scholar 

  33. Gaige TA, Benner T, Wang R et al (2007) Three dimensional myoarchitecture of the human tongue determined in vivo by diffusion tensor imaging with tractography. J Magn Reson Imaging 26(3):654–661. https://doi.org/10.1002/jmri.21022

    Article  PubMed  Google Scholar 

  34. Sigmund EE, Novikov DS, Sui D et al (2014) 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 27(5):519–528. https://doi.org/10.1002/nbm.3087

    Article  PubMed  PubMed Central  Google Scholar 

  35. Kermarrec E, Budzik J-F, Khalil C et al (2010) In vivo diffusion tensor imaging and tractography of human thigh muscles in healthy subjects. AJR Am J Roentgenol 195(5):W352–W356. https://doi.org/10.2214/AJR.09.3368

    Article  PubMed  Google Scholar 

  36. Fouré A, Ogier AC, Le Troter A et al (2018) Diffusion properties and 3d architecture of human lower leg muscles assessed with ultra-high-field-strength diffusion-tensor MR imaging and tractography: reproducibility and sensitivity to sex difference and intramuscular variability. Radiology 287(2):592–607. https://doi.org/10.1148/radiol.2017171330

    Article  PubMed  Google Scholar 

  37. Kan JH, Heemskerk AM, Ding Z et al (2009) DTI-based muscle fiber tracking of the quadriceps mechanism in lateral patellar dislocation. J Magn Reson Imaging 29(3):663–670. https://doi.org/10.1002/jmri.21687

    Article  PubMed  PubMed Central  Google Scholar 

  38. Côté M-A, Girard G, Boré A et al (2013) Tractometer: towards validation of tractography pipelines. Med Image Anal 17(7):844–857. https://doi.org/10.1016/j.media.2013.03.009

    Article  PubMed  Google Scholar 

  39. Tournier J-D, Calamante F, Connelly A (2012) MRtrix: diffusion tractography in crossing fiber regions. Int J Imaging Syst Technol 22(1):53–66. https://doi.org/10.1002/ima.22005

    Article  Google Scholar 

  40. Jeon T, Fung MM, Koch KM et al (2018) Peripheral nerve diffusion tensor imaging: overview, pitfalls, and future directions. J Magn Reson Imaging 47(5):1171–1189. https://doi.org/10.1002/jmri.25876

    Article  PubMed  Google Scholar 

  41. Kronlage M, Schwehr V, Schwarz D et al (2018) Peripheral nerve diffusion tensor imaging (DTI): normal values and demographic determinants in a cohort of 60 healthy individuals. Eur Radiol 28(5):1801–1808. https://doi.org/10.1007/s00330-017-5134-z

    Article  PubMed  Google Scholar 

  42. Manenti G, Capuani S, Fanucci E et al (2013) Diffusion tensor imaging and magnetic resonance spectroscopy assessment of cancellous bone quality in femoral neck of healthy, osteopenic and osteoporotic subjects at 3T: preliminary experience. Bone 55(1):7–15. https://doi.org/10.1016/j.bone.2013.03.004

    Article  PubMed  Google Scholar 

  43. Damon BM, Froeling M, Buck AKW et al (2017) Skeletal muscle diffusion tensor-MRI fiber tracking: rationale, data acquisition and analysis methods, applications and future directions. NMR Biomed. https://doi.org/10.1002/nbm.3563

    Article  PubMed  Google Scholar 

  44. Wickiewitz TL (1983) Architecture of human lower limb. Clin Orthop Relat Res 173:276–283

    Google Scholar 

  45. Lieber RL, Fridén J (2001) Clinical significance of skeletal muscle architecture. Clin Orthop Relat Res 383:140–151. https://doi.org/10.1097/00003086-200102000-00016

    Article  Google Scholar 

  46. Lieber RL, Fridén J (2000) Functional and clinical significance of skeletal muscle architecture. Muscle Nerve 23(11):1647–1666. https://doi.org/10.1002/1097-4598(200011)23:11%3c1647:AID-MUS1%3e3.0.CO;2-M

    Article  CAS  PubMed  Google Scholar 

  47. Okamoto Y (2008) Fractional anisotropy values of calf muscles in normative state after exercise: preliminary results. Magn Reson Med 7(3):157–162

    Google Scholar 

  48. Charles JP, Moon C, Anderst WJ (2019) Determining subject-specific lower-limb muscle architecture data for musculoskeletal models using diffusion tensor imaging. ASME J Biomech Eng 141(6):060905. https://doi.org/10.1115/1.4040946

    Google Scholar 

  49. Oudeman J, Mazzoli V, Marra MA et al (2016) A novel diffusion-tensor MRI approach for skeletal muscle fascicle length measurements. Physiol Rep. https://doi.org/10.14814/phy2.13012

    Article  PubMed  PubMed Central  Google Scholar 

  50. Bolsterlee B, D'Souza A, Herbert RD (2019) Reliability and robustness of muscle architecture measurements obtained using diffusion tensor imaging with anatomically constrained tractography. J Biomech 86:71–78. https://doi.org/10.1016/j.jbiomech.2019.01.043

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We thank Philips Germany for continuous scientific support and specifically Dr. Burkhard Mädler for valuable discussion. JF, LS and MT received funding from the Deutsche Forschungsgemeinschaft Project number 122679504 SFB874 (TP-A1 to MT and JF, TP-A5 to LS).

Author information

Authors and Affiliations

Authors

Contributions

JF: Study conception and design, acquisition of data, analysis and interpretation of data, drafting of manuscript. RR: Acquisition of data, critical revision. MF: Analysis and interpretation of data, critical revision. MV: Critical revision. MT: Study conception and design, critical revision. LS: Study conception and design, acquisition of data, analysis and interpretation of data, critical revision.

Corresponding author

Correspondence to Johannes Forsting.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

Study protocol was approved by local ethics committee.

Informed consent

Voluntary informed consent was obtained from all participants.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (EPS 23,188 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Forsting, J., Rehmann, R., Froeling, M. et al. Diffusion tensor imaging of the human thigh: consideration of DTI-based fiber tracking stop criteria. Magn Reson Mater Phy 33, 343–355 (2020). https://doi.org/10.1007/s10334-019-00791-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10334-019-00791-x

Keywords

Navigation