Abstract
Therapeutic response is evaluated using the diameter of tumors and quantitative parameters of 2-[18F] fluoro-2-deoxy-d-glucose positron emission tomography (FDG-PET). Tumor response to molecular-targeted drugs and immune checkpoint inhibitors is different from conventional chemotherapy in terms of temporal metabolic alteration and morphological change after the therapy. Cancer stem cells, immunologically competent cells, and metabolism of cancer are considered targets of novel therapy. Accumulation of FDG reflects the glucose metabolism of cancer cells as well as immune cells in the tumor microenvironment, which differs among patients according to the individual immune function; however, FDG-PET could evaluate the viability of the tumor as a whole. On the other hand, specific imaging and cell tracking of cancer cell or immunological cell subsets does not elucidate tumor response in a complexed interaction in the tumor microenvironment. Considering tumor heterogeneity and individual variation in therapeutic response, a radiomics approach with quantitative features of multimodal images and deep learning algorithm with reference to pathologic and genetic data has the potential to improve response assessment for emerging cancer therapy.
Highlights
Positron emission tomography (PET) has become an indispensable procedure for the initial assessment and post-therapeutic evaluation in clinical oncology, using dedicated radiopharmaceuticals targeting cellular metabolism and tumor-specific receptors [1]
We summarize the current understanding of the tumor microenvironment, focusing on metabolism, cancer stem cells, chemokine receptors, and immune mechanisms, all of which are targets of therapy
Wang et al have suggested that the performance of convolutional neural networks (CNN) from FDG PET/computed tomography (CT) images is comparable to the best classical machine learning and human radiologists and that CNN is more convenient and objective than the classical methods, because it does not need tumor segmentation, feature selection, or texture features for classifying mediastinal lymph node metastasis in patients with non-small cell lung cancer (NSCLC) [46]
Summary
Positron emission tomography (PET) has become an indispensable procedure for the initial assessment and post-therapeutic evaluation in clinical oncology, using dedicated radiopharmaceuticals targeting cellular metabolism and tumor-specific receptors [1]. Conventional response evaluation criteria use morphological parameters; on the other hand, 2-[18 F] fluoro-2-deoxy-d-glucose (FDG)-PET-based criteria use metabolic parameters. Histological response to anti-cancer therapy depends on the therapeutic modalities; cancer immunotherapy shows the distinctive phenomenon of immune-related tumor responses. The current approaches to anti-cancer therapy target the tumor microenvironment as well as anti-tumor immunity. We summarize the current understanding of the tumor microenvironment, focusing on metabolism, cancer stem cells, chemokine receptors, and immune mechanisms, all of which are targets of therapy. Molecular imaging may have promise to address therapeutic response and toxicity evaluation to provide useful information for the benefit of novel anti-cancer therapy. Biomedicines 2020, 8, 371 assessment of individual therapeutic effectiveness plays a definitive role in personalized therapeutic strategies within the framework of precision medicine
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