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Differentiation of treatment-related changes from tumour progression: a direct comparison between dynamic FET PET and ADC values obtained from DWI MRI

  • Jan-Michael Werner
  • Gabriele Stoffels
  • Thorsten Lichtenstein
  • Jan Borggrefe
  • Philipp Lohmann
  • Garry Ceccon
  • Nadim J. Shah
  • Gereon R. Fink
  • Karl-Josef Langen
  • Christoph Kabbasch
  • Norbert GalldiksEmail author
Original Article
  • 271 Downloads
Part of the following topical collections:
  1. Neurology

Abstract

Background

Following brain cancer treatment, the capacity of anatomical MRI to differentiate neoplastic tissue from treatment-related changes (e.g., pseudoprogression) is limited. This study compared apparent diffusion coefficients (ADC) obtained by diffusion-weighted MRI (DWI) with static and dynamic parameters of O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET for the differentiation of treatment-related changes from tumour progression.

Patients and methods

Forty-eight pretreated high-grade glioma patients with anatomical MRI findings suspicious for progression (median time elapsed since last treatment was 16 weeks) were investigated using DWI and dynamic FET PET. Maximum and mean tumour-to-brain ratios (TBRmax, TBRmean) as well as dynamic parameters (time-to-peak and slope values) of FET uptake were calculated. For mean ADC calculation, regions-of-interest analyses were performed on ADC maps calculated from DWI coregistered with the contrast-enhanced MR image. Diagnoses were confirmed neuropathologically (21%) or clinicoradiologically. Diagnostic performance was evaluated using receiver-operating-characteristic analyses or Fisher’s exact test for a combinational approach.

Results

Ten of 48 patients had treatment-related changes (21%). The diagnostic performance of FET PET was significantly higher (threshold for both TBRmax and TBRmean, 1.95; accuracy, 83%; AUC, 0.89 ± 0.05; P < 0.001) than that of ADC values (threshold ADC, 1.09 × 10−3 mm2/s; accuracy, 69%; AUC, 0.73 ± 0.09; P = 0.13). The addition of static FET PET parameters to ADC values increased the latter’s accuracy to 89%. The highest accuracy was achieved by combining static and dynamic FET PET parameters (93%). Moreover, in contrast to ADC values, TBRs <1.95 at suspected progression predicted a significantly longer survival (P = 0.01).

Conclusions

Data suggest that static and dynamic FET PET provide valuable information concerning the differentiation of early treatment-related changes from tumour progression and outperform ADC measurement for this highly relevant clinical question.

Keywords

Amino acid PET Glioblastoma Pseudoprogression Tumour relapse Diffusion-weighted imaging 

Notes

Funding

The Wilhelm-Sander Stiftung, Germany, supported this work.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed written consent was obtained from all individual participants included in the study.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Jan-Michael Werner
    • 1
  • Gabriele Stoffels
    • 2
  • Thorsten Lichtenstein
    • 3
  • Jan Borggrefe
    • 3
  • Philipp Lohmann
    • 2
  • Garry Ceccon
    • 1
  • Nadim J. Shah
    • 2
    • 4
  • Gereon R. Fink
    • 1
    • 2
  • Karl-Josef Langen
    • 2
    • 5
  • Christoph Kabbasch
    • 3
  • Norbert Galldiks
    • 1
    • 2
    • 6
    • 7
    • 8
    Email author
  1. 1.Department of Neurology, Faculty of Medicine and University Hospital CologneUniversity of CologneCologneGermany
  2. 2.Institute of Neuroscience and Medicine (INM-3, -4)Research Center JuelichJuelichGermany
  3. 3.Department of Neuroradiology, Faculty of Medicine and University Hospital CologneUniversity of CologneCologneGermany
  4. 4.Department of NeurologyUniversity Hospital AachenAachenGermany
  5. 5.Department of Nuclear MedicineUniversity Hospital AachenAachenGermany
  6. 6.Center of Integrated Oncology (CIO)Universities of Aachen, Bonn, Cologne, and DüsseldorfCologneGermany
  7. 7.Institute of Neuroscience and Medicine (INM-3)Research Center JuelichJuelichGermany
  8. 8.Department of NeurologyUniversity Hospital CologneCologneGermany

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