Pediatric Radiology

, Volume 44, Issue 5, pp 576–586 | Cite as

Quantitative versus semiquantitative MR imaging of cartilage in blood-induced arthritic ankles: preliminary findings

  • Andrea S. DoriaEmail author
  • Ningning Zhang
  • Bjorn Lundin
  • Pamela Hilliard
  • Carina Man
  • Ruth Weiss
  • Gary Detzler
  • Victor Blanchette
  • Rahim Moineddin
  • Felix Eckstein
  • Marshall S. Sussman
Original Article



Recent advances in hemophilia prophylaxis have raised the need for accurate noninvasive methods for assessment of early cartilage damage in maturing joints to guide initiation of prophylaxis. Such methods can either be semiquantitative or quantitative. Whereas semiquantitative scores are less time-consuming to be performed than quantitative methods, they are prone to subjective interpretation.


To test the feasibility of a manual segmentation and a quantitative methodology for cross-sectional evaluation of articular cartilage status in growing ankles of children with blood-induced arthritis, as compared with a semiquantitative scoring system and clinical-radiographic constructs.

Materials and methods

Twelve boys, 11 with hemophilia (A, n = 9; B, n = 2) and 1 with von Willebrand disease (median age: 13; range: 6–17), underwent physical examination and MRI at 1.5 T. Two radiologists semiquantitatively scored the MRIs for cartilage pathology (surface erosions, cartilage loss) with blinding to clinical information. An experienced operator applied a validated quantitative 3-D MRI method to determine the percentage area of denuded bone (dAB) and the cartilage thickness (ThCtAB) in the joints’ MRIs. Quantitative and semiquantitative MRI methods and clinical-radiographic constructs (Hemophilia Joint Health Score [HJHS], Pettersson radiograph scores) were compared.


Moderate correlations were noted between erosions and dAB (r = 0.62, P = 0.03) in the talus but not in the distal tibia (P > 0.05). Whereas substantial to high correlations (r range: 0.70–0.94, P < 0.05) were observed between erosions, cartilage loss, HJHS and Pettersson scores both at the distal tibia and talus levels, moderate/borderline substantial (r range: 0.55–0.61, P < 0.05) correlations were noted between dAB/ThCtAB and clinical-radiographic constructs.


Whereas the semiquantitative method of assessing cartilage status is closely associated with clinical-radiographic scores in cross-sectional studies of blood-induced arthropathy, quantitative measures provide independent information and are therefore less applicable for that research design.


Blood-induced arthritis Hemophilia Blood-induced arthropathy Children Ankles Cartilage Magnetic resonance imaging 



This study was supported by a salary award given to Dr. Andrea S. Doria through the Canadian Child Health Clinician-Scientist program. This study was funded by Bayer Healthcare Pharmaceuticals, Canada. We thank Susanne Maschek from Paracelsus Medical University, Salzburg, Austria, & Chondrometrics GmbH, Ainring, Germany, for segmentation of the MR images for the purpose of quantitative measurement of cartilage morphology.

A scientific paper on the results of this study was presented at the 2012 Society of Pediatric Radiology meeting, San Francisco, CA.

Conflict of interest



  1. 1.
    Roy S, Ghadially FN (1966) Pathology of experimental haemarthrosis. Ann Rheum Dis 25:402–415PubMedCentralPubMedGoogle Scholar
  2. 2.
    Mainardi CL, Levine PH, Werb Z et al (1978) Proliferative synovitis in hemophilia: biochemical and morphologic observations. Arthritis Rheum 21:137–144PubMedCrossRefGoogle Scholar
  3. 3.
    Stein H, Duthie RB (1981) The pathogenesis of chronic haemophilic arthropathy. J Bone Joint Surg Br 63B:601–609PubMedGoogle Scholar
  4. 4.
    Roosendaal G, Vianen ME, van den Berg HM et al (1997) Cartilage damage as a result of hemarthrosis in a human in vitro model. J Rheumatol 24:1350–1354PubMedGoogle Scholar
  5. 5.
    Roosendaal G, Vianen ME, Marx JJ et al (1999) Blood-induced joint damage: a human in vitro study. Arthritis Rheum 42:1025–1032PubMedCrossRefGoogle Scholar
  6. 6.
    Roosendaal G, Lafeber FP (2006) Pathogenesis of haemophilic arthropathy. Haemophilia 12:117–121PubMedCrossRefGoogle Scholar
  7. 7.
    Doria AS (2010) State-of-the-art imaging techniques for the evaluation of haemophilic arthropathy: present and future. Haemophilia 16:107–114PubMedCrossRefGoogle Scholar
  8. 8.
    Peterfy CG, van Dijke CF, Janzen DL et al (1994) Quantification of articular cartilage in the knee with pulsed saturation transfer subtraction and fat-suppressed MR imaging: optimization and validation. Radiology 192:485–491PubMedGoogle Scholar
  9. 9.
    Burgkart R, Glaser C, Hyhlik-Dürr A et al (2001) Magnetic resonance imaging-based assessment of cartilage loss in severe osteoarthritis: accuracy, precision, and diagnostic value. Arthritis Rheum 44:2072–2077PubMedCrossRefGoogle Scholar
  10. 10.
    Stammberger T, Eckstein F, Englmeier KH et al (1999) Determination of 3D cartilage thickness data from MR imaging: computational method and reproducibility in the living. Magn Reson Med 41:529–536PubMedCrossRefGoogle Scholar
  11. 11.
    Cohen ZA, McCarthy DM, Kwak SD et al (1999) Knee cartilage topography, thickness, and contact areas from MRI: in-vitro calibration and in-vivo measurements. Osteoarthr Cartil 7:95–109PubMedCrossRefGoogle Scholar
  12. 12.
    Graichen H, Eisenhart-Rothe R, Vogl T et al (2004) Quantitative assessment of cartilage status in osteoarthritis by quantitative magnetic resonance imaging: technical validation for use in analysis of cartilage volume and further morphologic parameters. Arthritis Rheum 50:811–816PubMedCrossRefGoogle Scholar
  13. 13.
    Cicuttini F, Forbes A, Morris K et al (1999) Gender differences in knee cartilage volume as measured by magnetic resonance imaging. Osteoarthr Cartil 7:265–271PubMedCrossRefGoogle Scholar
  14. 14.
    Al-Ali D, Graichen H, Faber S et al (2002) Quantitative cartilage imaging of the human hind foot: precision and inter-subject variability. J Orthop Res 20:249–256PubMedCrossRefGoogle Scholar
  15. 15.
    Reichenbach S, Yang M, Eckstein F et al (2010) Does cartilage volume or thickness distinguish knees with and without mild radiographic osteoarthritis? The Framingham Study. Ann Rheum Dis 69:143–149PubMedCentralPubMedCrossRefGoogle Scholar
  16. 16.
    Sharma L, Eckstein F, Song J et al (2008) Relationship of meniscal damage, meniscal extrusion, malalignment, and joint laxity to subsequent cartilage loss in osteoarthritic knees. Arthritis Rheum 58:1716–1726PubMedCrossRefGoogle Scholar
  17. 17.
    Graichen H, Springer V, Flaman T et al (2000) Validation of high-resolution water-excitation magnetic resonance imaging for quantitative assessment of thin cartilage layers. Osteoarthr Cartil 8:106–114PubMedCrossRefGoogle Scholar
  18. 18.
    Lundin B, Manco-Johnson ML, Ignas DM et al (2012) The International Prophylaxis Study Group. An MRI scale for assessment of haemophilic arthropathy from the International Prophylaxis Study Group. Haemophilia 18:962–970PubMedCrossRefGoogle Scholar
  19. 19.
    Buck RJ, Wyman BT, Le Graverand MP et al (2010) An efficient subset of morphological measures for articular cartilage in the healthy and diseased human knee. Magn Reson Med 63:680–690PubMedCrossRefGoogle Scholar
  20. 20.
    Intema F, Van Roermund PM, Marijnissen ACA et al (2011) Tissue structure modification in knee osteoarthritis by use of joint distraction: an open 1-year pilot study. Ann Rheum Dis 70:1441–1446PubMedCentralPubMedCrossRefGoogle Scholar
  21. 21.
    Feldman BM, Funk SM, Bergstrom BM et al (2011) Validation of a new pediatric joint scoring system from the international hemophilia prophylaxis study group: validity of the hemophilia joint health score (HJHS). Arthritis Care Res 63:223–230CrossRefGoogle Scholar
  22. 22.
    Pettersson H, Ahlberg A, Nilsson IM (1980) A radiologic classification of hemophilic arthropathy. Clin Orthop 149:153–159PubMedGoogle Scholar
  23. 23.
    Nuss R, Kilcoyne RF (2003) A magnetic resonance imaging atlas of hemophilic arthropathy, 1st edn. Professional Publishing Group Ltd., New YorkGoogle Scholar
  24. 24.
    Eckstein F, Hudelmaier M, Wirth W et al (2006) Double echo steady state magnetic resonance imaging of knee articular cartilage at 3 T: a pilot study for the Osteoarthritis Initiative. Ann Rheum Dis 65:433–441PubMedCentralPubMedCrossRefGoogle Scholar
  25. 25.
    Wirth W, Eckstein F (2008) A technique for regional analysis of femorotibial cartilage thickness based on quantitative magnetic resonance imaging. IEEE Trans Med Imaging 27:737–744PubMedCrossRefGoogle Scholar
  26. 26.
    Hohe J, Ateshian G, Reiser M et al (2002) Surface size, curvature analysis, and assessment of knee joint incongruity with MRI in vivo. Magn Reson Med 47:554–561PubMedCrossRefGoogle Scholar
  27. 27.
    Moisio KC, Eckstein F, Song J et al (2008) The relationship of denuded subchondral bone area to knee pain severity and incident frequent knee pain. Osteoarthritis Cartilage 16(Suppl 4):S31 (abstract)Google Scholar
  28. 28.
    Frobell RB, Wirth W, Nevitt M et al (2010) Presence, location, type and size of denuded areas of subchondral bone in the knee as a function of radiographic stage of OA - data from the OA initiative. Osteoarthr Cartil 18:668–676PubMedCentralPubMedCrossRefGoogle Scholar
  29. 29.
    Eckstein F, Winzheimer M, Hohe J et al (2001) Interindividual variability and correlation among morphological parameters of knee joint cartilage plates: analysis with three-dimensional MR imaging. Osteoarthr Cartil 9:101–111PubMedCrossRefGoogle Scholar
  30. 30.
    Altman DG (1991) Practical statistics for medical research. Chapman and Hall, London, pp 404–408Google Scholar
  31. 31.
  32. 32.
    Portney LG, Watkins MP (2000) Validity of measurements. In: Portney LG, Watkins MP (eds) Foundations of clinical research. Applications to practice, 2nd edn. Prentice-Hall Health, Upper Saddle River, pp 87–92Google Scholar
  33. 33.
    Hunter DJ, Bowes MA, Eaton XK et al (2010) Can cartilage loss be detected in knee osteoarthritis (OA) patients with 3-6 months’ observation using advanced image analysis of 3 T MRI? Osteoarthr Cartil 18:677–683PubMedCrossRefGoogle Scholar
  34. 34.
    Eckstein F, McCulloch CE, Lynch JA et al (2012) For the OA Initiative Investigators Group. How do short-term rates of femorotibial cartilage change compare to long-term changes? Four year follow-up data from the osteoarthritis initiative. Osteoarthr Cartil 20:1250–1257PubMedCentralPubMedCrossRefGoogle Scholar
  35. 35.
    Roemer FW, Eckstein F, Guermazi A (2009) Magnetic resonance imaging-based semiquantitative and quantitative assessment in osteoarthritis. Rheum Dis Clin N Am 35:521–555CrossRefGoogle Scholar
  36. 36.
    Eckstein F, Ateshian G, Burgkart R et al (2006) Proposal for a nomenclature for magnetic resonance imaging based measures of articular cartilage in osteoarthritis. Osteoarthr Cartil 14:974–983PubMedCrossRefGoogle Scholar
  37. 37.
    Hilliard P, Blanchette VS, Doria AS et al (2008) The Hemophilia Joint Health Score (HJHS) correlates highly with radiographic damage (Abstract). Proceedings of the XXVIII International Congress of the World Federation of Hemophilia, Istanbul, TurkeyGoogle Scholar
  38. 38.
    Spannow AH, Stenboeg E, Pfeiffer-Jensen M et al (2011) Ultrasound and MRI measurements of joint cartilage in healthy children: a validation study. Ultraschall Med 32:S110–S116PubMedCrossRefGoogle Scholar
  39. 39.
    Keshava S, Gibikote S, Mohanta A et al (2013) Ultrasound and MRI of growing joints in healthy boys: correlation with ex-vivo phantom measurements (Abstract). Proceedings of the 56th Annual Meeting of the Society for Pediatric Radiology, San Antonio, TXGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Andrea S. Doria
    • 1
    • 2
    Email author
  • Ningning Zhang
    • 3
  • Bjorn Lundin
    • 4
  • Pamela Hilliard
    • 5
  • Carina Man
    • 1
  • Ruth Weiss
    • 1
  • Gary Detzler
    • 1
  • Victor Blanchette
    • 6
  • Rahim Moineddin
    • 7
  • Felix Eckstein
    • 8
    • 9
  • Marshall S. Sussman
    • 2
    • 10
  1. 1.Department of Diagnostic ImagingThe Hospital for Sick ChildrenTorontoCanada
  2. 2.Department of Medical ImagingUniversity of TorontoTorontoCanada
  3. 3.Department of RadiologyChildren’s HospitalBeijingChina
  4. 4.Center for Medical Imaging and PhysiologySkåne University Hospital and Lund University, University Hospital of LundLundSweden
  5. 5.Department of Rehabilitation ServicesThe Hospital for Sick ChildrenTorontoCanada
  6. 6.Department of HematologyThe Hospital for Sick ChildrenTorontoCanada
  7. 7.Department of Public HealthFamily and Community MedicineTorontoCanada
  8. 8.Institute of Anatomy and Musculoskeletal ResearchParacelsus Medical UniversitySalzburgAustria
  9. 9.Chondrometrics GmbHAinringGermany
  10. 10.Department of Medical ImagingUniversity Health NetworkTorontoCanada

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