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Journal of Nuclear Cardiology

, Volume 26, Issue 1, pp 59–67 | Cite as

F-18 FDG PET for assessment of disease activity of large vessel vasculitis: A systematic review and meta-analysis

  • Sang-Woo Lee
  • Seong-Jang KimEmail author
  • Youngduk Seo
  • Shin Young Jeong
  • Byeong-Cheol Ahn
  • Jaetae Lee
Original Article

Abstract

Background

The aim of this study is to investigate the performance of F-18 fluorodeoxyglucose positron emission tomography (F-18 FDG PET) or positron emission tomography/computed tomography (PET/CT) for the assessment of disease activity in patients with large vessel vasculitis (LVV) through a meta-analysis.

Methods

The MEDLINE via PubMed and EMBASE were searched for the studies evaluating the performance of F-18 FDG PET or PET/CT in the assessment of disease activity in patients with LVV. Pooled sensitivity, specificity, diagnostic odds ratios (DORs), and summary receiver-operating characteristic (sROC) curve were estimated across the included studies. Possible publication bias was assessed by Deek’s funnel plot asymmetry tests.

Results

A total of 439 PET images from 298 patients pooled from nine studies showed that the pooled sensitivity was 0.88 [95% confidence interval (CI) 0.79-0.93] without heterogeneity (χ2 = 14.42, P = .07) and the pooled specificity was 0.81 (95% CI 0.64-0.91) with heterogeneity (χ2 = 63.72, P = .00) for the detection of active LVV. The pooled DOR was 30 (95% CI 8-107). Hierarchical sROC curve indicates that the area under the curve was 0.91 (95% CI 0.89-0.94). There was no significant publication bias (P = .42), and meta-regression analysis revealed that none of the variables was the source of the study heterogeneity.

Conclusions

F-18 FDG PET has a good performance for the detection of active disease status in patients with LVV. Revised criteria for the assessment of disease activity incorporated with F-18 FDG PET or PET/CT should be introduced and validated. Further studies are warranted to determine if PET-based treatment of LVV can improve outcomes.

Keywords

F-18 fluorodeoxyglucose PET large vessel vasculitis disease activity meta-analysis 

Abbreviations

DORs

Diagnostic odds ratios

ESR

Erythrocyte sedimentation rates

FDG

Fluorodeoxyglucose

GCA

Giant cell arteritis

LVV

Large vessel vasculitis

PET

Positron emission tomography

PET/CT

Positron emission tomography/computed tomography

SUVmax

Maximum standardized uptake value

TA

Takayasu’s arteritis

Notes

Disclosure

The authors of this manuscript declare no relationships with any companies products or services of which may be related to the subject matter of the article.

Informed Consent

Written informed consent was not required for this study because it is a meta-analysis based on the studies that have been published.

Ethical Approval

Institutional Review Board approval was not required because only the published studies were used in this meta-analysis. The manuscript has not been published before and is not under consideration for publication anywhere else.

Supplementary material

12350_2018_1406_MOESM1_ESM.pptx (1.1 mb)
Supplementary material 1 (pptx 1084 kb)

References

  1. 1.
    Hunder GG, Bloch DA, Michel BA, Stevens MB, Arend WP, Calabrese LH, et al. The American College of Rheumatology 1990 criteria for the classification of giant cell arteritis. Arthritis Rheumatol 1990;33:1122-8.Google Scholar
  2. 2.
    Arend WP, Michel BA, Bloch DA, Hunder GG, Calabrese LH, Edworthy SM, et al. The American College of Rheumatology 1990 criteria for the classification of Takayasu arteritis. Arthritis Rheumatol 1990;33:1129-34.Google Scholar
  3. 3.
    Rao JK, Allen NB, Pincus T. Limitations of the 1990 American College of Rheumatology classification criteria in the diagnosis of vasculitis. Ann Intern Med 1998;129:345-52.Google Scholar
  4. 4.
    Seeliger B, Sznajd J, Robson JC, Judge A, Craven A, Grayson PC, et al. Are the 1990 American College of Rheumatology vasculitis classification criteria still valid? Rheumatology (Oxf) 2017;56:1154-61.Google Scholar
  5. 5.
    Kerr GS, Hallahan CW, Giordano J, Leavitt RY, Fauci AS, Rottem M, et al. Takayasu arteritis. Ann Intern Med 1994;120:919-29.Google Scholar
  6. 6.
    Maleszewski JJ, Younge BR, Fritzlen JT, Hunder GG, Goronzy JJ, Warrington KJ, et al. Clinical and pathological evolution of giant cell arteritis: A prospective study of follow-up temporal artery biopsies in 40 treated patients. Mod Pathol 2017;30:788-96.Google Scholar
  7. 7.
    Love C, Tomas MB, Tronco GG, Palestro CJ. FDG PET of infection and inflammation. RadioGraphics 2005;25:1357-68.Google Scholar
  8. 8.
    Walter MA, Melzer RA, Schindler C, Müller-Brand J, Tyndall A, Nitzsche EU. The value of [18F]FDG-PET in the diagnosis of large-vessel vasculitis and the assessment of activity and extent of disease. Eur J Nucl Med Mol Imaging 2005;32:674-81.Google Scholar
  9. 9.
    Arnaud L, Haroche J, Malek Z, Archambaud F, Gambotti L, Grimon G, et al. Is (18)F-fluorodeoxyglucose positron emission tomography scanning a reliable way to assess disease activity in Takayasu arteritis? Arthritis Rheumatol 2009;60:1193-200.Google Scholar
  10. 10.
    Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med 2009;6:e1000097.Google Scholar
  11. 11.
    Whiting PF, Rutjes AW, Westwood ME, Mallett S, Deeks JJ, Reitsma JB, et al. QUADAS-2: A revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 2011;155:529-36.Google Scholar
  12. 12.
    Thompson SG. Why sources of heterogeneity in meta-analysis should be investigated. BMJ 1994;309:1351-5.Google Scholar
  13. 13.
    Zamora J, Abraira V, Muriel A, Khan K, Coomarasamy A. Meta-DiSc: A software for meta-analysis of test accuracy data. BMC Med Res Methodol 2006;6:31.Google Scholar
  14. 14.
    Deeks JJ, Macaskill P, Irwig L. The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. J Clin Epidemiol 2005;58:882-93.Google Scholar
  15. 15.
    Reitsma JB, Glas AS, Rutjes AW, Scholten RJ, Bossuyt PM, Zwinderman AH. Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J Clin Epidemiol 2005;58:982-90.Google Scholar
  16. 16.
    Hamza TH, van Houwelingen HC, Stijnen T. The binomial distribution of meta-analysis was preferred to model within-study variability. J Clin Epidemiol 2008;61:41-51.Google Scholar
  17. 17.
    Rutter CM, Gatsonis CA. A hierarchical regression approach to meta-analysis of diagnostic test accuracy evaluations. Stat Med 2001;20:2865-84.Google Scholar
  18. 18.
    Grayson PC, Alehashemi S, Bagheri AA, Civelek AC, Cupps TR, Kaplan MJ, et al. Positron emission tomography as an imaging biomarker in a prospective, longitudinal cohort of patients with large vessel vasculitis. Arthritis Rheumatol 2018;70:439-49.Google Scholar
  19. 19.
    Karapolat I, Kalfa M, Keser G, Yalçin M, Inal V, Kumanlioğlu K, et al. Comparison of 18F-FDG PET/CT findings with current clinical disease status in patients with Takayasu’s arteritis. Clin Exp Rheumatol 2013;31:S15-21.Google Scholar
  20. 20.
    Kobayashi Y, Ishii K, Oda K, Nariai T, Tanaka Y, Ishiwata K, et al. Aortic wall inflammation due to Takayasu arteritis imaged with 18F-FDG PET coregistered with enhanced CT. J Nucl Med 2005;46:917-22.Google Scholar
  21. 21.
    Lee KH, Cho A, Choi YJ, Lee SW, Ha YJ, Jung SJ, et al. The role of (18)F-fluorodeoxyglucose-positron emission tomography in the assessment of disease activity in patients with Takayasu arteritis. Arthritis Rheumatol 2012;64:866-75.Google Scholar
  22. 22.
    Lee SG, Ryu JS, Kim HO, Oh JS, Kim YG, Lee CK, et al. Evaluation of disease activity using F-18 FDG PET–CT in patients with Takayasu arteritis. Clin Nucl Med 2009;34:749-52.Google Scholar
  23. 23.
    Santhosh S, Mittal BR, Gayana S, Bhattacharya A, Sharma A, Jain S. F-18 FDG PET/CT in the evaluation of Takayasu arteritis: An experience from the tropics. J Nucl Cardiol 2014;21:993-1000.Google Scholar
  24. 24.
    Tezuka D, Haraguchi G, Ishihara T, Ohigashi H, Inagaki H, Suzuki J, et al. Role of FDG PET–CT in Takayasu arteritis: Sensitive detection of recurrences. JACC Cardiovasc Imaging 2012;5:422-9.Google Scholar
  25. 25.
    Webb M, Chambers A, Al-Nahhas A, Mason JC, Maudlin L, Rahman L, et al. The role of 18F-FDG PET in characterising disease activity in Takayasu arteritis. Eur J Nucl Med Mol Imaging 2004;31:627-34.Google Scholar
  26. 26.
    Affolter B, Thalhammer C, Aschwanden M, Glatz K, Tyndall A, Daikeler T. Difficult diagnosis and assessment of disease activity in giant cell arteritis: A report on two patients. Scand J Rheumatol 2009;38:393-4.Google Scholar
  27. 27.
    Chatterjee S, Flamm SD, Tan CD, Rodriguez ER. Clinical diagnosis and management of large vessel vasculitis: Giant cell arteritis. Curr Cardiol Rep 2014;16:498.Google Scholar
  28. 28.
    Besson FL, Parienti JJ, Bienvenu B, Prior JO, Costo S, Bouvard G, et al. Diagnostic performance of 18F-fluorodeoxyglucose positron emission tomography in giant cell arteritis: A systematic review and meta-analysis. Eur J Nucl Med Mol Imaging 2011;38:1764-72.Google Scholar
  29. 29.
    Lee YH, Choi SJ, Ji JD, Song GG. Diagnostic accuracy of 18F-FDG PET or PET/CT for large vessel vasculitis: A meta-analysis. Z Rheumatol 2016;75:924-31.Google Scholar
  30. 30.
    Aydin SZ, Yilmaz N, Akar S, Aksu K, Kamali S, Yucel E, et al. Assessment of disease activity and progression in Takayasu’s arteritis with Disease Extent Index-Takayasu. Rheumatology (Oxf) 2010;49:1889-93.Google Scholar
  31. 31.
    Turlakow A, Yeung HW, Pui J, Macapinlac H, Liebovitz E, Rusch V, et al. Fludeoxyglucose positron emission tomography in the diagnosis of giant cell arteritis. Arch Intern Med 2001;161:1003-7.Google Scholar
  32. 32.
    Puppo C, Massollo M, Paparo F, Camellino D, Piccardo A, Shoushtari Zadeh Naseri M, et al. Giant cell arteritis: A systematic review of the qualitative and semiquantitative methods to assess vasculitis with 18F-fluorodeoxyglucose positron emission tomography. BioMed Res Int 2014;2014:574248.Google Scholar
  33. 33.
    Meller J, Strutz F, Siefker U, Scheel A, Sahlmann CO, Lehmann K, et al. Early diagnosis and follow-up of aortitis with [(18)F]FDG PET and MRI. Eur J Nucl Med Mol Imaging 2003;30:730-6.Google Scholar
  34. 34.
    Moosig F, Czech N, Mehl C, Henze E, Zeuner RA, Kneba M, et al. Correlation between 18-fluorodeoxyglucose accumulation in large vessels and serological markers of inflammation in polymyalgia rheumatica: A quantitative PET study. Ann Rheum Dis 2004;63:870-3.Google Scholar
  35. 35.
    Both M, Ahmadi-Simab K, Reuter M, Dourvos O, Fritzer E, Ullrich S, et al. MRI and FDG-PET in the assessment of inflammatory aortic arch syndrome in complicated courses of giant cell arteritis. Ann Rheum Dis 2008;67:1030-3.Google Scholar

Copyright information

© American Society of Nuclear Cardiology 2018

Authors and Affiliations

  • Sang-Woo Lee
    • 1
  • Seong-Jang Kim
    • 2
    • 3
    Email author
  • Youngduk Seo
    • 4
  • Shin Young Jeong
    • 1
  • Byeong-Cheol Ahn
    • 1
  • Jaetae Lee
    • 1
  1. 1.Department of Nuclear Medicine, School of MedicineKyungpook National UniversityTaeguSouth Korea
  2. 2.Department of Nuclear MedicinePusan National University Yangsan HospitalYangsanSouth Korea
  3. 3.BioMedical Research Institute for Convergence of Biomedical Science and TechnologyPusan National University Yangsan HospitalYangsanSouth Korea
  4. 4.Department of Nuclear MedicineBusan Seongso HospitalPusanSouth Korea

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