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European Radiology

, Volume 29, Issue 12, pp 6708–6716 | Cite as

Clinical value of a [18F]-FDG PET-CT muscle-to-muscle SUV ratio for the diagnosis of active dermatomyositis

  • Nihal MartisEmail author
  • Philippe Viau
  • Thierry Zenone
  • Fanny Andry
  • Aurélie Grados
  • Mikael Ebbo
  • Emeline Castela
  • Benoit Brihaye
  • Eric Denis
  • Stéphane Liguori
  • Alexandra Audemard
  • Yoland Schoindre
  • Anne-Sophie Morin
  • Benjamin Terrier
  • Laurent Marcq
  • Nicolas Mounier
  • Olivier Lidove
  • Jean-Philippe Chaborel
  • Denis Quinsat
Nuclear Medicine

Abstract

Objective

To study a muscle-to-muscle standardised uptake value (SUV) ratio with FDG-PET/CT (FDG-PET) as a marker for the detection of disease activity in dermatomyositis (DM).

Methods

Patients with DM (n = 24) who met the European Neuro-Muscular Centre diagnostic criteria were retrospectively identified over a 3-year period through a national survey. Muscle biopsy was performed in all patients. Maximum SUV was measured in proximal muscles (SUVPROX) that had the highest radiotracer uptake on visual grading as well as in the musculus longissimus thoracis (SUVMLT), whereas mean SUV was measured for the liver (SUVLIV). Muscle-to-liver SUV ratios for either muscle group were compared and a SUVPROX/SUVMLT ratio was calculated. SUVPROX/SUVMLT of DM patients were compared with age- and sex-matched control subjects (n = 24) with melanoma who had received FDG-PET scans.

Results

DM patients presented with proximal and symmetrical muscle uptake. Differences in SUVPROX/SUVLIV and SUVMLT/SUVLIV ratios in DM subjects were significant (p < 0.001). SUVPROX/SUVMLT ratios in DM and their controls also differed significantly (p = 0.0012). The SUVPROX/SUVMLT ratio threshold between DM subjects and controls was 1.73 with a sensitivity of 50% (CI95%, 29.1 to 70.9%) and specificity at 83.3% (CI95%, 62.6 to 95.3%). When amyopathic DM patients were removed from the analysis, specificity was increased to 95% (CI95%, 75.1 to 99.9%) with a likelihood ratio of 10 and an AUC of 83.4% (CI95%, 71.4 to 95.4%).

Conclusion

A muscle-to-muscle SUVPROX/SUVMLT ratio with a cut-off value of 1.73 in FDG-PET imaging might serve as a non-invasive marker to determine disease activity in dermatomyositis.

Key Points

• [18F]-FDG PET-scanner standardised uptake value (SUV) could reflect disease activity in dermatomyositis (DM).

A ratio of SUV in proximal muscles (SUVPROX) to SUV in musculus longissimus thoracis (SUVMLT) could be used to determine active DM.

• Active disease is suspected for SUV PROX /SUV MLT ratios greater than 1.73.

Keywords

Positron-emission tomography Fluorodeoxyglucose F18 Myositis Dermatomyositis Amyopathic dermatomyositis 

Abbreviations

DM

Dermatomyositis

ENMC

European Neuro-Muscular Centre

IMM

Idiopathic inflammatory myositis

MAA

Myositis-associated autoantibodies

MSA

Myositis-specific autoantibodies

SUV

Standardised uptake value

SUVLIV

SUV of the liver

SUVMLT

Musculus longissimus thoracis SUV

SUVPROX

Proximal muscles SUV

Notes

Acknowledgements

We would like to thank all those who supported and collaborated on this work, especially the Amicale des Jeunes Internistes and the Société Nationale Française de Médecine Interne. Our special thanks to Dr. Arsène Mekinian for his precious advice.

Funding

The authors state that this work has not received any funding.

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Nihal Martis.

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 (Nicolas Mounier) has significant statistical expertise. No complex statistical methods were necessary for this paper.

Ethical approval

In accordance with French regulation, approval of the institutional review board was not required but the data were collected, stored and handled anonymously as it is usually the case in retrospective studies.

Informed consent

For this type of study, formal patient consent was not required for de-identified data according to French Regulation (“recherche de catégorie 3”).

Methodology

• retrospective

• diagnostic study

• multicentre study

Supplementary material

330_2019_6302_MOESM1_ESM.docx (108 kb)
ESM 1 (DOCX 108 kb)

References

  1. 1.
  2. 2.
    Stertz G (1916) Polymyositis. Berl Klin Wochenschr 489Google Scholar
  3. 3.
    Zampieri S, Valente M, Adami N et al (2010) Polymyositis, dermatomyositis and malignancy: a further intriguing link. Autoimmun Rev 9:449–453.  https://doi.org/10.1016/j.autrev.2009.12.005 CrossRefPubMedGoogle Scholar
  4. 4.
    Hoogendijk JE, Amato AA, Lecky BR et al (2004) 119th ENMC international workshop: Trial design in adult idiopathic inflammatory myopathies, with the exception of inclusion body myositis, 10–12 October 2003, Naarden, The Netherlands. Neuromuscul Disord 14:337–345.  https://doi.org/10.1016/j.nmd.2004.02.006 CrossRefPubMedGoogle Scholar
  5. 5.
    Bunch TW (1990) Polymyositis: a case history approach to the differential diagnosis and treatment. Mayo Clin Proc 65:1480–1497CrossRefGoogle Scholar
  6. 6.
    Day J, Patel S, Limaye V (2017) The role of magnetic resonance imaging techniques in evaluation and management of the idiopathic inflammatory myopathies. Semin Arthritis Rheum 46:642–649.  https://doi.org/10.1016/j.semarthrit.2016.11.001 CrossRefPubMedGoogle Scholar
  7. 7.
    Ukichi T, Yoshida K, Matsushima S et al (2019) MRI of skeletal muscles in patients with idiopathic inflammatory myopathies: characteristic findings and diagnostic performance in dermatomyositis. RMD Open 5:e000850.  https://doi.org/10.1136/rmdopen-2018-000850 CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Van De Vlekkert J, Maas M, Hoogendijk JE, De Visser M, Van Schaik IN (2014) Combining MRI and muscle biopsy improves diagnostic accuracy in subacute-onset idiopathic inflammatory myopathy. Muscle Nerve 51:253–258.  https://doi.org/10.1002/mus.24307
  9. 9.
    Owada T, Maezawa R, Kurasawa K, Okada H, Arai S, Fukuda T (2012) Detection of inflammatory lesions by F-18 fluorodeoxyglucose positron emission tomography in patients with polymyositis and dermatomyositis. J Rheumatol 39:1659–1665.  https://doi.org/10.3899/jrheum.111597
  10. 10.
    Pipitone N, Versari A, Zuccoli G et al (2012) 18F-Fluorodeoxyglucose positron emission tomography for the assessment of myositis: case series. Clin Exp Rheumatol 30:570–573Google Scholar
  11. 11.
    Tanaka S, Ikeda K, Uchiyama K et al (2013) [18F]FDG uptake in proximal muscles assessed by PET/CT reflects both global and local muscular inflammation and provides useful information in the management of patients with polymyositis/dermatomyositis. Rheumatology (Oxford) 52:1271–1278.  https://doi.org/10.1093/rheumatology/ket112 CrossRefGoogle Scholar
  12. 12.
    Tateyama M, Fujihara K, Misu T, Arai A, Kaneta T, Aoki M (2015) Clinical values of FDG PET in polymyositis and dermatomyositis syndromes: imaging of skeletal muscle inflammation. BMJ Open 5:e006763.  https://doi.org/10.1136/bmjopen-2014-006763
  13. 13.
    Weckbach S (2009) Whole-body MR imaging for patients with rheumatism. Eur J Radiol 70:431–441.  https://doi.org/10.1016/j.ejrad.2009.03.047 CrossRefPubMedGoogle Scholar
  14. 14.
    Berner U, Menzel C, Rinne D et al (2003) Paraneoplastic syndromes: detection of malignant tumors using [(18)F]FDG-PET. Q J Nucl Med 47:85–89PubMedGoogle Scholar
  15. 15.
    Kristensen SB, Hess S, Petersen H, Høilund-Carlsen PF (2015) Clinical value of FDG-PET/CT in suspected paraneoplastic syndromes: a retrospective analysis of 137 patients. Eur J Nucl Med Mol Imaging 42:2056–2063.  https://doi.org/10.1007/s00259-015-3126-2 CrossRefPubMedGoogle Scholar
  16. 16.
    Hill CL, Zhang Y, Sigurgeirsson B et al (2001) Frequency of specific cancer types in dermatomyositis and polymyositis: a population-based study. Lancet 357:96–100.  https://doi.org/10.1016/S0140-6736(00)03540-6 CrossRefPubMedGoogle Scholar
  17. 17.
    Shreve PD, Anzai Y, Wahl RL (1999) Pitfalls in oncologic diagnosis with FDG PET imaging: physiologic and benign variants. Radiographics 19:61–77; quiz 150–151.  https://doi.org/10.1148/radiographics.19.1.g99ja0761 CrossRefPubMedGoogle Scholar
  18. 18.
    Sugawara Y, Zasadny KR, Neuhoff AW, Wahl RL (1999) Reevaluation of the standardized uptake value for FDG: variations with body weight and methods for correction. Radiology 213:521–525.  https://doi.org/10.1148/radiology.213.2.r99nv37521 CrossRefPubMedGoogle Scholar
  19. 19.
    Kim CK, Gupta NC, Chandramouli B, Alavi A (1994) Standardized uptake values of FDG: body surface area correction is preferable to body weight correction. J Nucl Med 35:164–167PubMedGoogle Scholar
  20. 20.
    Iaccarino L, Cooper R, Doria A (2015) Polymyositis and dermatomyositis. In: EULAR textbook on rheumatic diseases, second editionGoogle Scholar
  21. 21.
    Mueller M, Reimold M, Pfannenberg C, Bares R (2009) Influence of the acute phase reaction on the [18F]FDG uptake of the liver. J Nucl Med 50:612Google Scholar
  22. 22.
    Ceriani L, Suriano S, Ruberto T, Zucca E, Giovanella L (2012) 18F-FDG uptake changes in liver and mediastinum during chemotherapy in patients with diffuse large B-cell lymphoma. Clin Nucl Med 37:949–952.  https://doi.org/10.1097/RLU.0b013e318263831d
  23. 23.
    Winter EM, Schrander-van der Meer A, Eustatia-Rutten C, Janssen M (2011) Hydroxychloroquine as a glucose lowering drug. BMJ Case Rep 2011.  https://doi.org/10.1136/bcr.06.2011.4393
  24. 24.
    Emami J, Gerstein HC, Pasutto FM, Jamali F (1999) Insulin-sparing effect of hydroxychloroquine in diabetic rats is concentration dependent. Can J Physiol Pharmacol 77:118–123CrossRefGoogle Scholar
  25. 25.
    Büsing KA, Schönberg SO, Brade J, Wasser K (2013) Impact of blood glucose, diabetes, insulin, and obesity on standardized uptake values in tumors and healthy organs on 18F-FDG PET/CT. Nucl Med Biol 40:206–213.  https://doi.org/10.1016/j.nucmedbio.2012.10.014 CrossRefPubMedGoogle Scholar
  26. 26.
    Selva-O’Callaghan A, Grau JM, Gámez-Cenzano C et al (2010) Conventional cancer screening versus PET/CT in dermatomyositis/polymyositis. Am J Med 123:558–562.  https://doi.org/10.1016/j.amjmed.2009.11.012 CrossRefPubMedGoogle Scholar
  27. 27.
    Selva-O’Callaghan A, Trallero-Araguás E, Grau-Junyent JM, Labrador-Horrillo M (2010) Malignancy and myositis: novel autoantibodies and new insights. Curr Opin Rheumatol 22:627–632.  https://doi.org/10.1097/BOR.0b013e32833f1075 CrossRefPubMedGoogle Scholar

Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  • Nihal Martis
    • 1
    Email author
  • Philippe Viau
    • 2
  • Thierry Zenone
    • 3
  • Fanny Andry
    • 4
  • Aurélie Grados
    • 5
  • Mikael Ebbo
    • 5
  • Emeline Castela
    • 1
  • Benoit Brihaye
    • 6
  • Eric Denis
    • 7
  • Stéphane Liguori
    • 8
  • Alexandra Audemard
    • 9
  • Yoland Schoindre
    • 10
  • Anne-Sophie Morin
    • 11
  • Benjamin Terrier
    • 12
  • Laurent Marcq
    • 7
  • Nicolas Mounier
    • 13
  • Olivier Lidove
    • 14
  • Jean-Philippe Chaborel
    • 15
  • Denis Quinsat
    • 7
  1. 1.Service de Médecine InterneCHU de Nice, Université Côte d’Azur, Faculté de Médecine de NiceNiceFrance
  2. 2.Service de Médecine Nucléaire, CHU de NiceUniversité Côte d’Azur, Faculté de Médecine de NiceNiceFrance
  3. 3.Service de Médecine InterneCH de ValenceValenceFrance
  4. 4.Service de Médecine InterneCHU MichallonGrenobleFrance
  5. 5.Service de Médecine InterneHôpital La Timone, AP-HMMarseilleFrance
  6. 6.Service de Médecine InterneCH Saint-QuentinSaint-QuentinFrance
  7. 7.Service de Médecine InterneCH d’Antibes-Juan-les-PinsAntibesFrance
  8. 8.Service de Biologie MédicaleCH d’Antibes-Juan-les-PinsAntibesFrance
  9. 9.Service de Médecine InterneCHU de CaenCaenFrance
  10. 10.Service de Médecine InterneHôpital de la Pitié Salpêtrière, AP-HPParisFrance
  11. 11.Service de Médecine InterneHôpital Jean Verdier, AP-HPBondyFrance
  12. 12.Service de Médecine InterneHôpital Cochin, AP-HPParisFrance
  13. 13.Service d’Onco-HématologieCHU de Nice, Université Côte d’Azur, Faculté de Médecine de NiceNiceFrance
  14. 14.Service de Médecine InterneCH Croix St-SimonParisFrance
  15. 15.Service de Médecine Nucléaire, Institut Tzanck MouginsMouginsFrance

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