Immunotherapy by Immune Checkpoint Inhibitors and Nuclear Medicine Imaging: Current and Future Applications

Abstract

Immunotherapy by using immune checkpoint inhibitors is a revolutionary development in oncology. Medical imaging is also impacted by this new therapy, particularly nuclear medicine imaging (also called radionuclide imaging), which uses radioactive tracers to visualize metabolic functions. Our aim was to review the current applications of nuclear medicine imaging in immunotherapy, along with their limitations, and the perspectives offered by this imaging modality. Method: Articles describing the use of radionuclide imaging in immunotherapy were researched using PubMed by April 2019 and analyzed. Results: More than 5000 articles were analyzed, and nearly 100 of them were retained. Radionuclide imaging, notably 18F-FDG PET/CT, already has a major role in many cancers for pre-therapeutic and therapeutic evaluation, diagnoses of adverse effects, called immune-related adverse events (IrAE), and end-of-treatment evaluations. However, these current applications can be hindered by immunotherapy, notably due to atypical response patterns such as pseudoprogression, which is defined as an increase in the size of lesions, or the visualization of new lesions, followed by a response, and hyperprogression, which is an accelerated tumor growth rate after starting treatment. To overcome these difficulties, new opportunities are offered, particularly therapeutic evaluation criteria adapted to immunotherapy and immuno-PET allowing us to predict responses to immunotherapy. Moreover, some new technological solutions are also promising, such as radiomic analyses and body composition on associated anatomical images. However, more research has to be done, notably for the diagnosis of hyperprogression and pseudoprogression. Conclusion: Immunotherapy, by its major impact on cancer and by the new patterns generated on images, is revolutionary in the field of medical images. Nuclear medicine imaging is already established and will be able to help meet new challenges through its plasticity.

Current Landscape and Emerging Fields of PET Imaging in Patients with Brain Tumors

“…Therefore, the significance of PET for predicting response to immunotherapy and patient selection increases. Among other methods, immuno-PET combines antibodies or antibody fragments with a radionuclide and takes advantage of the specificity and affinity of antibodies and the sensitivity of PET [162]. Generally, targets for immuno-PET can be T-cell markers (e.g., CD4 + , CD8 + ), immune checkpoints (e.g., CTLA-4, PD-1, PD-L1), or biomarkers of the immune response (e.g., interferon-γ, interleukin-2) [23].…”

Immunotherapy in Metastatic Colorectal Cancer: Could the Latest Developments Hold the Key to Improving Patient Survival?

“…Data from all sources are subsequently combined and analyzed to develop diagnostic, therapeutic, prognostic, and predictive models. Among medical imaging modalities, computed tomography (CT) and positron emission tomography (PET)/CT are frequently used methods in 'radiomics' studies [74]. A very recent meta-analysis found poor diagnostic performance of 2-deoxy-2-[fluorine-18]fluoro-D-glucose (F-18 FDG) PET/CT for the prediction of KRAS mutation in colorectal cancer patients [75].…”

Comparison of Metabolic and Morphological Response Criteria for Early Prediction of Response and Survival in NSCLC Patients Treated With Anti-PD-1/PD-L1

“…Indeed, PD-1/L1 and CTLA-4 blockage aims to restore the immune response by recalling neutrophils, macrophages, and activating T cells within the tumor microenvironment. Consequently, because of tumor inflammation, malignant lesions might appear stable, or even larger either in size or in metabolic activity before effective shrinkage occurs, making it difficult to discriminate between true progression from the so-called pseudo-progression ( 4 – 7 ). To overcome these limitations, numerous response criteria have been proposed, starting with the traditional Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 ( 8 ).…”