Skip to main content
SpringerLink
Log in

Comparative analysis of the diagnostic values of T2 mapping and diffusion-weighted imaging for sacroiliitis in ankylosing spondylitis

  • Scientific Article
  • Published:
Skeletal Radiology Aims and scope Submit manuscript

Abstract

Objective

To investigate the diagnostic values of T2 mapping and diffusion-weighted imaging (DWI) for active sacroiliitis in ankylosing spondylitis (AS) and to evaluate the correlations of T2 and ADC values with Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and Spondyloarthritis Research Consortium of Canada (SPARCC) scores.

Methods

A total of 77 AS patients with sacroiliitis and 45 healthy controls were enrolled. All patients were scanned by standard magnetic resonance imaging longitudinal relaxation time (T1)-weighted imaging (T1WI), fat-saturated T2-weighted imaging (FS-T2WI)] and DWI, and T2 mapping of the sacroiliac joints. According to whether subchondral bone marrow edema was present in the FS-T2WI sequence, the 77 patients were divided into an active group (41 cases) and an inactive group (36 cases). The T2 and apparent diffusion coefficient (ADC) values of the subchondral bone marrow were measured in the active group, the inactive group, and the healthy control group. The average T2 and ADC values were compared among the three groups. Receiver operating characteristic (ROC) curves were used to analyze the diagnostic efficacy of T2 and ADC values for sacroiliitis. The correlations of T2 and ADC values with the BASDAI score and the SPARCC score were analyzed.

Results

The T2 and ADC values in the active group were higher than those in the inactive group, while that in the inactive group were significantly higher than those in the healthy control group (p < 0.0001). The T2 and ADC values of the AS patients were positively correlated with BASDAI scores, and the correlation coefficients (r) were 0.786 (p < 0.0001) and 0.842 (p < 0.0001), respectively. The areas under the ROC curves (AUCs) of T2 and ADC values between the active and inactive groups, the active group and the healthy control group, and the inactive group and the healthy control group were 0.889 (95% CI, 0.80–0.95) and 0.917 (95% CI, 0.83–0.97), 0.982 (95% CI, 0.93–1.00) and 0.984 (95% CI, 0.93–1.00), and 0.628 (95% CI, 0.51–0.73) and 0.871 (95% CI, 0.78–0.94), respectively. The T2 and ADC values of the AS patients in the active group were positively correlated with SPARCC scores, and the correlation coefficients (r) were 0.757 (p < 0.0001) and 0.764 (p < 0.0001), respectively.

Conclusion

T2 and ADC values can be used to quantitatively assess the activity of AS, and the efficacy of the ADC value in the diagnosis of AS was higher than that of the T2 value.

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

Access this article

Log in via an institution

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. Jacobson JA, Girish G, Jiang YB, et al. Radiographic evaluation of arthritis: inflammatory conditions. Radiology. 2008;248(2):378–89.

    Article  Google Scholar 

  2. Poddubnyy D, Rudwaleit M. Early spondyloarthritis. Rheum Dis Clin N Am. 2012;38(2):387–403.

    Article  Google Scholar 

  3. Gaspersic N, Sersa I, Jevtic V, et al. Monitoring ankylosing spondylitis therapy by dynamic contrast-enhanced and diffusion-weighted magnetic resonance imaging. Skelet Radiol. 2008;37(2):123–31.

    Article  Google Scholar 

  4. Lukas C, Landewé R, Sieper J, et al. Development of an ASAS-endorsed disease activity score (ASDAS) in patients with ankylosing spondylitis. Ann Rheum Dis. 2009;68(1):18–24.

    Article  CAS  Google Scholar 

  5. Garrett S, Jenkinson T, Kennedy LG, et al. A new approach to defining disease status in ankylosing spondylitis: the Bath Ankylosing Spondylitis Disease Activity Index. J Rheumatol. 1994;21(12):2286–91.

    CAS  PubMed  Google Scholar 

  6. Zochling J, Braun J, Van der HD. Assessments in ankylosing spondylitis. Best Pract Res Clin Rheumatol. 2006;20(3):521–37.

    Article  Google Scholar 

  7. Rudwaleit M, Metter A, Listing J, et al. Inflammatory back pain in ankylosing spondylitis: a reassessment of the clinical history for application as classification and diagnostic criteria. Arthritis Rheum. 2014;54(2):569–78.

    Article  Google Scholar 

  8. Braun J, Baraliakos X, Hermann KGA, et al. Golimumab reduces spinal inflammation in ankylosing spondylitis: MRI results of the randomised, placebo-controlled GO-RAISE study. Ann Rheum Dis. 2012;71(6):878–84.

    Article  CAS  Google Scholar 

  9. van der LS, Valkenburg HA, Cats A. Evaluation of diagnostic criteria for ankylosing spondylitis. A proposal for modification of the New York criteria. Arthritis Rheum. 1984;27(4):361–8.

    Article  Google Scholar 

  10. Marzo-Ortega H, O'Connor P, Emery P, et al. Sacroiliac joint biopsies in early sacroiliitis. Rheumatology (Oxford). 2007;46(7):1210–1.

    Article  CAS  Google Scholar 

  11. Rudwaleit M, Jurik AG, Hermann K-G A, et al. Defining active sacroiliitis on magnetic resonance imaging (MRI) for classification of axial spondyloarthritis: a consensual approach by the ASAS/OMERACT MRI group. Ann Rheum Dis. 2009;68(10):1520–7.

    Article  CAS  Google Scholar 

  12. Bozgeyik Z, Ozgocmen S, Kocakoc E. Role of diffusion-weighted MRI in the detection of early active sacroiliitis. AJR Am J Roentgenol. 2008;191(4):980–6.

    Article  Google Scholar 

  13. de HM, Van den BR, Navarro-Compán V, et al. Magnetic resonance imaging of the sacroiliac joints in the early detection of spondyloarthritis: no added value of gadolinium compared with short tau inversion recovery sequence. Rheumatology (Oxford). 2013;52(7):1220–4.

    Article  Google Scholar 

  14. Zhao YH, Zhang Q, Li W, et al. Assessment of correlation between intravoxel incoherent motion diffusion weighted MR imaging and dynamic contrast-enhanced MR imaging of sacroiliitis with ankylosing spondylitis. Biomed Res Int. 2017;2017:1–9.

    Google Scholar 

  15. Attari H, Cao Y, Elmholdt TR, et al. A systematic review of 639 patients with biopsy-confirmed nephrogenic systemic fibrosis. Radiology. 2019;292:376–86.

    Article  Google Scholar 

  16. Akakuru OU, Iqbal MZ, Saeed M, et al. The transition from metal-based to metal-free contrast agents for magnetic resonance imaging enhancement. Bioconjug Chem. 2019;30:2264–86.

    Article  CAS  Google Scholar 

  17. Althoff CE, Feist E, Burova E, et al. Magnetic resonance imaging of active sacroiliitis: do we really need gadolinium? Eur J Radiol. 2009;71(2):0–236.

    Article  Google Scholar 

  18. Boy FN, Kayhan A, Karakas HM, et al. The role of multi-parametric MR imaging in the detection of early inflammatory sacroiliitis according to ASAS criteria. Eur J Radiol. 2014;83(6):989–96.

    Article  Google Scholar 

  19. Shi ZJ, Han JK, Qin J, et al. Clinical application of diffusion-weighted imaging and dynamic contrast-enhanced MRI in assessing the clinical curative effect of early ankylosing spondylitis. Medicine (Baltimore). 2019;98:e15227.

    Article  CAS  Google Scholar 

  20. Bradbury LA, Hollis KA, Gautier B, et al. Diffusion-weighted imaging is a sensitive and specific magnetic resonance sequence in the diagnosis of ankylosing spondylitis. J Rheumatol. 2018;45(6):771–8.

    Article  CAS  Google Scholar 

  21. Gezmis E, Donmez FY, Agildere M. Diagnosis of early sacroiliitis in seronegative spondyloarthropathies by DWI and correlation of clinical and laboratory findings with ADC values. Eur J Radiol. 2013;82(12):2316–21.

    Article  Google Scholar 

  22. Ren C, Zhu Q, Yuan HS. Mono-exponential and bi-exponential model-based diffusion-weighted MR imaging and IDEAL-IQ sequence for quantitative evaluation of sacroiliitis in patients with ankylosing spondylitis. Clin Rheumatol. 2018;37:3069–76.

    Article  Google Scholar 

  23. Årøen A, Brøgger H, Røtterud JH, et al. Evaluation of focal cartilage lesions of the knee using MRI T2 mapping and delayed gadolinium enhanced MRI of cartilage (dGEMRIC). BMC Musculoskelet Disord. 2016;17(1):73.

    Article  Google Scholar 

  24. Fernquest S, Palmer A, Gammer B et al. Compositional MRI of the hip: reproducibility, effect of joint unloading, and comparison of T2 relaxometry with delayed gadolinium-enhanced magnetic resonance imaging of cartilage. Cartilage 2019. https://doi.org/10.1177/1947603519841670

  25. Bristela M, Skolka A, Eder J, et al. T2 mapping with 3.0 T MRI of the temporomandibular joint disc of patients with disc dislocation. Magn Reson Imaging. 2019;58:125–34.

    Article  Google Scholar 

  26. Baum T, Joseph GB, Karampinos DC, et al. Cartilage and meniscal T2 relaxation time as non-invasive biomarker for knee osteoarthritis and cartilage repair procedures. Osteoarthr Cartil. 2013;21(10):1474–84.

    Article  CAS  Google Scholar 

  27. Vermes E, Pantaléon C, Auvet A, et al. Cardiovascular magnetic resonance in heart transplant patients: diagnostic value of quantitative tissue markers: T2 mapping and extracellular volume fraction, for acute rejection diagnosis. J Cardiovasc Magn Reson. 2018;20(1):59.

    Article  Google Scholar 

  28. Maksymowych WP, Inman RD, Salonen D, et al. Spondyloarthritis research consortium of Canada magnetic resonance imaging index for assessment of sacroiliac joint inflammation in ankylosing spondylitis. Arthritis Rheum. 2005;53(5):703–9.

    Article  Google Scholar 

  29. Lambert RGW, Bakker PAC, van der HD, et al. Defining active sacroiliitis on MRI for classification of axial spondyloarthritis: update by the ASAS MRI working group. Ann Rheum Dis. 2016;75:1958–63.

    Article  Google Scholar 

  30. Mosher TJ, Dardzinski BJ, Cartilage MRI. T2 relaxation time mapping: overview and applications. Semin Musculoskelet Radiol. 2004;08(04):355–68.

    Article  Google Scholar 

  31. Albano D, Chianca V, Cuocolo R, et al. T2-mapping of the sacroiliac joints at 1.5 Tesla: a feasibility and reproducibility study. Skelet Radiol. 2018;47:1691–6.

    Article  Google Scholar 

  32. Bining HJS, Santos R, Andrews G, et al. Can T2 relaxation values and color maps be used to detect chondral damage utilizing subchondral bone marrow edema as a marker? Skelet Radiol. 2009;38(5):459–65.

    Article  Google Scholar 

  33. Gong JS, Pedoia V, Facchetti L, et al. Bone marrow edema-like lesions (BMELs) are associated with higher T1ρand T2 values of cartilage in anterior cruciate ligament (ACL)-reconstructed knees: a longitudinal study. Quant Imaging Med Surg. 2016;6(6):661–70.

    Article  Google Scholar 

  34. Maksymowych WP. Ankylosing spondylitis--at the interface of bone and cartilage. J Rheumatol. 2000;27:2295–301.

    CAS  PubMed  Google Scholar 

  35. Van der Heijde D, Rudwaleit M, Landewé Robert BM, et al. Justification for including MRI as a tool in the diagnosis of axial SpA. Nat Rev Rheumatol. 2010;6:670–2.

    Article  Google Scholar 

  36. Maksymowych WP. Imaging in axial spondyloarthritis: evaluation of inflammatory and structural changes. Rheum Dis Clin N Am. 2016;42(4):645–62.

    Article  Google Scholar 

  37. Gatidis S, Schmidt H, Martirosian P, et al. Apparent diffusion coefficient-dependent voxelwise computed diffusion-weighted imaging: an approach for improving SNR and reducing T2 shine-through effects. J Magn Reson Imaging. 2016;43(4):824–32.

    Article  Google Scholar 

  38. Sun HT, Liu K, Liu H, et al. Comparison of bi-exponential and mono-exponential models of diffusion-weighted imaging for detecting active sacroiliitis in ankylosing spondylitis. Acta Radiol. 2018;59:468–77.

    Article  Google Scholar 

  39. Zhang P, Yu K, Guo R, et al. Ankylosing spondylitis: correlations between clinical and MRI indices of sacroiliitis activity. Clin Radiol. 2015;70(1):62–6.

    Article  CAS  Google Scholar 

  40. Zhang MC, Zhou L, Huang N, et al. Assessment of active and inactive sacroiliitis in patients with ankylosing spondylitis using quantitative dynamic contrast-enhanced MRI. J Magn Reson Imaging. 2017;46:71–8.

    Article  Google Scholar 

  41. Bruno F, Arrigoni F, Palumbo P, et al. New advances in MRI diagnosis of degenerative osteoarthropathy of the peripheral joints. Radiol Med. 2019; 124:1121-1127.

Download references

Funding

This work was supported by the Henan Medical Science and Technology Research Program [grant numbers 2018020357 and 2018020367].

Author information

Author notes

  1. Dongdong Wang and Huijia Yin contributed equally to this work.

Authors and Affiliations

  1. Department of MR, The First Affiliated Hospital, Xinxiang Medical University, 88 Jiankang Road, Weihui, 453100, People’s Republic of China

    Dongdong Wang, Huijia Yin, Wenling Liu, Zhong Li, Jipeng Ren & Dongming Han

  2. MR Research China, GE Healthcare, Beijing, 100000, People’s Republic of China

    Kaiyu Wang

Authors
  1. Dongdong Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Huijia Yin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wenling Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhong Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jipeng Ren
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Kaiyu Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Dongming Han
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dongming Han.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Additional information

Publisher’s note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, D., Yin, H., Liu, W. et al. Comparative analysis of the diagnostic values of T2 mapping and diffusion-weighted imaging for sacroiliitis in ankylosing spondylitis. Skeletal Radiol 49, 1597–1606 (2020). https://doi.org/10.1007/s00256-020-03442-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00256-020-03442-8

Keywords

Search

Navigation