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Molecular Imaging and Biology

, Volume 20, Issue 4, pp 641–649 | Cite as

Role of CT Density in PET/CT-Based Assessment of Lymphoma

  • Paul Flechsig
  • Christina Walker
  • Clemens Kratochwil
  • Laila König
  • Andrei Iagura
  • Jan Moltz
  • Tim Holland-Letz
  • Hans-Ulrich Kauczor
  • Uwe Haberkorn
  • Frederik L. Giesel
Research Article

Abstract

Purpose

In patients with Hodgkin (HL) and non-Hodgkin lymphoma (NHL), primary staging, as well as intermediate and late response assessment, is often performed by integrated 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography/X-ray computed tomography (PET/CT). The purpose of this analysis was to evaluate if findings in patients with histopathologically proven HL or NHL might correlate with semi-automated density measurements of target lesions (TLs) in the CT component of the integrated PET/CT examination.

Procedures

After approval by the institutional review board, 176 lymph nodes (LN) in 90 PET/CT examinations of 90 patients were retrospectively analyzed (HL, 108 TLs out of 55 patients; NHL, 68 TLs out of 35 patients). PET/CT was performed for reasons of primary staging, response evaluation as interim PET, or as final examination after therapy, according to the clinical schedule. Analyses of TLs were performed on the basis of tracer uptake (SUV) 60 min after tracer injection and volumetric CT histogram analysis in non-contrast-enhanced CT.

Results

All patients were diagnosed with HL or NHL in a pretreatment biopsy. Prior to therapy induction, staging of all patients was performed using contrast-enhanced CT of the neck to the pelvis, or by [18F]FDG PET/CT. Of the 176 TLs, 119 were classified as malignant, and 57 were benign. Malignant TLs had significantly higher CT density values compared to benign (p < 0.01).

Conclusion

Density measurements of TLs in patients with HL and NHL correlate with the dignity of TLs and might therefore serve as a complementary surrogate parameter for the differentiation between malignant and benign TLs. A possible density threshold in clinical routine might be a 20-Hounsfield units (HU) cutoff value to rule out benignancy in TLs that are above the 20-HU threshold.

Key words

Staging FDG-PET-CT Lymphoma Deauville criteria 

Notes

Compliance with Ethical Standards

The study was approved by the institutional review board and conducted according to the guidelines of the institutional review board and to good clinical practice according to the ethical principles that have their origin in the Declaration of Helsinki.

Conflict of Interest

The authors declare that they have no conflict of interest.

References

  1. 1.
    Barrington SF, Kluge R (2017) FDG PET for therapy monitoring in Hodgkin and non-Hodgkin lymphomas. Eur J Nucl Med Mol Imaging 44(Suppl 1):97–110.  https://doi.org/10.1007/s00259-017-3690-8 CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Follows GA, Ardeshna KM, Barrington SF, Culligan DJ, Hoskin PJ, Linch D, Sadullah S, Williams MV, Wimperis JZ, The British Committee for Standards in Haematology (2014) Guidelines for the first line management of classical Hodgkin lymphoma. Br J Haematol 166(1):34–49.  https://doi.org/10.1111/bjh.12878 CrossRefPubMedGoogle Scholar
  3. 3.
    Fallanca F, Alongi P, Incerti E, Gianolli L, Picchio M, Kayani I, Bomanji J (2016) Diagnostic accuracy of FDG PET/CT for clinical evaluation at the end of treatment of HL and NHL: a comparison of the Deauville Criteria (DC) and the International Harmonization Project Criteria (IHPC). Eur J Nucl Med Mol Imaging 43(10):1837–1848.  https://doi.org/10.1007/s00259-016-3390-9 CrossRefPubMedGoogle Scholar
  4. 4.
    Barrington SF, Qian W, Somer EJ, Franceschetto A, Bagni B, Brun E, Almquist H, Loft A, Højgaard L, Federico M, Gallamini A, Smith P, Johnson P, Radford J, O’Doherty MJ (2010) Concordance between four European centres of PET reporting criteria designed for use in multicentre trials in Hodgkin lymphoma. Eur J Nucl Med Mol Imaging 37(10):1824–1833.  https://doi.org/10.1007/s00259-010-1490-5 CrossRefPubMedGoogle Scholar
  5. 5.
    Furth C, Meseck RM, Steffen IG, Schoenberger S, Denecke T, Henze G, Hautzel H, Hofheinz F, Großer O, Hundsdoerfer P, Amthauer H, Ruf J (2012) SUV-measurements and patient-specific corrections in pediatric Hodgkin-lymphoma: is there a benefit for PPV in early response assessment by FDG-PET? Pediatr Blood Cancer 59(3):475–480.  https://doi.org/10.1002/pbc.24047 CrossRefPubMedGoogle Scholar
  6. 6.
    Biggi A, Gallamini A, Chauvie S, Hutchings M, Kostakoglu L, Gregianin M, Meignan M, Malkowski B, Hofman MS, Barrington SF (2013) International validation study for interim PET in ABVD-treated, advanced-stage Hodgkin lymphoma: interpretation criteria and concordance rate among reviewers. J Nucl Med 54(5):683–690.  https://doi.org/10.2967/jnumed.112.110890 CrossRefPubMedGoogle Scholar
  7. 7.
    Le Roux PY, Gastinne T, Le Gouill S, Nowak E, Bodet-Milin C, Querellou S, Mahe B, Dubruille V, Blin N, Salaun PY, Bodere-Kraeber F (2011) Prognostic value of interim FDG PET/CT in Hodgkin’s lymphoma patients treated with interim response-adapted strategy: comparison of International Harmonization Project (IHP), Gallamini and London criteria. Eur J Nucl Med Mol Imaging 38(6):1064–1071.  https://doi.org/10.1007/s00259-011-1741-0 CrossRefPubMedGoogle Scholar
  8. 8.
    Juweid ME, Stroobants S, Hoekstra OS, Mottaghy FM, Dietlein M, Guermazi A, Wiseman GA, Kostakoglu L, Scheidhauer K, Buck A, Naumann R, Spaepen K, Hicks RJ, Weber WA, Reske SN, Schwaiger M, Schwartz LH, Zijlstra JM, Siegel BA, Cheson BD, Imaging Subcommittee of International Harmonization Project in Lymphoma (2007) Use of positron emission tomography for response assessment of lymphoma: consensus of the Imaging Subcommittee of International Harmonization Project in lymphoma. J Clin Oncol 25(5):571–578.  https://doi.org/10.1200/JCO.2006.08.2305 CrossRefPubMedGoogle Scholar
  9. 9.
    Giesel FL, Schneider F, Kratochwil C, Rath D, Moltz J, Holland-Letz T, Kauczor HU, Schwartz LH, Haberkorn U, Flechsig P (2017) Correlation between SUVmax and CT radiomic analysis using lymph node density in PET/CT-based lymph node staging. J Nucl Med 58(2):282–287.  https://doi.org/10.2967/jnumed.116.179648 CrossRefPubMedGoogle Scholar
  10. 10.
    Lambin P, Rios-Velazquez E, Leijenaar R, Carvalho S, van Stiphout RGPM, Granton P, Zegers CML, Gillies R, Boellard R, Dekker A, Aerts HJWL (2012) Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer 48(4):441–446.  https://doi.org/10.1016/j.ejca.2011.11.036 CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Avanzo M, Stancanello J, El Naqa I (2017) Beyond imaging: the promise of radiomics. Phys Med 38:122–139.  https://doi.org/10.1016/j.ejmp.2017.05.071 CrossRefPubMedGoogle Scholar
  12. 12.
    Flechsig P, Kratochwil C, Schwartz LH, Rath D, Moltz J, Antoch G, Heussel CP, Rieser M, Warth A, Zabeck H, Kauczor HU, Haberkorn U, Giesel FL (2014) Quantitative volumetric CT-histogram analysis in N-staging of 18F-FDG-equivocal patients with lung cancer. J Nucl Med 55(4):559–564.  https://doi.org/10.2967/jnumed.113.128504 CrossRefPubMedGoogle Scholar
  13. 13.
    Shao T, Yu L, Li Y, Chen M (2015) Density and SUV ratios from PET/CT in the detection of mediastinal lymph node metastasis in non-small cell lung cancer. Zhongguo Fei Ai Za Zhi 18(3):155–160.  https://doi.org/10.3779/j.issn.1009-3419.2015.03.05 PubMedCrossRefGoogle Scholar
  14. 14.
    Pfluger T, Melzer HI, Schneider V, la Fougere C, Coppenrath E, Berking C, Bartenstein P, Weiss M (2011) PET/CT in malignant melanoma: contrast-enhanced CT versus plain low-dose CT. Eur J Nucl Med Mol Imaging 38(5):822–831.  https://doi.org/10.1007/s00259-010-1702-z CrossRefPubMedGoogle Scholar
  15. 15.
    Goeckenjan G, Sitter H, Thomas M, Branscheid D, Flentje M, Griesinger F, Niederle N, Stuschke M, Blum T, Deppermann KM, Ficker J, Freitag L, Lübbe A, Reinhold T, Späth-Schwalbe E, Ukena D, Wickert M, Wolf M, Andreas S, Auberger T, Baum R, Baysal B, Beuth J, Bickeböller H, Böcking A, Bohle R, Brüske I, Burghuber O, Dickgreber N, Diederich S, Dienemann H, Eberhardt W, Eggeling S, Fink T, Fischer B, Franke M, Friedel G, Gauler T, Gütz S, Hautmann H, Hellmann A, Hellwig D, Herth F, Heußel C, Hilbe W, Hoffmeyer F, Horneber M, Huber R, Hübner J, Kauczor HU, Kirchbacher K, Kirsten D, Kraus T, Lang S, Martens U, Mohn-Staudner A, Müller KM, Müller-Nordhorn J, Nowak D, Ochmann U, Passlick B, Petersen I, Pirker R, Pokrajac B, Reck M, Riha S, Rübe C, Schmittel A, Schönfeld N, Schütte W, Serke M, Stamatis G, Steingräber M, Steins M, Stoelben E, Swoboda L, Teschler H, Tessen H, Weber M, Werner A, Wichmann HE, Irlinger Wimmer E, Witt C, Worth H (2011) Prevention, diagnosis, therapy, and follow-up of lung cancer. Interdisciplinary guideline of the German Respiratory Society and the German Cancer Society—abridged version. Pneumologie 65(08):e51–e75.  https://doi.org/10.1055/s-0030-1256562 CrossRefPubMedGoogle Scholar
  16. 16.
    Flechsig P, Zechmann CM, Schreiweis J, Kratochwil C, Rath D, Schwartz LH, Schlemmer HP, Kauczor HU, Haberkorn U, Giesel FL (2015) Qualitative and quantitative image analysis of CT and MR imaging in patients with neuroendocrine liver metastases in comparison to (68)Ga-DOTATOC PET. Eur J Radiol 84(8):1593–1600.  https://doi.org/10.1016/j.ejrad.2015.04.009 CrossRefPubMedGoogle Scholar
  17. 17.
    Giesel FL, Kratochwil C, Mehndiratta A, Wulfert S, Moltz JH, Zechmann CM, Kauczor HU, Haberkorn U, Ley S (2012) Comparison of neuroendocrine tumor detection and characterization using DOTATOC-PET in correlation with contrast enhanced CT and delayed contrast enhanced MRI. Eur J Radiol 81(10):2820–2825.  https://doi.org/10.1016/j.ejrad.2011.11.007 CrossRefPubMedGoogle Scholar
  18. 18.
    Moltz JH, Bornemann L, Kuhnigk JM et al (2009) Advanced segmentation techniques for lung nodules, liver metastases, and enlarged lymph nodes in CT scans. J-STSP 3:122–134Google Scholar
  19. 19.
    Hajian-Tilaki K (2013) Receiver operating characteristic (ROC) curve analysis for medical diagnostic test evaluation. Caspian J Intern Med 4(2):627–635PubMedPubMedCentralGoogle Scholar
  20. 20.
    Flechsig P, Choyke P, Kratochwil C, Warth A, Antoch G, Holland Letz T, Rath D, Eichwald V, Huber PE, Kauczor HU, Haberkorn U, Giesel FL (2016) Increased X-ray attenuation in malignant vs. benign mediastinal nodes in an orthotopic model of lung cancer. Diagn Interv Radiol 22(1):35–39.  https://doi.org/10.5152/dir.2015.15220 CrossRefPubMedGoogle Scholar
  21. 21.
    Jensen TH, Bech M, Binderup T, Böttiger A, David C, Weitkamp T, Zanette I, Reznikova E, Mohr J, Rank F, Feidenhans’l R, Kjær A, Højgaard L, Pfeiffer F (2013) Imaging of metastatic lymph nodes by X-ray phase-contrast micro-tomography. PLoS One 8(1):e54047.  https://doi.org/10.1371/journal.pone.0054047 CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Puesken M, Buerke B, Gerss J, Frisch B, Beyer F, Weckesser M, Seifarth H, Heindel W, Wessling J (2010) Prediction of lymph node manifestations in malignant lymphoma: significant role of volumetric compared with established metric lymph node analysis in multislice computed tomography. J Comput Assist Tomogr 34(4):564–569.  https://doi.org/10.1097/RCT.0b013e3181db2901 CrossRefPubMedGoogle Scholar
  23. 23.
    Bryant AS, Cerfolio RJ (2006) The maximum standardized uptake values on integrated FDG-PET/CT is useful in differentiating benign from malignant pulmonary nodules. Ann Thorac Surg 82(3):1016–1020.  https://doi.org/10.1016/j.athoracsur.2006.03.095 CrossRefPubMedGoogle Scholar
  24. 24.
    Brown RS, Leung JY, Kison PV, Zasadny KR, Flint A, Wahl RL (1999) Glucose transporters and FDG uptake in untreated primary human non-small cell lung cancer. J Nucl Med 40(4):556–565PubMedGoogle Scholar
  25. 25.
    Cuaron J, Dunphy M, Rimner A (2013) Role of FDG-PET scans in staging, response assessment, and follow-up care for non-small cell lung cancer. Front Oncol 3.  https://doi.org/10.3389/fonc.2012.00208

Copyright information

© World Molecular Imaging Society 2017

Authors and Affiliations

  • Paul Flechsig
    • 1
    • 2
  • Christina Walker
    • 1
  • Clemens Kratochwil
    • 1
  • Laila König
    • 3
  • Andrei Iagura
    • 4
  • Jan Moltz
    • 5
  • Tim Holland-Letz
    • 6
  • Hans-Ulrich Kauczor
    • 2
    • 7
  • Uwe Haberkorn
    • 1
    • 2
    • 8
  • Frederik L. Giesel
    • 1
    • 2
    • 8
    • 9
  1. 1.Department of Nuclear MedicineUniversity Hospital HeidelbergHeidelbergGermany
  2. 2.Translational Lung Research Center Heidelberg, Member of the German Center for Lung Research DZLHeidelbergGermany
  3. 3.Department of Radiation OncologyUniversity Hospital HeidelbergHeidelbergGermany
  4. 4.Division of Nuclear Medicine and Molecular ImagingStanford UniversityStanfordUSA
  5. 5.Fraunhofer MEVISInstitute for Medical Image ComputingBremenGermany
  6. 6.Department of BiostatisticsGerman Cancer Research CenterHeidelbergGermany
  7. 7.Department of Diagnostic and Interventional RadiologyUniversity Hospital HeidelbergHeidelbergGermany
  8. 8.Clinical Cooperation Unit, Department of Nuclear MedicineDKFZHeidelbergGermany
  9. 9.Department of Radiology, New York Presbyterian HospitalColumbia University Medical CentreNew YorkUSA

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