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The Basics of Visualizing, Analyzing, and Reporting Preclinical PET/CT Imaging Data

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Positron Emission Tomography

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2729))

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Abstract

Positron emission tomography (PET) has transformed medical imaging, and while first developed and applied to the human setting, it has found widespread application at the preclinical level over the past two decades. Its strength is that it offers noninvasive 3D tomographic imaging in a quantitative manner at very high sensitivity. Paired with the right molecular probes, invaluable insights into physiology and pathophysiology have been accessible and therapeutic development has been enhanced through preclinical PET imaging. PET imaging is now often routinely combined with either computed tomography (CT) or magnetic resonance imaging (MRI) to provide additional anatomical context. All these developments were accompanied by the provision of ever more complex and powerful analysis software enabling users to visualize and quantify signals from PET imaging data. Aside from experimental complexities, there are also various pitfalls in PET image data analysis, which can negatively impact on reporting and reproducibility.

Here, we provide a protocol intended to guide the inexperienced user through PET/CT data analysis. We describe the general principles and workflows required for PET/CT image data visualization and quantitative analysis using various software packages popular in the field. Moreover, we present recommendations for reporting of preclinical PET/CT data including examples of good and poor practice.

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Acknowledgments

This work was supported by the Cancer Research UK grant to GOF [C48390/A21153], the National Institute for Health Research (NIHR) Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London, and the Wellcome/EPSRC Centre for Medical Engineering at King’s College London [WT 203148/Z/16/Z]. AV is supported by The Center for Experimental Immuno-Oncology Fellowship Award (FP00001443), the Tow Foundation Fellowship Award (FP000004141) and the Fiona and Stanley Druckenmiller Center for Lung Cancer Research Fellowship Award (FP00005072) at Memorial Sloan Kettering Cancer Center. Further support was received by an NIH/NCI Cancer Center Support Grant to MSKCC (P30 CA008748). Views expressed are those of the authors and not necessarily those of the NIHR or NHS.

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Author notes

  1. Christopher J. Cawthorne and Gilbert O. Fruhwirth contributed equally with all other contributors.

Authors and Affiliations

  1. Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, Katholieke Universiteit Leuven, Leuven, Belgium

    Christopher J. Cawthorne

  2. Molecular Imaging Group, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Alessia Volpe

  3. Imaging Therapies and Cancer Group, Comprehensive Cancer Centre, School of Cancer and Pharmaceutical Sciences, King’s College London, London, UK

    Gilbert O. Fruhwirth

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  1. Christopher J. Cawthorne
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  2. Alessia Volpe
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  3. Gilbert O. Fruhwirth
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Corresponding authors

Correspondence to Christopher J. Cawthorne or Gilbert O. Fruhwirth .

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Editors and Affiliations

  1. School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK

    Timothy H. Witney

  2. Department of Chemistry and Biomolecular Sciences, University of Ottawa, Ottawa, ON, Canada

    Adam J. Shuhendler

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Cawthorne, C.J., Volpe, A., Fruhwirth, G.O. (2024). The Basics of Visualizing, Analyzing, and Reporting Preclinical PET/CT Imaging Data. In: Witney, T.H., Shuhendler, A.J. (eds) Positron Emission Tomography. Methods in Molecular Biology, vol 2729. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3499-8_12

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  • DOI: https://doi.org/10.1007/978-1-0716-3499-8_12

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