Publikationen

Assessment of an antidepressant's occupancy at the serotonin transporter (SERT) in vivo using PET scans represents a demanding procedure. We evaluated novel approaches for SERT quantification to simplify the occupancy calculation. [C]DASB PET/MRI scans with bolus plus constant infusion were performed twice in 47 healthy controls and 31 patients with major depressive disorder with intravenous application of 8 mg citalopram or saline solution (randomized, cross-over, double-blind). Binding potentials (BP and BP) were estimated over time and within two radioligand equilibrium periods (before and after drug challenge). Reference occupancy was calculated as the relative decrease in post-drug BP between the placebo and citalopram scans. We introduced three methods for estimating SERT occupancy. Method 1 replaced the arterial blood sampling (BP) by reference region modeling during equilibrium timeframes (BP). Method 2 replaced the post-dose placebo equilibrium period with the pre-dose citalopram equilibrium period. Method 3 integrated aspects of both Methods 1 and 2, utilizing BP and the pre-dose citalopram equilibrium phase. The results showed equivalent occupancy values (p < 0.05) for the majority of VOIs and high agreement (max R = 0.89) between the reference (utilizing arterial blood sampling, along with the placebo and citalopram scan) and the proposed methods, indicating that they are a promising solution for simplifying occupancy estimation.

The advent of sophisticated image analysis techniques has facilitated the extraction of increasingly complex data, such as radiomic features, from various imaging modalities, including [F]FDG PET/CT, a well-established cornerstone of oncological imaging. Furthermore, the use of artificial intelligence (AI) algorithms has shown considerable promise in enhancing the interpretation of these quantitative parameters. Additionally, AI-driven models enable the integration of parameters from multiple imaging modalities along with clinical data, facilitating the development of comprehensive models with significant clinical impact. However, challenges remain regarding standardization and validation of the AI-powered models, as well as their implementation in real-world clinical practice. The variability in imaging acquisition protocols, segmentation methods, and feature extraction approaches across different institutions necessitates robust harmonization efforts to ensure reproducibility and clinical utility. Moreover, the successful translation of AI models into clinical practice requires prospective validation in large cohorts, as well as seamless integration into existing workflows to assess their ability to enhance clinicians' performance. This review aims to provide an overview of the literature and highlight three key applications: diagnostic impact, prediction of treatment response, and long-term patient prognostication. In the first part, we will focus on head and neck, lung, breast, gastroesophageal, colorectal, and gynecological malignancies.

Novel nomograms predicting lymph node involvement (LNI) of prostate cancer (PCa) including PSMA PET information have been developed. However, their predictive accuracy in external populations is still unclear.

Functional Positron Emission Tomography (fPET) is an effective tool for studying dynamic processes in glucose metabolism and neurotransmitter action, providing insights into brain function and disease progression. However, optimizing signal processing to extract stimulation-specific information remains challenging. This study systematically evaluates state-of-the-art filtering techniques for fPET imaging. Forty healthy participants performed a cognitive task (Tetris®) during [F]FDG PET/MR scans. Seven filtering techniques and multiple hyperparameters were tested: including 3D and 4D Gaussian smoothing, highly constrained backprojection (HYPR), iterative HYPR (IHYPR4D), MRI-Markov Random Field (MRI-MRF) filters, and dynamic/extended dynamic Non-Local Means (dNLM/edNLM). Filters were assessed based on test-retest reliability, task signal identifiability (temporal signal-to-noise ratio, tSNR), spatial task-based activation, and sample size calculations were assessed. Compared to 3D Gaussian smoothing, edNLM, dNLM, MRI-MRF L = 10, and IHYPR4D filters improved tSNR, while edNLM and HYPR enhanced test-retest reliability. Spatial task-based activation was enhanced by NLM filters and MRI-MRF approaches. The edNLM filter reduced the required sample size by 15.4%. Simulations supported these findings. This study highlights the strengths and limitations of fPET filtering techniques, emphasizing how hyperparamter adjustments affect outcome parameters. The edNLM filter shows promise with improved performance across all metrics, but filter selection should consider specific study objectives and resource constraints.

To evaluate the capability of hyperpolarized [1-C] pyruvate MRI to predict pathologic response to neoadjuvant treatment in multi-site abdominopelvic disease of high-grade serous ovarian cancer (HGSOC) patients and to compare C MRI and [F]-FDG PET/CT measurements for detecting early treatment response. We recruited eight patients with HGSOC in this prospective study who underwent C MRI and [F]-FDG PET/CT before and after the first cycle of neoadjuvant chemotherapy treatment (NACT). Imaging parameters were compared with clinical and histophatologic parameters.

Since its inception in 2012, the Nuclear Medicine Global Initiative (NMGI) of the Society of Nuclear Medicine and Molecular Imaging has played an important role in addressing significant challenges in the field of nuclear medicine and molecular imaging. The first 3 projects were dedicated to standardizing pediatric nuclear medicine practices, addressing the global challenges of radionuclide access and availability, and assessing the educational and training initiatives on theranostics across the globe. These efforts aimed to advance human health, foster worldwide educational collaboration, and standardize procedural guidelines to enhance quality and safety in nuclear medicine practice. In its latest project, NMGI aimed to develop a unified nomenclature for systemic radionuclide therapy in nuclear medicine, addressing the diverse terminology currently used. An online survey was distributed to NMGI member organizations, drawing participation from various geographical locations and disciplines. The survey anonymously collected responses from physicians, physicists, scientists, radiopharmacists, radiopharmaceutical scientists, dosimetrists, technologists, and nurse managers, totaling 240 responses from 30 countries. Findings revealed a prevailing use of the term targeted radionuclide therapy for radionuclide therapy, with 52% of respondents expressing a preference for this term. In contrast, approximately 37% favored "radiopharmaceutical therapy," whereas 11% favored "molecular radionuclide therapy." Other key terms under the umbrella of targeted radionuclide therapy were also discussed to achieve a consensus on terminology. NMGI efforts to standardize terminology in this dynamic and fluid field should improve communication within the field, better reflect the technology used, enable comparison of results, and ultimately lead to improved patient outcomes.

The rapid growth of radiopharmaceutical sciences, driven by regulatory approvals of theranostic agents and the expanding role of PET imaging, underscores the need for sustainable and green practices. While radiopharmaceuticals offer high precision and targeted therapy with minimal systemic toxicity, the field faces challenges related to increasing demand, energy consumption, and waste management. The nuclear medicine market is projected to reach $30 billion by 2030, necessitating the integration of sustainability principles such as green chemistry and green engineering into radiopharmaceutical development. Given the energy-intensive nature of radiochemical processes, these principles provide strategies for reducing environmental impact. However, radiopharmaceutical sciences require adaptations to traditional sustainability frameworks due to factors like radiation safety, speed, and automation. This perspective examines the applicability of the 12 principles of green chemistry and engineering, proposing nine key principles tailored to radiopharmaceutical sciences. These principles address waste prevention, radionuclide recycling, energy efficiency, and the adoption of cleaner irradiation technologies. As the field evolves, incorporating sustainability into training programs and research initiatives will be essential.

This systematic review aims to examine the safety and efficacy of fibroblast activation protein inhibitor (FAPI) radioligand therapy (RLT) for various epithelial neoplasms. PubMed, Web of Science, and Scopus databases were searched up to Jan 4, 2025, for studies involving FAPI RLT in various cancers. Data extraction focused on exploring safety and efficacy of FAPI RLT. Overall, 27 studies involving a total of 144 patients who received FAPI RLT were included in this systematic review. [Lu]Lu-FAPI was employed in 21 studies, with 225 cycles administered to 95 patients at a median dose of 6.8 GBq/cycle. Six non-randomized clinical investigations using [Lu]Lu-FAPI reported disease control rates ranging from 18.2% to 83.3%. Only three studies documented a cumulative total of six patients who experienced grade 3 or 4 toxicity post [Lu]Lu-FAPI RLT. Of 16 case reports utilizing [Lu]Lu-FAPI, nine achieved disease control across various cancer types, with no reported adverse events. Four studies employed [Y]Y-FAPI, totaling 103 cycles in 42 patients at a median dose of 6.7 GBq/cycle. Three non-randomized clinical investigations reported disease control rates of 50% to 82%, with two studies documenting eight high-grade toxicity events. Furthermore, a successful administration of [Y]Y-FAPI was employed in a single reported case involving multiple primary neoplasms with no reported adverse events. However, the patient did not achieve disease control post [Y]Y-FAPI. A cohort study utilized 53 [Bi]Bi-FAPI-46 injections following a fractionated dose regimen in six cancer patients, achieving a 33.3% disease control rate without reported adverse events. One case report described dual radionuclide therapy using two cycles with a cumulative 20 GBq [Sm]Sm-FAPI and a third 8 GBq [Y]Y-FAPI cycle in a lung cancer patient, resulting in stable disease for eight months. FAPI RLT is a promising and safe therapeutic agent in oncology, with potential benefits achieved on short-term basis. However, its long-term efficacy and safety require further research with larger, controlled studies, considering the currently observed variations in patient populations, cancer types, and methodologies within reviewed studies.

Radioligand therapy (RLT) has garnered significant attention due to the recent emergence of innovative and effective theranostic agents, which showed promising therapeutic and prognostic results in various cancers. Moreover, understanding the interaction between different types of radiation and biological tissues is essential for optimizing therapeutic interventions These concepts directly apply to clinical RLTs and play a crucial role in determining the efficacy and toxicity profile of different radiopharmaceutical agents. Personalized dosimetry is a powerful tool that aids in estimating patient-specific absorbed doses in both tumors and normal organs. Dosimetry in RLT is an area of active investigation, as our current understanding of the relationship between absorbed dose and tissue damage is primarily derived from external-beam radiation therapy. Further research is necessary to comprehensively comprehend this relationship in the context of RLTs. In the present review, we present a thorough examination of the involvement of Lu/Ac radioisotopes in the induction of direct and indirect DNA damage, as well as their influence on the initiation of DNA repair mechanisms in cancer cells of neuroendocrine tumors and metastatic prostate cancer. Current data indicate that high-energy α-emitter radioisotopes can directly impact DNA structure by causing ionization, leading to the formation of ionized atoms or molecules. This ionization process predominantly leads to the formation of irreparable and intricate double-strand breaks (DSBs). On the other hand, the majority of DNA damage caused by β-emitter radioisotopes is indirect, as it involves the production of free radicals and subsequent chemical reactions. Beta particles themselves can also physically interact with the DNA molecule, resulting in single-strand breaks (SSBs) and potentially reversible DSBs.