European Radiology

, Volume 29, Issue 5, pp 2598–2607 | Cite as

Diffusion tensor imaging of articular cartilage using a navigated radial imaging spin-echo diffusion (RAISED) sequence

  • Alejandra Duarte
  • Amparo Ruiz
  • Uran Ferizi
  • Jenny Bencardino
  • Steven B. Abramson
  • Jonathan Samuels
  • Svetlana Krasnokutsky-Samuels
  • José G. RayaEmail author



To validate a radial imaging spin-echo diffusion tensor (RAISED) sequence for high-resolution diffusion tensor imaging (DTI) of articular cartilage at 3 T.


The RAISED sequence implementation is described, including the used non-linear motion correction algorithm. The robustness to eddy currents was tested on phantoms, and accuracy of measurement was assessed with measurements of temperature-dependent diffusion of free water. Motion correction was validated by comparing RAISED with single-shot diffusion-weighted echo-planar imaging (EPI) measures. DTI was acquired in asymptomatic subjects (n = 6) and subjects with doubtful (Kellgren-Lawrence [KL] grade 1, n = 9) and mild (KL = 2, n = 9) symptomatic knee osteoarthritis (OA). MD and FA values without correction, and after all corrections, were calculated. A test-retest evaluation of the DTI acquisition on three asymptomatic and three OA subjects was also performed.


The root mean squared coefficient of variation of the global test-restest reproducibility was 3.54% for MD and 5.34% for FA. MD was significantly increased in both femoral condyles (7–9%) of KL 1 and in the medial (11–17%) and lateral (10–12%) compartments of KL 2 subjects. Averaged FA presented a trend of lower values with increasing KL grade, which was significant for the medial femoral condyle (-11%) of KL 1 and all three compartments in KL 2 subjects (-18 to -11%). Group differences in MD and FA were only significant after motion correction.


The RAISED sequence with the proposed reconstruction framework provides reproducible assessment of DTI parameters in vivo at 3 T and potentially the early stages of the disease in large regions of interest.

Key Points

• DTI of articular cartilage is feasible at 3T with a multi-shot RAISED sequence with non-linear motion correction.

• RAISED sequence allows estimation of the diffusion indices MD and FA with test-retest errors below 4% (MD) and 6% (FA).

• RAISED-based measurement of DTI of articular cartilage with non-linear motion correction holds potential to differentiate healthy from OA subjects.


Articular cartilage Diffusion tensor imaging Osteoarthritis Reproducibility of results Magnetic resonance imaging 



Coefficient of variation


Diffusion tensor imaging


Echo-planar imaging


Fractional anisotropy


Femoral trochlea


Kellgren-Lawrence score


Lateral femoral condyle


Lateral tibia


Mean diffusivity


Medial femoral condyle


Magnetic resonance imaging


Medial tibia








Radial imaging spin-echo diffusion tensor


Spin echo


Signal-to-noise ratio



This study has received funding from the (US) National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) of the National Institute of Health (NIH), Grant/Award Number R01AR067789.

Compliance with ethical standards

The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.


The scientific guarantor of this publication is José G Raya, PhD.

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 has significant statistical expertise.

No complex statistical methods were necessary for this paper.

Informed consent

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

Ethical approval

Institutional Review Board approval was obtained.


• prospective

• case-control study

• performed at one institution


  1. 1.
    Filidoro L, Dietrich O, Weber J et al (2005) High-resolution diffusion tensor imaging of human patellar cartilage: feasibility and preliminary findings. Magn Reson Med 53:993–998CrossRefGoogle Scholar
  2. 2.
    Meder R, de Visser SK, Bowden JC, Bostrom T, Pope JM (2006) Diffusion tensor imaging of articular cartilage as a measure of tissue microstructure. Osteoarthritis Cartilage 14:875–881CrossRefGoogle Scholar
  3. 3.
    de Visser SK, Bowden JC, Wentrup-Byrne E et al (2008) Anisotropy of collagen fibre alignment in bovine cartilage: comparison of polarised light microscopy and spatially resolved diffusion-tensor measurements. Osteoarthritis Cartilage 16:689–697CrossRefGoogle Scholar
  4. 4.
    Raya JG, Melkus G, Adam-Neumair S et al (2011) Change of diffusion tensor imaging parameters in articular cartilage with progressive proteoglycan extraction. Invest Radiol 46:401–409CrossRefGoogle Scholar
  5. 5.
    Raya JG, Melkus G, Adam-Neumair S et al (2013) Diffusion-tensor imaging of human articular cartilage specimens with early signs of cartilage damage. Radiology 266:831–841CrossRefGoogle Scholar
  6. 6.
    Deng X, Farley M, Nieminen MT, Gray M, Burstein D (2007) Diffusion tensor imaging of native and degenerated human articular cartilage. Magn Reson Imaging 25:168–171CrossRefGoogle Scholar
  7. 7.
    Ferizi U, Rossi I, Lee Y et al (2017) Diffusion tensor imaging of articular cartilage at 3T correlates with histology and biomechanics in a mechanical injury model. Magn Reson Med 78:69–78CrossRefGoogle Scholar
  8. 8.
    Guha A, Wyatt C, Karampinos DC, Nardo L, Link TM, Majumdar S (2015) Spatial variations in magnetic resonance-based diffusion of articular cartilage in knee osteoarthritis. Magn Reson Imaging 33:1051–1058CrossRefGoogle Scholar
  9. 9.
    Raya JG, Dettmann E, Notohamiprodjo M, Krasnokutsky S, Abramson S, Glaser C (2014) Feasibility of in vivo diffusion tensor imaging of articular cartilage with coverage of all cartilage regions. Eur Radiol 24(7):1700–1706CrossRefGoogle Scholar
  10. 10.
    Raya JG, Horng A, Dietrich O et al (2012) Articular cartilage: in vivo diffusion-tensor imaging. Radiology 262:550–559CrossRefGoogle Scholar
  11. 11.
    Berstein MA, King KF, Zhou XJ (2004) Chapter 14 − Basic pulse sequences. In: Berstein MA, King KF, Zhou XJ (eds) Handbook of MRI pulse sequences, 1st editionGoogle Scholar
  12. 12.
    Miller KL, Pauly JM (2003) Nonlinear phase correction for navigated diffusion imaging. Magn Reson Med 50:343–353CrossRefGoogle Scholar
  13. 13.
    Skare S, Hedehus M, Moseley ME, Li TQ (2000) Condition number as a measure of noise performance of diffusion tensor data acquisition schemes with MRI. J Magn Reson 147:340–352CrossRefGoogle Scholar
  14. 14.
    Mills R (1973) Self-diffusion in normal and heavy water. J Phys Chem 77:685–688CrossRefGoogle Scholar
  15. 15.
    Tofts PS, Lloyd D, Clark CA et al (2000) Test liquids for quantitative MRI measurements of self-diffusion coefficients in vivo. Magn Reson Med 43:368–374CrossRefGoogle Scholar
  16. 16.
    Gillen KT, Douglass DC, Hoch MJR (1972) Self-diffusion in liquid water to -31°C. J Chem Phys 57:5117–5119CrossRefGoogle Scholar
  17. 17.
    Harris KR, Woolf LA (1980) Pressure and temperature dependence of the self diffusion coefficient of water and oxygen-18 water. J Chem Soc Faraday Trans 76:377–385CrossRefGoogle Scholar
  18. 18.
    Dietrich O (2018) Diffusion coefficients of water. Available via http://dtrxde/od/diff/. Accessed 2018-07-08 2018
  19. 19.
    Bodammer N, Kaufmann J, Kanowski M, Tempelmann C (2004) Eddy current correction in diffusion-weighted imaging using pairs of images acquired with opposite diffusion gradient polarity. Magn Reson Med 51:188–193CrossRefGoogle Scholar
  20. 20.
    Neeman M, Freyer JP, Sillerud LO (1991) A simple method for obtaining cross-term-free images for diffusion anisotropy studies in NMR microimaging. Magn Reson Med 21:138–143CrossRefGoogle Scholar
  21. 21.
    König L, Groher M, Keil A, Glaser C, Reiser M, Navab N (2007) Semi-automatic segmentation of the patellar cartilage in MRI. Bildverarbeitung für die Medizin 17:404–408Google Scholar
  22. 22.
    Altman R, Asch E, Bloch D et al (1986) Development of criteria for the classification and reporting of osteoarthritis. Classification of osteoarthritis of the knee. Diagnostic and Therapeutic Criteria Committee of the American Rheumatism Association. Arthritis Rheum 29:1039–1049CrossRefGoogle Scholar
  23. 23.
    Guizar-Sicairos M (2008) Efficient subpixel image registration by cross-correlation Accessed 1 Jan 2016
  24. 24.
    Guizar-Sicairos M, Thurman ST, Fienup JR (2008) Efficient subpixel image registration algorithms. Opt Lett 33:156–158CrossRefGoogle Scholar
  25. 25.
    Ferizi U, Ruiz A, Rossi I, Bencardino J, Raya JG (2018) A robust diffusion tensor model for clinical applications of MRI to cartilage. Magn Reson Med 79:1157–1164CrossRefGoogle Scholar
  26. 26.
    Constantinides CD, Atalar E, McVeigh ER (1997) Signal-to-noise measurements in magnitude images from NMR phased arrays. Magn Reson Med 38:852–857CrossRefGoogle Scholar
  27. 27.
    Lin LI (1989) A concordance correlation coefficient to evaluate reproducibility. Biometrics 45:255–268CrossRefGoogle Scholar
  28. 28.
    Miller KL, Hargreaves BA, Gold GE, Pauly JM (2004) Steady-state diffusion-weighted imaging of in vivo knee cartilage. Magn Reson Med 5:394–398CrossRefGoogle Scholar
  29. 29.
    Bieri O, Ganter C, Scheffler K (2012) Quantitative in vivo diffusion imaging of cartilage using double echo steady-state free precession. Magn Reson Med 68:720–729CrossRefGoogle Scholar
  30. 30.
    Heule R, Ganter C, Bieri O (2014) Rapid estimation of cartilage T with reduced T sensitivity using double echo steady state imaging. Magn Reson Med 71(3):1137–1143.
  31. 31.
    Staroswiecki E, Granlund KL, Alley MT, Gold GE, Hargreaves BA (2012) Simultaneous estimation of T(2) and apparent diffusion coefficient in human articular cartilage in vivo with a modified three-dimensional double echo steady state (DESS) sequence at 3 T. Magn Reson Med 67:1086–1096CrossRefGoogle Scholar
  32. 32.
    Raya JG (2015) Techniques and applications of in vivo diffusion imaging of articular cartilage. J Magn Reson Imaging 41:1487–1504CrossRefGoogle Scholar
  33. 33.
    Azuma T, Nakai R, Takizawa O, Tsutsumi S (2009) In vivo structural analysis of articular cartilage using diffusion tensor magnetic resonance imaging. Magn Reson Imaging 27:1242–1248CrossRefGoogle Scholar
  34. 34.
    Glaser C, Mendlik T, Dinges J et al (2006) Global and regional reproducibility of T2 relaxation time measurements in human patellar cartilage. Magn Reson Med 56:527–534CrossRefGoogle Scholar
  35. 35.
    Raya JG, Horng A, Dietrich O et al (2009) Voxel-based reproducibility of T2 relaxation time in patellar cartilage at 1.5 T with a new validated 3D rigid registration algorithm. MAGMA 22:229–239Google Scholar
  36. 36.
    Madelin G, Babb JS, Xia D, Chang G, Jerschow A, Regatte RR (2012) Reproducibility and repeatability of quantitative sodium magnetic resonance imaging in vivo in articular cartilage at 3 T and 7 T. Magn Reson Med 68:841–849CrossRefGoogle Scholar
  37. 37.
    Multanen J, Rauvala E, Lammentausta E et al (2009) Reproducibility of imaging human knee cartilage by delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) at 1.5 Tesla. Osteoarthritis Cartilage 17:559–564CrossRefGoogle Scholar
  38. 38.
    Jordan CD, McWalter EJ, Monu UD et al (2014) Variability of CubeQuant T1rho, quantitative DESS T2, and cones sodium MRI in knee cartilage. Osteoarthritis Cartilage 22:1559–1567CrossRefGoogle Scholar
  39. 39.
    Gupta R, Virayavanich W, Kuo D et al (2014) MR T(1)rho quantification of cartilage focal lesions in acutely injured knees: correlation with arthroscopic evaluation. Magn Reson Imaging 32:1290–1296CrossRefGoogle Scholar
  40. 40.
    Xu J, Xie G, Di Y, Bai M, Zhao X (2011) Value of T2-mapping and DWI in the diagnosis of early knee cartilage injury. J Radiol Case Rep 5:13–18Google Scholar

Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  1. 1.Center for Biomedical Imaging, Department of RadiologyNew York University Langone HealthNew YorkUSA
  2. 2.Division of Rheumatology, Department of MedicineNew York University Langone HealthNew YorkUSA

Personalised recommendations