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European Radiology

, Volume 25, Issue 8, pp 2214–2221 | Cite as

Evaluation of several FDG PET parameters for prediction of soft tissue tumour grade at primary diagnosis and recurrence

  • Wolfgang P. Fendler
  • Rebecca P. Chalkidis
  • Harun Ilhan
  • Thomas Knösel
  • Ken Herrmann
  • Rolf D. Issels
  • Peter Bartenstein
  • Clemens C. Cyran
  • Lars H. Lindner
  • Marcus Hacker
Nuclear Medicine

ABSTRACT

Objectives

This study evaluates the diagnostic accuracy of SUV-based parameters derived from [18 F]-2-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) in order to optimize non-invasive prediction of soft tissue tumour (STT) grade.

Methods

One hundred and twenty-nine lesions from 123 patients who underwent FDG-PET for primary staging (n = 79) or assessment of recurrence (n = 44) of STT were analyzed retrospectively. Histopathology was the reference standard for tumour grading. Absolute values and tumour-to-liver ratios of several standardized uptake value (SUV) parameters were correlated with tumour grading.

Results

At primary diagnosis SUVmax, SUVpeak, SUVmax/SUVliver and SUVpeak/SUVliver showed good correlation with tumour grade. SUVpeak (area under the receiver-operating-characteristic, AUC-ROC: 0.82) and SUVpeak/SUVliver (AUC-ROC: 0.82) separated best between low grade (WHO intermediate, grade 1 sarcoma, and low risk gastrointestinal stromal tumours, GISTs) and high grade (grade 2/3 sarcoma and intermediate/high risk GISTs) lesions: optimal threshold for SUVpeak/SUVliver was 2.4, which resulted in a sensitivity of 79 % and a specificity of 81 %. At disease recurrence, the AUC-ROC was <0.75 for each parameter.

Conclusions

A tumour SUVpeak of at least 2.4 fold mean liver uptake predicts high grade histopathology with good diagnostic accuracy at primary staging. At disease recurrence, FDG-PET does not reliably separate high and low grade lesions.

Key Points

Several SUV parameters accurately predict soft tissue sarcoma grade at primary diagnosis.

Tumour-to-liver ratios are of comparable value to absolute SUV parameters.

SUV peak /SUV liver >2.4 had 79 % sensitivity and 81 % specificity for high grade lesions.

At recurrence, FDG PET does not reliably indicate high grade sarcomas.

Keywords

Sensitivity and Specificity Sarcoma Positron-Emission Tomography Computed Tomography Fluorodeoxyglucose F18 Tumour grade 

Notes

ACKNOWLEDGMENTS

We thank Andreas Elsner for customizing the Hybrid Viewer 3D. The scientific guarantor of this publication is Wolfgang Peter Fendler, MD. The authors state that this work has not received any funding. One of the authors has significant statistical expertise. Institutional Review Board approval was obtained. Written informed consent was obtained from all subjects (patients) in this study. None of the study subjects or cohorts have been previously reported. Methodology: retrospective, diagnostic or prognostic study, performed at one institution.

Supplementary material

330_2015_3654_MOESM1_ESM.doc (2.7 mb)
ESM 1 (DOC 2722 kb)

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Copyright information

© European Society of Radiology 2015

Authors and Affiliations

  • Wolfgang P. Fendler
    • 1
    • 8
  • Rebecca P. Chalkidis
    • 1
  • Harun Ilhan
    • 1
  • Thomas Knösel
    • 2
  • Ken Herrmann
    • 3
  • Rolf D. Issels
    • 4
    • 5
  • Peter Bartenstein
    • 1
    • 5
  • Clemens C. Cyran
    • 6
  • Lars H. Lindner
    • 4
    • 5
  • Marcus Hacker
    • 7
  1. 1.Department of Nuclear MedicineLudwig-Maximilians-University of MunichMunichGermany
  2. 2.Institute of PathologyLudwig-Maximilians-University of MunichMunichGermany
  3. 3.Department of Nuclear MedicineJulius-Maximilians-University of WürzburgWürzburgGermany
  4. 4.Department of Internal Medicine IIILudwig-Maximilians-University of MunichMunichGermany
  5. 5.Comprehensive Cancer CenterLudwig-Maximilians-University of MunichMunichGermany
  6. 6.Department of Clinical RadiologyLudwig-Maximilians-University of MunichMunichGermany
  7. 7.Department of Nuclear MedicineVienna General HospitalViennaAustria
  8. 8.Department of Nuclear MedicineMunichGermany

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