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European Journal of Nuclear Medicine and Molecular Imaging

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12.01.2021 | Original Article

Assessing immune organs on ¹⁸F-FDG PET/CT imaging for therapy monitoring of immune checkpoint inhibitors: inter-observer variability, prognostic value and evolution during the treatment course of melanoma patients

verfasst von: Kevin Prigent, Charline Lasnon, Emilien Ezine, Mélanie Janson, Nicolas Coudrais, Elisa Joly, Laure Césaire, Andrea Stefan, Michel Depontville, Nicolas Aide

Erschienen in: European Journal of Nuclear Medicine and Molecular Imaging | Ausgabe 8/2021

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Abstract

Background

Immune checkpoint inhibitors (ICIs) have significantly improved survival in advanced melanoma. There is a need for robust biomarkers to identify patients who do not respond. We analysed 14 baseline ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) metrics and their evolution to assess their correlation with patient outcome, compared with 7 established biological markers and 7 clinical variables.

Methods

We conducted a retrospective monocentric observational study of 29 patients with advanced melanoma who underwent baseline ¹⁸F-FDG PET/CT, followed by an early monitoring PET/CT (iPET) scan after 1 month of treatment and follow-up studies at 3rd (M3PET) and 6th month (M6PET). ¹⁸F-FDG uptake in immune organs (spleen, bone marrow, ileocecal valve) and derived spleen-to-liver (SLR) and bone-to-liver (BLR) ratios were reviewed by two PET readers for reproducibility analysis purposes including 14 PET variables. The most reproducible indexes were used for evaluation as predictors of overall survival (OS) in comparison with PET response using imPERCIST5, whole-body metabolic active tumour volume (WB-MATV) and biological parameters (lactate dehydrogenases (LDH), reactive protein c (CRP), white blood count (WBC), absolute lymphocyte count (ALC), neutrophil to lymphocyte ratio (NLR) and derived neutrophils to lymphocyte ratio).

Results

Strong reproducibility’s (intraclass coefficients of correlation (ICC) > 0.90) were observed for spleen anterior SUV_peak, spleen MV, spleen TLG, spleen length and BLR_mean. ICC for SLR_mean and ileocecal SUV_mean were 0.86 and 0.65, respectively. In the 1-year OS 1 group, SLR_mean tended to increase at each time point to reach a significant difference at M6-PET (p = 0.019). The same trends were observed with spleen SUV_peak anterior and spleen length. In the 1-year OS 0 group, a significative increase of spleen length was found at iPET, as compared with baseline PET (p = 0.014) and M3-PET (p = 0.0239). Univariable Kaplan-Meier survival analysis found that i%var spleen length, M3%var SLR_mean, baseline LDH, i%var NLR and response at M6PET were all predictors of 1-year OS.

Conclusions

SLR_mean is recommended as a prognosticator in melanoma patients under immunotherapy: its increase greater than 25% at 3 months, compared with baseline, was associated with poor outcome after ICIs.

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Hodi FS, O'Day SJ, McDermott DF, Weber RW, Sosman JA, Haanen JB, et al. Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med. 2010;363:711–23. https://doi.org/10.1056/NEJMoa1003466.CrossRefPubMedPubMedCentral

Robert C, Schachter J, Long GV, Arance A, Grob JJ, Mortier L, et al. Pembrolizumab versus ipilimumab in advanced melanoma. N Engl J Med. 2015;372:2521–32. https://doi.org/10.1056/NEJMoa1503093.CrossRefPubMed

Herbst RS, Baas P, Kim DW, Felip E, Pérez-Gracia JL, Han JY, et al. Pembrolizumab versus docetaxel for previously treated, PD-L1-positive, advanced non-small-cell lung cancer (KEYNOTE-010): a randomised controlled trial. Lancet (London, England). 2016;387:1540–50. https://doi.org/10.1016/s0140-6736(15)01281-7.CrossRef

Tomita M, Yasui H, Higashikawa K, Nakajima K, Takakura H, Shiga T, et al. Anti PD-1 treatment increases [(18)F]FDG uptake by cancer cells in a mouse B16F10 melanoma model. EJNMMI Res. 2018;8:82. https://doi.org/10.1186/s13550-018-0433-1.CrossRefPubMedPubMedCentral

Sachpekidis C, Larribere L, Pan L, Haberkorn U, Dimitrakopoulou-Strauss A, Hassel JC. Predictive value of early 18F-FDG PET/CT studies for treatment response evaluation to ipilimumab in metastatic melanoma: preliminary results of an ongoing study. Eur J Nucl Med Mol Imaging. 2015;42:386–96. https://doi.org/10.1007/s00259-014-2944-y.CrossRefPubMed

Hodi FS, Hwu WJ, Kefford R, Weber JS, Daud A, Hamid O, et al. Evaluation of immune-related response criteria and RECIST v1.1 in patients with advanced melanoma treated with pembrolizumab. J Clin Oncol: Off J Am Soc Clin Oncol. 2016;34:1510–7. https://doi.org/10.1200/jco.2015.64.0391.CrossRef

Ito K, Teng R, Schoder H, Humm JL, Ni A, Michaud L, et al. (18)F-FDG PET/CT for Monitoring of ipilimumab therapy in patients with metastatic melanoma. Journal of nuclear medicine : official publication. Soc Nucl Med. 2019;60:335–41. https://doi.org/10.2967/jnumed.118.213652.CrossRef

Seban RD, Moya-Plana A, Antonios L, Yeh R, Marabelle A, Deutsch E, et al. Prognostic 18F-FDG PET biomarkers in metastatic mucosal and cutaneous melanoma treated with immune checkpoint inhibitors targeting PD-1 and CTLA-4. Eur J Nucl Med Mol Imaging. 2020. https://doi.org/10.1007/s00259-020-04757-3.

Ayati N, Sadeghi R, Kiamanesh Z, Lee ST, Zakavi SR, Scott AM. The value of (18)F-FDG PET/CT for predicting or monitoring immunotherapy response in patients with metastatic melanoma: a systematic review and meta-analysis. Eur J Nucl Med Mol Imaging. 2020. https://doi.org/10.1007/s00259-020-04967-9.

10.

Kolinger GD, Vallez Garcia D, Kramer GM, Frings V, Smit EF, de Langen AJ, et al. Repeatability of [(18)F]FDG PET/CT total metabolic active tumour volume and total tumour burden in NSCLC patients. EJNMMI research. 2019;9:14. https://doi.org/10.1186/s13550-019-0481-1.CrossRefPubMedPubMedCentral

11.

Lodge MA. Repeatability of SUV in Oncologic (18)F-FDG PET. J Nucl Med: Off Publ, Soc Nucl Med. 2017;58:523–32. https://doi.org/10.2967/jnumed.116.186353.CrossRef

12.

Yeh R, Trager MH, Rizk EM, Finkel GG, Barker LW, Carvajal RD, et al. FLT-PET at 6 weeks predicts response assessed by CT at 12 weeks in melanoma patients treated with pembrolizumab. Clin Nucl Med. 2020;45:267–75. https://doi.org/10.1097/rlu.0000000000002967.CrossRefPubMedPubMedCentral

13.

Aide N, Hicks RJ, Le Tourneau C, Lheureux S, Fanti S, Lopci E. FDG PET/CT for assessing tumour response to immunotherapy: report on the EANM symposium on immune modulation and recent review of the literature. Eur J Nucl Med Mol Imaging. 2019;46:238–50. https://doi.org/10.1007/s00259-018-4171-4.CrossRefPubMed

14.

Wong A, Callahan J, Keyaerts M, Neyns B, Mangana J, Aberle S, et al. (18)F-FDG PET/CT based spleen to liver ratio associates with clinical outcome to ipilimumab in patients with metastatic melanoma. Cancer Imaging: Off Publ Int Cancer Imaging Soc. 2020;20:36. https://doi.org/10.1186/s40644-020-00313-2.CrossRef

15.

Seban RD, Nemer JS, Marabelle A, Yeh R, Deutsch E, Ammari S, et al. Prognostic and theranostic 18F-FDG PET biomarkers for anti-PD1 immunotherapy in metastatic melanoma: association with outcome and transcriptomics. Eur J Nucl Med Mol Imaging. 2019;46:2298–310. https://doi.org/10.1007/s00259-019-04411-7.CrossRefPubMed

16.

Dercle L, Seban RD, Lazarovici J, Schwartz LH, Houot R, Ammari S, et al. (18)F-FDG PET and CT scans detect new imaging patterns of response and progression in patients with Hodgkin lymphoma treated by anti-programmed death 1 immune checkpoint inhibitor. J Nucl Med: Off Publ Soc Nucl Med. 2018;59:15–24. https://doi.org/10.2967/jnumed.117.193011.CrossRef

17.

Capone M, Giannarelli D, Mallardo D, Madonna G, Festino L, Grimaldi AM, et al. Baseline neutrophil-to-lymphocyte ratio (NLR) and derived NLR could predict overall survival in patients with advanced melanoma treated with nivolumab. J Immunother Cancer. 2018;6:74. https://doi.org/10.1186/s40425-018-0383-1.CrossRefPubMedPubMedCentral

18.

Wagner NB, Forschner A, Leiter U, Garbe C, Eigentler TK. S100B and LDH as early prognostic markers for response and overall survival in melanoma patients treated with anti-PD-1 or combined anti-PD-1 plus anti-CTLA-4 antibodies. Br J Cancer. 2018;119:339–46. https://doi.org/10.1038/s41416-018-0167-x.CrossRefPubMedPubMedCentral

19.

Boellaard R, Delgado-Bolton R, Oyen WJ, Giammarile F, Tatsch K, Eschner W, et al. FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0. Eur J Nucl Med Mol Imaging. 2015;42:328–54. https://doi.org/10.1007/s00259-014-2961-x.CrossRefPubMed

20.

Aide N, Lasnon C, Veit-Haibach P, Sera T, Sattler B, Boellaard R. EANM/EARL harmonization strategies in PET quantification: from daily practice to multicentre oncological studies. Eur J Nucl Med Mol Imaging. 2017;44:17–31. https://doi.org/10.1007/s00259-017-3740-2.CrossRefPubMedPubMedCentral

21.

Nioche C, Orlhac F, Boughdad S, Reuzé S, Goya-Outi J, Robert C, et al. LIFEx: a freeware for radiomic feature calculation in multimodality imaging to accelerate advances in the characterization of tumor heterogeneity. Cancer Res. 2018;78:4786–9. https://doi.org/10.1158/0008-5472.Can-18-0125.CrossRefPubMed

22.

Bezerra AS, D'Ippolito G, Faintuch S, Szejnfeld J, Ahmed M. Determination of splenomegaly by CT: is there a place for a single measurement? AJR Am J Roentgenol. 2005;184:1510–3. https://doi.org/10.2214/ajr.184.5.01841510.CrossRefPubMed

23.

Mekki A, Dercle L, Lichtenstein P, Marabelle A, Michot JM, Lambotte O, et al. Detection of immune-related adverse events by medical imaging in patients treated with anti-programmed cell death 1. Eur J Cancer (Oxf, Engl: 1990). 2018;96:91–104. https://doi.org/10.1016/j.ejca.2018.03.006.CrossRef

24.

Mekki A, Dercle L, Lichtenstein P, Nasser G, Marabelle A, Champiat S, et al. Machine learning defined diagnostic criteria for differentiating pituitary metastasis from autoimmune hypophysitis in patients undergoing immune checkpoint blockade therapy. Eur J Cancer (Oxf, Engl: 1990). 2019;119:44–56. https://doi.org/10.1016/j.ejca.2019.06.020.CrossRef

25.

Prigent K, Aide N. (18)F-Fludeoxyglucose PET/computed tomography for assessing tumor response to immunotherapy and detecting immune-related side effects: a checklist for the PET reader. PET Clin. 2020;15:1–10. https://doi.org/10.1016/j.cpet.2019.08.006.CrossRefPubMed

26.

Barrington SF, Meignan M. Time to Prepare for Risk Adaptation in Lymphoma by Standardizing Measurement of Metabolic Tumor Burden. J Nucl Med: Off Publ Soc Nucl Med. 2019;60:1096–102. https://doi.org/10.2967/jnumed.119.227249.CrossRef

27.

Breiman L. Classification and regression trees. New York: Routledge; 1984.

28.

Zhao X, Subramanian S. Intrinsic resistance of solid tumors to immune checkpoint blockade therapy. Cancer Res. 2017;77:817–22. https://doi.org/10.1158/0008-5472.Can-16-2379.CrossRefPubMed

29.

Tartari F, Santoni M, Burattini L, Mazzanti P, Onofri A, Berardi R. Economic sustainability of anti-PD-1 agents nivolumab and pembrolizumab in cancer patients: recent insights and future challenges. Cancer Treat Rev. 2016;48:20–4. https://doi.org/10.1016/j.ctrv.2016.06.002.CrossRefPubMed

30.

Wong ANM, McArthur GA, Hofman MS, Hicks RJ. 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. 2017;44:67–77. https://doi.org/10.1007/s00259-017-3691-7.CrossRefPubMed

31.

Mebius RE, Kraal G. Structure and function of the spleen. Nat Rev Immunol. 2005;5:606–16. https://doi.org/10.1038/nri1669.CrossRefPubMed

32.

Salaun PY, Gastinne T, Bodet-Milin C, Campion L, Cambefort P, Moreau A, et al. Analysis of 18F-FDG PET diffuse bone marrow uptake and splenic uptake in staging of Hodgkin's lymphoma: a reflection of disease infiltration or just inflammation? Eur J Nucl Med Mol Imaging. 2009;36:1813–21. https://doi.org/10.1007/s00259-009-1183-0.CrossRefPubMed

33.

Chen A, Mokrane FZ, Schwartz LH, Morschhauser F, Stamatoullas A, Schiano de Colella JM, et al. Early (18)F-FDG PET/CT response predicts survival in relapsed or refractory Hodgkin lymphoma treated with nivolumab. J Nucl Med. 2020;61:649–54. https://doi.org/10.2967/jnumed.119.232827.CrossRefPubMed

34.

Mokrane FZ, Chen A, Schwartz LH, Morschhauser F, Stamatoullas A, Schiano de Colella JM, et al. Performance of CT Compared with (18)F-FDG PET in predicting the efficacy of nivolumab in relapsed or refractory Hodgkin lymphoma. Radiology. 2020;295:651–61. https://doi.org/10.1148/radiol.2020192056.CrossRefPubMed

35.

Dercle L, Ammari S, Seban RD, Schwartz LH, Houot R, Labaied N, et al. Kinetics and nadir of responses to immune checkpoint blockade by anti-PD1 in patients with classical Hodgkin lymphoma. Eur J Cancer (Oxf, Engl: 1990). 2018;91:136–44. https://doi.org/10.1016/j.ejca.2017.12.015.CrossRef

36.

Dercle L, Mokrane FZ, Schiano de Colella JM, Stamatoullas A, Morschhauser F, Brice P, et al. Unconventional immune-related phenomena observed using 18F-FDG PET/CT in Hodgkin lymphoma treated with anti PD-1 monoclonal antibodies. Eur J Nucl Med Mol Imaging. 2019;46:1391–2. https://doi.org/10.1007/s00259-019-04310-x.CrossRefPubMed

37.

Kim SY, Moon CM, Yoon HJ, Kim BS, Lim JY, Kim TO, et al. Diffuse splenic FDG uptake is predictive of clinical outcomes in patients with rectal cancer. Sci Rep. 2019;9:1313. https://doi.org/10.1038/s41598-018-35912-4.CrossRefPubMedPubMedCentral

38.

Oliveira M, Lasnon C, Nganoa C, Gac AC, Damaj G, Aide N. Comprehensive analysis of the influence of G-CSF on the biodistribution of (18)F-FDG in lymphoma patients: insights for PET/CT scheduling. EJNMMI Res. 2019;9:79. https://doi.org/10.1186/s13550-019-0546-1.CrossRefPubMedPubMedCentral

39.

Chang CH, Qiu J, O'Sullivan D, Buck MD, Noguchi T, Curtis JD, et al. Metabolic competition in the tumor microenvironment is a driver of cancer progression. Cell. 2015;162:1229–41. https://doi.org/10.1016/j.cell.2015.08.016.CrossRefPubMedPubMedCentral

40.

Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144:646–74. https://doi.org/10.1016/j.cell.2011.02.013.CrossRefPubMed

41.

Ostrand-Rosenberg S, Sinha P. Myeloid-derived suppressor cells: linking inflammation and cancer. J Immunol (Baltimore, Md : 1950). 2009;182:4499–506. https://doi.org/10.4049/jimmunol.0802740.CrossRef

42.

Jordan KR, Kapoor P, Spongberg E, Tobin RP, Gao D, Borges VF, et al. Immunosuppressive myeloid-derived suppressor cells are increased in splenocytes from cancer patients. Cancer Immunol Immunother. 2017;66:503–13. https://doi.org/10.1007/s00262-016-1953-z.CrossRefPubMedPubMedCentral

43.

Kotwal A, Kottschade L, Ryder M. PD-L1 inhibitor-induced thyroiditis is associated with better overall survival in cancer patients. Thyroid: Off J Am Thyroid Assoc. 2020;30:177–84. https://doi.org/10.1089/thy.2019.0250.CrossRef

44.

Nobashi T, Baratto L, Reddy SA, Srinivas S, Toriihara A, Hatami N, et al. Predicting response to immunotherapy by evaluating tumors, lymphoid cell-rich organs, and immune-related adverse events using FDG-PET/CT. Clin Nucl Med. 2019;44:e272–e9. https://doi.org/10.1097/rlu.0000000000002453.CrossRefPubMed

45.

Wachsmann JW, Ganti R, Peng F. Immune-mediated disease in ipilimumab immunotherapy of melanoma with FDG PET-CT. Acad Radiol. 2017;24:111–5. https://doi.org/10.1016/j.acra.2016.08.005.CrossRefPubMed

46.

Iravani A, Osman MM, Weppler AM, Wallace R, Galligan A, Lasocki A, et al. FDG PET/CT for tumoral and systemic immune response monitoring of advanced melanoma during first-line combination ipilimumab and nivolumab treatment. Eur J Nucl Med Mol Imaging. 2020. https://doi.org/10.1007/s00259-020-04815-w.

47.

Kamarudin AN, Cox T, Kolamunnage-Dona R. Time-dependent ROC curve analysis in medical research: current methods and applications. BMC Med Res Methodol. 2017;17:53. https://doi.org/10.1186/s12874-017-0332-6.CrossRefPubMedPubMedCentral

Titel: Assessing immune organs on 18F-FDG PET/CT imaging for therapy monitoring of immune checkpoint inhibitors: inter-observer variability, prognostic value and evolution during the treatment course of melanoma patients
verfasst von: Kevin Prigent
Charline Lasnon
Emilien Ezine
Mélanie Janson
Nicolas Coudrais
Elisa Joly
Laure Césaire
Andrea Stefan
Michel Depontville
Nicolas Aide
Publikationsdatum: 12.01.2021
Verlag: Springer Berlin Heidelberg
Erschienen in: European Journal of Nuclear Medicine and Molecular Imaging / Ausgabe 8/2021
Print ISSN: 1619-7070
Elektronische ISSN: 1619-7089
DOI: https://doi.org/10.1007/s00259-020-05103-3

Live-Webinar "Chronische Unterbauch- und Viszeralschmerzen in der Praxis managen"

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Assessing immune organs on ¹⁸F-FDG PET/CT imaging for therapy monitoring of immune checkpoint inhibitors: inter-observer variability, prognostic value and evolution during the treatment course of melanoma patients

Abstract

Background

Methods

Results

Conclusions

Live-Webinar "Chronische Unterbauch- und Viszeralschmerzen in der Praxis managen"

Springer Medizin

Abstract

Background

Methods

Results

Conclusions

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