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Advances in PET imaging of cancer

Nature Reviews Cancer volume 23, pages 474–490 (2023)Cite this article

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Abstract

Molecular imaging has experienced enormous advancements in the areas of imaging technology, imaging probe and contrast development, and data quality, as well as machine learning-based data analysis. Positron emission tomography (PET) and its combination with computed tomography (CT) or magnetic resonance imaging (MRI) as a multimodality PET–CT or PET–MRI system offer a wealth of molecular, functional and morphological data with a single patient scan. Despite the recent technical advances and the availability of dozens of disease-specific contrast and imaging probes, only a few parameters, such as tumour size or the mean tracer uptake, are used for the evaluation of images in clinical practice. Multiparametric in vivo imaging data not only are highly quantitative but also can provide invaluable information about pathophysiology, receptor expression, metabolism, or morphological and functional features of tumours, such as pH, oxygenation or tissue density, as well as pharmacodynamic properties of drugs, to measure drug response with a contrast agent. It can further quantitatively map and spatially resolve the intertumoural and intratumoural heterogeneity, providing insights into tumour vulnerabilities for target-specific therapeutic interventions. Failure to exploit and integrate the full potential of such powerful imaging data may lead to a lost opportunity in which patients do not receive the best possible care. With the desire to implement personalized medicine in the cancer clinic, the full comprehensive diagnostic power of multiplexed imaging should be utilized.

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Fig. 1: The next generation of total-body PET scanners.
Fig. 2: PET–MRI of a patient with glioblastoma after combined anticancer treatment with external beam radiation and immune checkpoint inhibitor therapy.
Fig. 3: Towards converging in vitro and in vivo data for cancer diagnosis.
Fig. 4: Clinically established and next-generation PET tracers under development to image tumour immunity, stress responses, the microenvironment and metabolism.
Fig. 5: A proposed strategy for advanced multimodal cancer imaging.

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Acknowledgements

The authors are supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy — EXC 2180-390900677: Cluster of Excellence iFIT ‘Image-Guided and Functionally Instructed Tumour Therapies’.

Author information

Author notes

  1. These authors contributed equally: Johannes Schwenck, Dominik Sonanini, Jonathan M. Cotton.

Authors and Affiliations

  1. Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University of Tübingen, Tübingen, Germany

    Johannes Schwenck, Dominik Sonanini, Jonathan M. Cotton & Bernd J. Pichler

  2. Nuclear Medicine and Clinical Molecular Imaging, Department of Radiology, Eberhard Karls University of Tübingen, Tübingen, Germany

    Johannes Schwenck & Christian la Fougère

  3. Cluster of Excellence iFIT (EXC 2180) ‘Image-Guided and Functionally Instructed Tumour Therapies’, Eberhard Karls University, Tübingen, Germany

    Johannes Schwenck, Jonathan M. Cotton, Hans-Georg Rammensee, Christian la Fougère, Lars Zender & Bernd J. Pichler

  4. Medical Oncology and Pulmonology, Department of Internal Medicine, Eberhard Karls University of Tübingen, Tübingen, Germany

    Dominik Sonanini & Lars Zender

  5. Department of Immunology, IFIZ Institute for Cell Biology, Eberhard Karls University of Tübingen, Tübingen, Germany

    Hans-Georg Rammensee

  6. German Cancer Research Center, German Cancer Consortium DKTK, Partner Site Tübingen, Tübingen, Germany

    Hans-Georg Rammensee, Christian la Fougère, Lars Zender & Bernd J. Pichler

Authors
  1. Johannes Schwenck
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  2. Dominik Sonanini
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  3. Jonathan M. Cotton
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  4. Hans-Georg Rammensee
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  5. Christian la Fougère
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Contributions

All authors researched data for the article. All authors contributed substantially to discussion of the content. All authors wrote the article. B.J.P. reviewed and/or edited the manuscript before submission.

Corresponding author

Correspondence to Bernd J. Pichler.

Ethics declarations

Competing interests

J.M.C., J.S., C.la F., L.Z. and B.J.P. hold a patent for the senescence tracer mentioned in this Review. It has not been licensed yet. The Department of Preclinical Imaging and Radiopharmacy (B.J.P.), as well as the Department of Nuclear Medicine (C.la F.) and Department of Radiology at the University of Tübingen, have scientific collaborations with ImaginAb on CD8 imaging. The Department of Preclinical Imaging and Radiopharmacy (B.J.P.) performs contractual productions of the CD8+ tracer (sponsor: ImaginAb). D.S. and H.-G.R. have no competing interests.

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Nature Reviews Cancer thanks Abass Alavi, Sandip Basu and Rakesh Kumar for their contribution to the peer review of this work.

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Glossary

Axial field of view

The active imaging field of view of a scanner where, for example, radiation is detected in PET.

Base excision repair pathway

A DNA repair pathway that replaces missing or modified DNA bases, such as those produced by alkylating agents or in spontaneously degraded DNA, with the correct DNA base.

Chemical exchange saturation transfer

MRI method based on protons of a targeted tissue exchanging with molecules of surrounding protons to enhance the MRI contrast.

Computed tomography

(CT). X-ray-based tomographic imaging system.

Dynamic contrast-enhanced (DCE)-MRI

Quantitative temporal measurement of the in vivo distribution of a contrast agent by MRI.

Hyperpolarized imaging

MRI method to probe metabolic information in vivo by using exogenous labelled 13C substrates.

Magnetic resonance imaging

(MRI). Non-radiation-based imaging using the contrast of proton density.

Megabecquerels

Refers to one million becquerel; a becquerel is a unit of measurement of radioactivity equivalent to one nucleus decaying every second.

Multiplexed imaging

Combining different in vivo and ex vivo imaging information.

Nuclear magnetic resonance (NMR) spectroscopy

In vivo detection system revealing the distribution endogenous metabolites in tissue.

Partial volume effect

Refers to an error or underestimation in absolute quantification if the object to be detected is smaller or at the same range of the pixel size of the detector.

Positron emission tomography

(PET). Tomographic in vivo imaging system detecting quantitatively the distribution of an intravenously injected radiolabelled compound to reveal molecular information up to a picomolar sensitivity.

PET–CT

Combination of PET and X-ray CT in one single device enabling image fusion of high spatial accuracy.

PET–MRI

Combination of PET and MRI in one single device enabling simultaneous data acquisition to reveal metabolic, functional, morphological and anatomical parameters at high spatial and temporal fusion accuracy.

Pharmacokinetics

Distribution dynamic of a pharmaceutical, for example, in PET, the kinetics of the radiolabelled tracer.

Radiomics

Quantitative analysis of imaging features such as sphericity, shape and size.

Raman imaging

Inelastic scattering of laser light on matter to reveal spectroscopic information.

Spectral clustering

Analysis of multiparametric images using the spectrum of a similarity matrix.

T1-weighted (T1W) contrast-enhanced (CE) MRI

Uses gadolinium-based contrast agents to enable a more detailed and accurate representation of patho-physiological change, for example, the disruption of the blood–brain barrier and thus helps in differential diagnoses.

T2-weighted (T2W) axial MRI

Used to differentiate between water-bound protons and fat-bound protons providing a strong anatomical contrast in the brain.

Theranostic approaches

The principle of combining diagnostics with therapy, ideally by using one molecule for therapy and diagnosis.

Tracers

Radiolabelled biologically active compounds such as the radiolabelled glucose analogue [18F]FDG.

Ultrasound

(US). Imaging system applying ultrasound waves to reveal soft tissue contrasts in vivo.

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Schwenck, J., Sonanini, D., Cotton, J.M. et al. Advances in PET imaging of cancer. Nat Rev Cancer 23, 474–490 (2023). https://doi.org/10.1038/s41568-023-00576-4

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