Editorial: Rising Stars in PET and SPECT: 2024

Mario Petretta^*

• University of Naples Federico II, Naples, Italy

1. the likely usefulness of performing V/Q-SPECT/CT imaging in patients presenting with respiratory deterioration following endoscopic lung volume reduction; 2. the central role of FAPI PET/CT for the work-up and management of lymphoma patients;3. the potential of the Self-SiMilARiTy-Aware Generative Adversarial Framework (SMART) in low count PET images (SMART-PET) to synthesize standard of care activity PET images; 4. the feasibility of 68 Ga-Trivehexin for imaging of αvβ6-integrin expression in pancreatic cancer and its ability to distinguish primary carcinoma and metastases from background tissue.The aim of this Editorial is to offer the reader a brief presentation of the articles in this Research Topic, mentioning the value that the individual contributions bring to the horizons and results of research in the field of PET and SPECT. This brief presentation hopes to encourage the reader to delve deeper into the individual contributions, which contribute to the promise of a future of innovation and progress.The paper by Quartuccio et al explores the role of FAPI PET/CT in lymphoma patients. In particular, while fluorodeoxyglucose PET/CT (FDG PET/CT) is generally considered the gold standard imaging technique for the initial evaluation and follow-up of lymphoma patients, it is not uncommon for this approach to prove inconclusive. Therefore, fibroblast activation protein inhibitor PET/CT (FAPI PET/CT) has been widely explored as a useful resource. The authors therefore performed a thorough systematic review of the literature available on PubMed/MEDLINE and Cochrane CENTRAL of studies with FAPI PET/CT in lymphoma patients according to the QUADAS-2 criteria. The systematic review reveals that FAPI PET/CT exhibits lower diagnostic sensitivity than [ 18 F]-fluorodeoxyglucose ( 18 F-FDG) PET/CT in lymphomas characterized by low FAP expression. Nevertheless, FAPI PET/CT retains potential as a complementary imaging modality. In particular, it could help identify lymphoma subgroups with distinct stromal environments, potentially serving as a prognostic biomarker.The article by Raymond et al present a novel PET only deep learning framework, the Self-SiMilARiTy-Aware Generative Adversarial Framework (SMART), which leverages Generative Adversarial Networks (GANs) and a self-similarity-aware attention mechanism for denoising 18 F-FDG PET images. This approach was developed with the aim of obtaining PET images with high diagnostic quality while minimizing the radiation risk. In fact, minimizing radiation risks while preserving PET image quality could potentially enlarge the current applications of PET medical imaging, in particular for longitudinal evaluations and in radiosensitive populations such as pediatrics. This solution can be implemented by denoising PET images with low injected activity. However, the proposed method differs from previous algorithms that rely on structural or anatomical guidance from magnetic In conclusions, the articles selected for this Research Topic highlight the potential of advances in nuclear medicine to improve the diagnostic and therapeutic workup of diseases. Increasingly accurate imaging techniques, artificial intelligence algorithms, and innovative radiotracers are expanding the boundaries and indications of nuclear medical imaging. It should be emphasized, however, that biomedical knowledge is constantly evolving, as are epidemiological scenarios. Therefore, increased research collaboration and full sharing of results across different fields are essential to address these challenges and realize the full potential of various proposed innovative approaches. Our hope is that these articles will contribute to this goal and encourage young talents to continue their efforts to advance our knowledge in outcome research and implement the results obtained in daily clinical practice.