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Title

Towards enhanced PET quantification in clinical oncology

Authors
Karakatsanis, Nicolas
Published in British Journal of Radiology. 2018, vol. 90, p. 20170508
Abstract Positron emission tomography (PET) has, since its inception, established itself as the imaging modality of choice for the in vivo quantitative assessment of molecular targets in a wide range of biochemical processes underlying tumour physiology. PET image quantification enables to ascertain a direct link between the time-varying activity concentration in organs/tissues and the fundamental parameters portraying the biological processes at the cellular level being assessed. However, the quantitative potential of PET may be affected by a number of factors related to physical effects, hardware and software system specifications, tracer kinetics, motion, scan protocol design and limitations in current image-derived PET metrics. Given the relatively large number of PET metrics reported in the literature, the selection of the best metric for fulfilling a specific task in a particular application is still a matter of debate. Quantitative PET has advanced elegantly during the last two decades and is now reaching the maturity required for clinical exploitation, particularly in oncology where it has the capability to open many avenues for clinical diagnosis, assessment of response to treatment and therapy planning. Therefore, the preservation and further enhancement of the quantitative features of PET imaging is crucial to ensure that the full clinical value of PET imaging modality is utilized in clinical oncology. Recent advancements in PET technology and methodology have paved the way for faster PET acquisitions of enhanced sensitivity to support the clinical translation of highly quantitative 4D parametric imaging methods in clinical oncology. In this report, we provide an overview of recent advances and future trends in quantitative PET imaging in the context of clinical oncology. The pros/cons of the various image-derived PET metrics will be discussed and the promise of novel methodologies will be highlighted.
Identifiers
PMID: 29164924
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Article (Published version) (4.6 MB) - public document Free access
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Research group Imagerie Médicale (TEP et TEMP) (542)
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ZAIDI, Habib, KARAKATSANIS, Nicolas. Towards enhanced PET quantification in clinical oncology. In: British Journal of Radiology, 2018, vol. 90, p. 20170508. https://archive-ouverte.unige.ch/unige:99864

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Deposited on : 2017-11-30

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