Clinical value of 3'-deoxy-3'-[18F]fluorothymidine-positron emission tomography for diagnosis, staging and assessing therapy response in lung cancer

Hypoxia Imaging in Lung Cancer: A PET-Based Narrative Review for Clinicians and Researchers

Background: Hypoxia plays a critical role in lung cancer progression and treatment resistance by contributing to aggressive tumor behavior and poor therapeutic response. Molecular imaging, particularly positron emission tomography (PET), has become an essential tool for noninvasive hypoxia detection, providing valuable insights into tumor biology and aiding in personalized treatment strategies. Objective: This narrative review explores recent advancements in PET imaging for detecting hypoxia in lung cancer, with a focus on the development, characteristics, and clinical applications of various radiotracers. Findings: Numerous PET-based hypoxia radiotracers have been investigated, each with distinct pharmacokinetics and imaging capabilities. Established tracers such as 18F-Fluoromisonidazole (18F-FMISO) remain widely used, while newer alternatives like 18F-Fluoroazomycin Arabinoside (18F-FAZA) and 18F-Flortanidazole (18F-HX4) demonstrate improved clearance and image contrast. Additionally, 64Cu-ATSM has gained attention for its rapid tumor uptake and hypoxia selectivity. The integration of PET with hybrid imaging modalities, such as PET/CT and PET/MRI, enhances the spatial resolution and functional interpretation, making hypoxia imaging a promising approach for guiding radiotherapy, chemotherapy, and targeted therapies. Conclusions: PET imaging of hypoxia offers significant potential in lung cancer diagnosis, treatment planning, and therapeutic response assessment. However, challenges remain, including tracer specificity, quantification variability, and standardization of imaging protocols. Future research should focus on developing next-generation radiotracers with enhanced specificity, optimizing imaging methodologies, and leveraging multimodal approaches to improve clinical utility and patient outcomes.

The Role of [18F]FDG PET/CT in Monitoring of Therapy Response in Lung Cancer

Lung cancer remains a leading cause of cancer deaths worldwide, with an all stage 5-year relative survival rate of less than 30%. Multiple treatment strategies are available and continue to evolve, with therapy primarily tailored to the type and stage of the disease. Accurate monitoring of therapy response is crucial for optimizing treatment outcomes. PET/CT imaging with [18F]FDG has become the standard of care across various phases of lung cancer management due to its ability to assess metabolic activity. This review underscores the pivotal role of [18F]FDG PET/CT in evaluating therapy response in lung cancer, particularly in non-small cell lung cancer (NSCLC). It examines conventional response criteria and their adaptations in the era of immunotherapy, highlighting the value of integrating metabolic imaging with established criteria to improve treatment assessment and guide clinical decisions. The potential of non-[18F]FDG PET tracers targeting diverse biological pathways to provide deeper insights into tumor biology, therapy response and predictive outcomes is also explored. Additionally, the emerging role of radiomics in enhancing treatment efficacy assessment and improving patient management is briefly highlighted. Despite the challenges in the routine clinical application of various metabolic response criteria, [18F]FDG PET/CT remains a crucial tool in monitoring therapy response in lung cancer. Ongoing advancements in therapeutic strategies, radiopharmaceuticals, and imaging techniques continue to drive progress in lung cancer management, promising improved patient outcomes.

Imaging at the nexus: how state of the art imaging techniques can enhance our understanding of cancer and fibrosis

Both cancer and fibrosis are diseases involving dysregulation of cell signaling pathways resulting in an altered cellular microenvironment which ultimately leads to progression of the condition. The two disease entities share common molecular pathophysiology and recent research has illuminated the how each promotes the other. Multiple imaging techniques have been developed to aid in the early and accurate diagnosis of each disease, and given the commonalities between the pathophysiology of the conditions, advances in imaging one disease have opened new avenues to study the other. Here, we detail the most up-to-date advances in imaging techniques for each disease and how they have crossed over to improve detection and monitoring of the other. We explore techniques in positron emission tomography (PET), magnetic resonance imaging (MRI), second generation harmonic Imaging (SGHI), ultrasound (US), radiomics, and artificial intelligence (AI). A new diagnostic imaging tool in PET/computed tomography (CT) is the use of radiolabeled fibroblast activation protein inhibitor (FAPI). SGHI uses high-frequency sound waves to penetrate deeper into the tissue, providing a more detailed view of the tumor microenvironment. Artificial intelligence with the aid of advanced deep learning (DL) algorithms has been highly effective in training computer systems to diagnose and classify neoplastic lesions in multiple organs. Ultimately, advancing imaging techniques in cancer and fibrosis can lead to significantly more timely and accurate diagnoses of both diseases resulting in better patient outcomes.

Deciphering Tumor Response: The Role of Fluoro-18-d-Glucose Uptake in Evaluating Targeted Therapies with Tyrosine Kinase Inhibitors

Background/Objectives: The inhibitory effects of tyrosine kinase inhibitors (TKIs) on glucose uptake through their binding to human glucose transporter-1 (GLUT-1) have been well documented. Thus, our research aimed to explore the potential impact of various TKIs of GLUT-1 on the standard [18F]FDG-PET monitoring of tumor response in patients. Methods: To achieve this, we conducted an analysis on three patients who were undergoing treatment with different TKIs and harbored actionable alterations. Alongside the assessment of FDG data (including SUVmax, total lesion glycolysis (TLG), and metabolic tumor volume (MTV)), we also examined the changes in tumor sizes through follow-up [18F]FDG-PET/CT imaging. Notably, our patients harbored alterations in BRAFV600, RET, and c-KIT and exhibited positive responses to the targeted treatment. Results: Our analysis revealed that FDG data derived from SUVmax, TLG, and MTV offered quantifiable outcomes that were consistent with the measurements of tumor size. Conclusions: These findings lend support to the notion that the inhibition of GLUT-1, as a consequence of treatment efficacy, could be indirectly gauged through [18F] FDG-PET/CT imaging in cancer patients undergoing TKI therapy.

Dominant roles of BRCA1 in cellular tolerance to a chain-terminating nucleoside analog, alovudine

Alovudine is a chain-terminating nucleoside analog (CTNA) that is frequently used as an antiviral and anticancer agent. Generally, CTNAs inhibit DNA replication after their incorporation into nascent DNA during DNA synthesis by suppressing subsequent polymerization, which restricts the proliferation of viruses and cancer cells. Alovudine is a thymidine analog used as an antiviral drug. However, the mechanisms underlying the removal of alovudine and DNA damage tolerance pathways involved in cellular resistance to alovudine remain unclear. Here, we explored the DNA damage tolerance pathways responsible for cellular tolerance to alovudine and found that BRCA1-deficient cells exhibited the highest sensitivity to alovudine. Moreover, alovudine interfered with DNA replication in two distinct mechanisms: first: alovudine incorporated at the end of nascent DNA interfered with subsequent DNA synthesis; second: DNA replication stalled on the alovudine-incorporated template strand. Additionally, BRCA1 facilitated the removal of the incorporated alovudine from nascent DNA, and BRCA1-mediated homologous recombination (HR) contributed to the progressive replication on the alovudine-incorporated template. Thus, we have elucidated the previously unappreciated mechanism of alovudine-mediated inhibition of DNA replication and the role of BRCA1 in cellular tolerance to alovudine.

Hematopoiesis in the spleen after engraftment in unrelated cord blood transplantation evaluated by 18F-FLT PET imaging

Cord blood is an important donor source for allogeneic hematopoietic stem cell transplantation (allo-HSCT), with its unique composition and quality of hematopoietic cells. The proliferation site and potency of infused hematopoietic stem cells in humans may vary between stem cell sources. We investigated this possibility in a prospective, exploratory study to assess hematopoietic dynamics using the radiopharmaceutical 3'-deoxy-3'-18F-fluorothymidine (18F-FLT), a thymidine analog used in positron emission tomography imaging, before allo-HSCT and on days 50 and 180 after allo-HSCT. We evaluated 11 patients with hematological malignancies who underwent allo-HSCT [five with peripheral blood stem cell transplantation (PBSCT) and six with unrelated cord blood transplantation (UCBT)]. Before allo-HSCT, 18F-FLT uptake did not differ between the two groups. At day 50, 18F-FLT uptake in the spleen was significantly greater in the UCBT group than in the PBSCT group (p = 0.0043), with no difference in whole-body bone marrow. At day 180, the differences in spleen uptake had diminished, and there were no differences between groups in whole-body bone marrow or the spleen, except for the sternum. The persistence of splenic hematopoiesis after engraftment in the UCBT group may reflect the complex systemic homing and proliferation mechanisms of cord blood hematopoietic cells.

Tumor microenvironment and fibroblast activation protein inhibitor (FAPI) PET: developments toward brain imaging

Fibroblast activation protein (FAP) is a type-II membrane bound glycoprotein specifically expressed by activated fibroblasts almost exclusively in pathological conditions including arthritis, fibrosis and cancer. FAP is overexpressed in cancer-associated fibroblasts (CAFs) located in tumor stroma, and is known to be involved in a variety of tumor-promoting activities such as angiogenesis, proliferation, resistance to chemotherapy, extracellular matrix remodeling and immunosuppression. In most cancer types, higher FAP expression is associated with worse clinical outcomes, leading to the hypothesis that FAP activity is involved in cancer development, cancer cell migration, and cancer spread. Recently, various high selectivity FAP inhibitors (FAPIs) have been developed and subsequently used for positron emission tomography (PET) imaging of different pathologies. Considering the paucity of widely available and especially mainstream reliable radioligands in brain cancer PET imaging, and the poor survival rates of patients with certain types of brain cancer such as glioblastoma, FAPI-PET represents a major development in enabling the detection of small primary or metastatic lesions in the brain due to its biological characteristics and low background accumulation. In this work, we aim to summarize the potential avenues for use of FAPI-PET, from the basic biological processes to oncologic imaging and with a main focus on brain imaging.

Fluorinated carbohydrates for 18F-positron emission tomography (PET)

Carbohydrate diversity is foundational in the molecular literacy that regulates cellular function and communication. Consequently, delineating and leveraging this structure-function interplay continues to be a core research objective in the development of candidates for biomedical diagnostics. A totemic example is the ubiquity of 2-deoxy-2-[18F]-fluoro-D-glucose (2-[18F]-FDG) as a radiotracer for positron emission tomography (PET), in which metabolic trapping is harnessed. Building on this clinical success, more complex sugars with unique selectivities are gaining momentum in molecular recognition and personalised medicine: this reflects the opportunities that carbohydrate-specific targeting affords in a broader sense. In this Tutorial Review, key milestones in the development of 2-[18F]-FDG and related glycan-based radiotracers for PET are described, with their diagnostic functions, to assist in navigating this rapidly expanding field of interdisciplinary research.

Dose evaluation of the one-year-old child in PET imaging by18F-(DOPA, FDG, FLT, FET) and68Ga-EDTA using reference voxel phantoms

Because of more sensitive organs due to high growth rates, evaluating the absorbed dose is essential for children to prevent irreparable damage. Therefore, to this aim, a one-year-old child's whole-body effective dose and organ absorbed dose were evaluated for various PET imaging Radiopharmaceuticals such as:¹⁸F-DOPA,¹⁸F-FDG,¹⁸F-FLT,¹⁸F-FET, and⁶⁸Ga-EDTA. For this aim, one-year-old child reference voxel phantoms and GATE Monte Carlo simulation were used, and the results were compared with the ICRP128 report (for stylized phantom). The highest absorbed dose was related to bladder wall (for¹⁸F-DOPA,¹⁸F-FET, and⁶⁸Ga-EDTA), heart wall (for¹⁸F-FDG), and liver (for¹⁸F-FLT) between 30 organs that have been studied. Comparing the results with the ICRP128 report values for a one-year-old child show a significant difference in some organs. Comparison of the effective dose with the ICRP128 report shows a relative difference of 22%, 12.5%, 11.8%, 10.8% and 8.6% for¹⁸F-DOPA,⁶⁸Ga-EDTA,¹⁸F-FDG,¹⁸F-FET,¹⁸F-FLT, respectively. In conclusion, using new one-year-old voxel phantoms could provide a better estimate of organs absorbed dose and whole-body effective dose due to its exact structure.

A Role of Non-FDG Tracers in Lung Cancer?

Since the introduction of PET/CT hybrid imaging about two decades ago the landscape of oncological imaging has fundamentally changed, opening a new era of molecular imaging with emphasis on functional characterization of biological processes such as metabolism, cellular proliferation, hypoxia, apoptosis, angiogenesis and immune response. The most commonly assessed functional hallmark of cancer is the increased metabolism in tumor cells due to well-known Warburg effect, because of which FDG has been the most employed radiotracer, the so-called pan-cancer agent, in oncological imaging. However, several limitations such as low specificity and low sensitivity for several histopathological forms of lung cancer as well as high background uptake in the normal tissue of FDG imaging lead to numerous serious pitfalls. This restricts its utilization and diagnostic value in lung cancer imaging, even though this is currently considered to be the method of choice in pulmonary cancer imaging. Accurate initial tumor staging and therapy response monitoring with respect to the TNM criteria plays a crucial role in therapy planning and management in patients with lung cancer. To this end, many efforts have been made for decades to develop novel PET radiopharmaceuticals with innovative approaches that go beyond the assessment of increased glycolytic activity alone. Radiopharmaceuticals targeting DNA synthesis, amino acid metabolism, angiogenesis, or hypoxia have been extensively studied, leading to the emergence of indications for specific clinical questions or as a complementary imaging tool alongside existing conventional or FDG imaging. Nevertheless, despite some initial encouraging results, these tracers couldn't gain a widespread use and acceptance in clinical routine. However, given its mechanism of action and some initial pilot studies regarding lung cancer imaging, FAPI has emerged as a very promising alternative tool that could provide superior or comparable diagnostic performance to FDG imaging in lung cancer entities. Thus, in this review article, we summarized the current PET radiopharmaceuticals, different imaging approaches and discussed the potential benefits and clinical applications of these agents in lung cancer imaging.

Molecular Imaging of Renal Cell Carcinoma in Precision Medicine

Renal cell carcinoma (RCC) is the sixth most common cancer among men and the ninth among women, and its prognosis is closely correlated with metastasis. Targeted therapy and immunotherapy are the main adjuvant treatments for advanced RCC and require early diagnosis, precise assessment, and prediction of the therapeutic responses. Current conventional imaging methods of RCC only provide structural information rather than biological processes. Noninvasive diagnostic tools are therefore needed to image RCC early and accurately at the molecular level. Nuclear medicine imaging combines the high sensitivity of radionuclides with the high resolution of structural imaging to visualize the metabolic processes and specific targets of RCC for more accurate and reliable diagnosis, staging, prognosis prediction, and response assessment. This review summarizes the most recent applications of nuclear medicine receptor imaging and metabolic imaging in RCC and highlights future development perspectives in the field.

Brain Tumor Classification Using a Combination of Variational Autoencoders and Generative Adversarial Networks

Brain tumors are a pernicious cancer with one of the lowest five-year survival rates. Neurologists often use magnetic resonance imaging (MRI) to diagnose the type of brain tumor. Automated computer-assisted tools can help them speed up the diagnosis process and reduce the burden on the health care systems. Recent advances in deep learning for medical imaging have shown remarkable results, especially in the automatic and instant diagnosis of various cancers. However, we need a large amount of data (images) to train the deep learning models in order to obtain good results. Large public datasets are rare in medicine. This paper proposes a framework based on unsupervised deep generative neural networks to solve this limitation. We combine two generative models in the proposed framework: variational autoencoders (VAEs) and generative adversarial networks (GANs). We swap the encoder-decoder network after initially training it on the training set of available MR images. The output of this swapped network is a noise vector that has information of the image manifold, and the cascaded generative adversarial network samples the input from this informative noise vector instead of random Gaussian noise. The proposed method helps the GAN to avoid mode collapse and generate realistic-looking brain tumor magnetic resonance images. These artificially generated images could solve the limitation of small medical datasets up to a reasonable extent and help the deep learning models perform acceptably. We used the ResNet50 as a classifier, and the artificially generated brain tumor images are used to augment the real and available images during the classifier training. We compared the classification results with several existing studies and state-of-the-art machine learning models. Our proposed methodology noticeably achieved better results. By using brain tumor images generated artificially by our proposed method, the classification average accuracy improved from 72.63% to 96.25%. For the most severe class of brain tumor, glioma, we achieved 0.769, 0.837, 0.833, and 0.80 values for recall, specificity, precision, and F1-score, respectively. The proposed generative model framework could be used to generate medical images in any domain, including PET (positron emission tomography) and MRI scans of various parts of the body, and the results show that it could be a useful clinical tool for medical experts.