Cancer Immunology, Immunotherapy

, Volume 68, Issue 2, pp 297–303 | Cite as

Can benign lymphoid tissue changes in 18F-FDG PET/CT predict response to immunotherapy in metastatic melanoma?

  • Christos SachpekidisEmail author
  • Lionel Larribère
  • Annette Kopp-Schneider
  • Jessica C. Hassel
  • Antonia Dimitrakopoulou-Strauss
Original Article



An association between immune-related adverse events (irAEs) caused by immunotherapeutic agents and the clinical benefit of immunotherapy has been suggested. We retrospectively evaluated by means of 18F-FDG PET/CT lymphoid tissue changes in the mediastinal/hilar lymph nodes and the spleen in response to ipilimumab administration in metastatic melanoma.


A total of 41 patients with unresectable metastatic melanoma underwent 18F-FDG PET/CT before the start of ipilimumab (baseline PET/CT), after two cycles (interim PET/CT) and at the end of treatment (late PET/CT). Data analysis was focused on the mediastinal/hilar lymph nodes and the spleen. The patients’ best clinical response (BCR) was used as reference.


According to the BCR reference, 31 patients showed disease control (DC) and 10 patients showed progressive disease (PD). Mediastinal/hilar lymph node evaluation revealed that in total 4 patients in the interim or late PET/CT (10%) demonstrated a ‘sarcoid-like lymphadenopathy’ as response to treatment (LN-positive). All LN-positive patients responded to ipilimumab with DC. On the other hand, no significant differences between the DC and PD groups regarding both semi-quantitative and quantitative 18F-FDG PET spleen-related parameters at baseline and as response to treatment were detected.


Based on our findings, 10% patients in the interim or late PET/CT showed ‘sarcoid-like lymphadenopathy’ as response to treatment. All these patients showed disease control, implying a relation between the appearance of sarcoid-like lymphadenopathy and the clinical benefit of anti-CTLA-4 therapy. On the other hand, quantitative 18F-FDG PET analysis of the spleen showed a poor performance in predicting clinical benefit to ipilimumab.


Metastatic melanoma Ipilimumab ‘Sarcoid-like lymphadenopathy’ Spleen glucose metabolism 18F-FDG PET/CT 





Best clinical response


Complete response


Computed tomography


Disease control


Dynamic positron emission tomography/computed tomography


Fractal dimension


Immune-related adverse events


Negative mediastinal/hilar lymph nodes


Positive mediastinal/hilar lymph nodes


Progressive disease


Positron emission tomography


Positron emission tomography/computed tomography


Partial response


Stable disease


Standardized uptake value


Volume of interest


Author contributions

CS performed the PET/CT studies, carried out the PET/CT data analysis, drafted and performed final editing of the manuscript. LL contributed to the conception of the study and co-drafted the manuscript. AK-S was responsible for the statistical analysis of the study. JCH was responsible for the selection of the patients who received the ipilimumab therapy and co-drafted the manuscript. AD-S was responsible for the PET-CT study design and the data evaluation and coordinated the project.


This study was supported in part by the German Cancer Aid under the project with the title ‘Therapy monitoring of ipilimumab based on the quantification of F-18-FDG kinetics with 4D PET/CT (dPET-CT) in patients with melanoma (stage 4)’. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. No additional external funding was received for this study.

Compliance with ethical standards

Conflict of interest

Jessica C. Hassel received honoraria for talks and travel expenses from Bristol-Myers Squibb (BMS), Merck, Sharp & Dohm (MSD), Roche, Novartis, Pfizer and is a member of an advisory board for MSD and Amgen. The other authors declare that they have no conflict of interest.

Ethical approval

The presented results are part of the study entitled “Quantification of 18F-FDG kinetics with 4D PET-CT in patients with melanoma stage IV”, which was approved by the Ethical Committee of the University of Heidelberg (Ethikvotum: S-107 /2012—Ethical Committee 1 of the University of Heidelberg) and the Federal Office for Radiation Protection (Bundesamt für Strahlenschutz; BfS: Z5- 22463 / 2 2012a-016). This study does not contain any studies with animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study. The patient presented in Fig. 1 agreed to the publication of this figure.


  1. 1.
    Downey SG, Klapper JA, Smith FO et al (2007) Prognostic factors related to clinical response in patients with metastatic melanoma treated by CTL-associated antigen-4 blockade. Clin Cancer Res 13(22 Pt 1):6681–6688CrossRefGoogle Scholar
  2. 2.
    Hodi FS, O’Day SJ, McDermott DF et al (2010) Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med 363:711–723CrossRefGoogle Scholar
  3. 3.
    Postow MA, Chesney J, Pavlick AC et al (2015) Nivolumab and ipilimumab versus ipilimumab in untreated melanoma. N Engl J Med 372:2006–2017CrossRefGoogle Scholar
  4. 4.
    Larkin J, Chiarion-Sileni V, Gonzalez R et al (2015) Combined nivolumab and ipilimumab or monotherapy in untreated melanoma. N Engl J Med 373:23–34CrossRefGoogle Scholar
  5. 5.
    Weber JS, Kähler KC, Hauschild A (2012) Management of immune-related adverse events and kinetics of response with ipilimumab. J Clin Oncol 30(21):2691–2697CrossRefGoogle Scholar
  6. 6.
    Attia P, Phan GQ, Maker AV et al (2005) Autoimmunity correlates with tumor regression in patients with metastatic melanoma treated with anti-cytotoxic T-lymphocyte antigen-4. J Clin Oncol 23(25):6043–6053CrossRefGoogle Scholar
  7. 7.
    Kaehler KC, Piel S, Livingstone E, Schilling B, Hauschild A, Schadendorf D (2010) Update on immunologic therapy with anti-CTLA-4 antibodies in melanoma: identification of clinical and biological response patterns, immune-related adverse events, and their management. Semin Oncol 37(5):485–498CrossRefGoogle Scholar
  8. 8.
    Kubota R, Yamada S, Kubota K, Ishiwata K, Tamahashi N, Ido T (1992) Intratumoral distribution of fluorine-18-fluorodeoxyglucose in vivo: high accumulation in macrophages and granulation tissues studied by microautoradiography. J Nucl Med 33:1972–1980Google Scholar
  9. 9.
    Gamelli RL, Liu H, He LK, Hofmann CA (1996) Augmentations of glucose uptake and glucose transporter-1 in macrophages following thermal injury and sepsis in mice. J Leukoc Biol 59:639–647CrossRefGoogle Scholar
  10. 10.
    Mochizuki T, Tsukamoto E, Kuge Y et al (2001) FDG uptake and glucose transporter subtype expressions in experimental tumor and inflammation models. J Nucl Med 42:1551–1555Google Scholar
  11. 11.
    Zhuang H, Alavi A (2002) 18-fluorodeoxyglucose positron emission tomographic imaging in the detection and monitoring of infection and inflammation. Semin Nucl Med 32:47–59CrossRefGoogle Scholar
  12. 12.
    Paik JY, Lee KH, Choe YS et al (2004) Augmented 18F-FDG uptake in activated monocytes occurs during the priming process and involves tyrosine kinases and protein kinase C. J Nucl Med 45:124–128Google Scholar
  13. 13.
    Jamar F, Buscombe J, Chiti A et al (2013) EANM/SNMMI guideline for 18F-FDG use in inflammation and infection. J Nucl Med 54(4):647–658CrossRefGoogle Scholar
  14. 14.
    Wong ANM, McArthur GA, Hofman MS, Hicks RJ (2017) The advantages and challenges of using FDG PET/CT for response assessment in melanoma in the era of targeted agents and immunotherapy. Eur J Nucl Med Mol Imaging 44(Suppl 1):67–77CrossRefGoogle Scholar
  15. 15.
    Balch CM, Gershenwald JE, Soong S-J et al (2009) Final version of 2009 AJCC melanoma staging and classification. J Clin Oncol 27(36):6199–6206CrossRefGoogle Scholar
  16. 16.
    Anwar H, Sachpekidis C, Winkler J et al (2018) Absolute number of new lesions in 18F-FDG PET/CT is more predictive of clinical outcome than SUV changes in metastatic melanoma patients receiving ipilimumab. Eur J Nucl Med Mol Imaging 45(3):376–383CrossRefGoogle Scholar
  17. 17.
    Sachpekidis C, Anwar H, Winkler J et al (2018) The role of interim 18F-FDG PET/CT in prediction of response to ipilimumab treatment in metastatic melanoma. Eur J Nucl Med Mol Imaging 45(8):1289–1296CrossRefGoogle Scholar
  18. 18.
    Sachpekidis C, Anwar H, Winkler JK et al (2018) Longitudinal studies of the 18F-FDG kinetics after ipilimumab treatment in metastatic melanoma patients based on dynamic FDG PET/CT. Cancer Immunol Immunother 67:1261–1270. (Epub ahead of print)CrossRefGoogle Scholar
  19. 19.
    Sokoloff L, Smith CB (1983) Basic principles underlying radioisotopic methods for assay of biochemical processes in vivo. In: Greitz T, Ingvar DH, Widén L (eds) The metabolism of the human brain studied with positron emission tomography. Raven Press, New York, pp 123–148Google Scholar
  20. 20.
    Ohtake T, Kosaka N, Watanabe T et al (1991) Noninvasive method to obtain input function for measuring tissue glucose utilization of thoracic and abdominal organs. J Nucl Med 32:1432–1438Google Scholar
  21. 21.
    Miyazawa H, Osmont A, Petit-Taboué MC et al (1993) Determination of 18F-fluoro-2-deoxy-d-glucose rate constants in the anesthetized baboon brain with dynamic positron tomography. J Neurosci Methods 50:263–272CrossRefGoogle Scholar
  22. 22.
    Burger C, Buck A (1997) Requirements and implementation of a flexible kinetic modeling tool. J Nucl Med 38:1818–1823Google Scholar
  23. 23.
    Sachpekidis C, Thieke C, Askoxylakis V et al (2015) Combined use of (18)F-FDG and (18)F-FMISO in unresectable non-small cell lung cancer patients planned for radiotherapy: a dynamic PET/CT study. Am J Nucl Med Mol Imaging 5(2):127–142Google Scholar
  24. 24.
    Dimitrakopoulou-Strauss A, Strauss LG, Mikolajczyk K, Burger C, Lehnert T, Bernd L, Ewerbeck V (2003) On the fractal nature of dynamic positron emission tomography (PET) studies. World J Nucl Med 2:306–313Google Scholar
  25. 25.
    Bronstein Y, Ng CS, Hwu P, Hwu WJ (2011) Radiologic manifestations of immune-related adverse events in patients with metastatic melanoma undergoing anti-CTLA-4 antibody therapy. Am J Roentgenol 197(6):W992–W1000CrossRefGoogle Scholar
  26. 26.
    Kwak JJ, Tirumani SH, Van den Abbeele AD, Koo PJ, Jacene HA (2015) Cancer immunotherapy: imaging assessment of novel treatment response patterns and immune-related adverse events. Radiographics 35(2):424–437CrossRefGoogle Scholar
  27. 27.
    Howard SA, Krajewski KM, Jagannathan JP et al (2016) A new look at toxicity in the era of precision oncology: imaging findings, their relationship with tumor response, and effect on metastasectomy. Am J Roentgenol 207(1):4–14CrossRefGoogle Scholar
  28. 28.
    MacDonald IC, Ragan DM, Schmidt EE, Groom AC (1987) Kinetics of red blood cell passage through interendothelial slits into venous sinuses in rat spleen, analyzed by in vivo microscopy. Microvasc Res 33:118–134CrossRefGoogle Scholar
  29. 29.
    Bratosin D, Mazurier J, Tissier JP et al (1998) Cellular and molecular mechanisms of senescent erythrocyte phagocytosis by macrophages. A review. Biochimie 80(2):173–195. (Review)CrossRefGoogle Scholar
  30. 30.
    Yin Y, Choi SC, Xu Z et al (2015) Normalization of CD41 T cell metabolism reverses lupus. Sci Transl Med 7:274ra18CrossRefGoogle Scholar
  31. 31.
    Ahn SS, Hwang SH, Jung SM et al (2017) Evaluation of spleen glucose metabolism using 18F-FDG PET/CT in patients with febrile autoimmune disease. J Nucl Med 58(3):507–513CrossRefGoogle Scholar
  32. 32.
    Sachpekidis C, Larribere L, Kopp-Schneider A, Haberkorn U, Hassel J, Dimitrakopoulou-Strauss A (2018) Benign lymphoid tissue changes as response to immunotherapy in metastatic melanoma patients: an 18F-FDG PET/CT study. Eur J Nucl Med Mol Imaging 45 (Suppl 1): S517 (Abstract EP-0551)Google Scholar
  33. 33.
    Ribas A, Benz MR, Allen-Auerbach MS et al (2010) Imaging of CTLA4 blockade-induced cell replication with (18)F-FLT PET in patients with advanced melanoma treated with tremelimumab. J Nucl Med 51:340–346CrossRefGoogle Scholar
  34. 34.
    Tsai KK, Pampaloni MH, Hope C et al (2016) Increased FDG avidity in lymphoid tissue associated with response to combined immune checkpoint blockade. J Immunother Cancer 4:58CrossRefGoogle Scholar
  35. 35.
    Pektor S, Hilscher L, Walzer KC et al (2018) In vivo imaging of the immune response upon systemic RNA cancer vaccination by FDG-PET. EJNMMI Res 8(1):80CrossRefGoogle Scholar
  36. 36.
    Eshghi N, Garland LL, Nia E, Betancourt R, Krupinski E, Kuo PH (2018) 18F-FDG PET/CT can predict development of thyroiditis due to immunotherapy for lung cancer. J Nucl Med Technol 46:260–264CrossRefGoogle Scholar
  37. 37.
    Phelps ME, Huang SC, Hoffman EJ et al (1979) Tomographic measurement of local cerebral glucose metabolic rate in humans with (F-18)2-fluoro-2-deoxy-d-glucose: validation of method. Ann Neurol 6:371–388CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Christos Sachpekidis
    • 1
    • 2
    Email author
  • Lionel Larribère
    • 3
    • 4
  • Annette Kopp-Schneider
    • 5
  • Jessica C. Hassel
    • 6
  • Antonia Dimitrakopoulou-Strauss
    • 1
  1. 1.Clinical Cooperation Unit Nuclear MedicineGerman Cancer Research Center (DKFZ)HeidelbergGermany
  2. 2.Department of Nuclear MedicineUniversity Hospital HeidelbergHeidelbergGermany
  3. 3.Skin Cancer UnitGerman Cancer Research Center (DKFZ)HeidelbergGermany
  4. 4.Department of Dermatology, Venereology and Allergology, University Medical Center MannheimRuprecht-Karl University of HeidelbergMannheimGermany
  5. 5.Department of BiostatisticsGerman Cancer Research Center (DKFZ)HeidelbergGermany
  6. 6.Department of Dermatology and National Center for Tumor DiseasesUniversity Hospital HeidelbergHeidelbergGermany

Personalised recommendations