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Population Pharmacokinetic Approach Applied to Positron Emission Tomography: Computed Tomography for Tumor Tissue Identification in Patients with Glioma

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Abstract

Background and Aims

18F-fluoro-ethyl-tyrosine (FET) is a radiopharmaceutical used in positron emission tomography (PET)-computed tomography in patients with glioma. We propose an original approach combining a radiotracer-pharmacokinetic exploration performed at the voxel level (three-dimensional pixel) and voxel classification to identify tumor tissue. Our methodology was validated using the standard FET-PET approach and magnetic resonance imaging (MRI) data acquired according to the current clinical practices.

Methods

FET-PET and MRI data were retrospectively analyzed in ten patients presenting with progressive high-grade glioma. For FET-PET exploration, radioactivity acquisition started 15 min after radiotracer injection, and was measured each 5 min during 40 min. The tissue segmentation relies on population pharmacokinetic modeling with dependent individuals (voxels). This model can be approximated by a linear mixed-effects model. The tumor volumes estimated by our approach were compared with those determined with the current clinical techniques, FET-PET standard approach (i.e., a cumulated value of FET signal is computed during a time interval) and MRI sequences (T1 and T2/fluid-attenuated inversion recovery [FLAIR]), used as references. The T1 sequence is useful to identify highly vascular tumor and necrotic tissues, while the T2/FLAIR sequence is useful to isolate infiltration and edema tissue located around the tumor.

Results

With our kinetic approach, the volumes of tumor tissue were larger than the tissues identified by the standard FET-PET and MRI T1, while they were smaller than those determined with MRI T2/FLAIR.

Conclusion

Our results revealed the presence of suspected tumor voxels not identified by the standard PET approach.

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Acknowledgements

The authors are grateful to Prof. J. Woodley for help with the English language. The authors thank the two reviewers for their constructive suggestions, which greatly improved the quality of the article.

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Authors and Affiliations

  1. CRCT, Université de Toulouse, Inserm, UPS, Toulouse, France

    Peggy Gandia & Etienne Chatelut

  2. Department of Nuclear Medicine, UZ Brussel, Brussels, Belgium

    Cyril Jaudet, Hendrik Everaert & Johannes Heemskerk

  3. Department of Radiology, UZ Brussel, Brussels, Belgium

    Anne Marie Vanbinst & Johan de Mey

  4. Department of Neurosurgery, UZ Brussel, Brussels, Belgium

    Johnny Duerinck

  5. Department of Medical Oncology, UZ Brussel, Brussels, Belgium

    Bart Neyns

  6. Department of Radiotherapy, UZ Brussel, Brussels, Belgium

    Mark de Ridder

  7. Institut Claudius Regaud, Toulouse, France

    Etienne Chatelut

  8. Toxalim, Université de Toulouse, INRA, ENVT, 23 chemin des Capelles, BP 87614, 31076, Toulouse Cedex 3, France

    Peggy Gandia & Didier Concordet

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  1. Peggy Gandia
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Correspondence to Didier Concordet.

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No external funding was used in the preparation of this article.

Conflict of interest

Peggy Gandia, Cyril Jaudet, Hendrik Everaert, Johannes Heemskerk, Anne Marie Vanbinst, Johan de Mey, Johnny Duerinck, Bart Neyns, Mark De Ridder, Etienne Chatelut, and Didier Concordet declare that they have no conflicts of interest that might be relevant to the contents of this article.

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Gandia, P., Jaudet, C., Everaert, H. et al. Population Pharmacokinetic Approach Applied to Positron Emission Tomography: Computed Tomography for Tumor Tissue Identification in Patients with Glioma. Clin Pharmacokinet 56, 953–961 (2017). https://doi.org/10.1007/s40262-016-0490-4

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