Current radiopharmaceuticals最新文献

Background: [68Ga-DOTA-D-Phe1-Tyr3]octreotide ([68Ga]Ga-DOTA-TOC) is a somatostatin analogue largely used in PET/CT applications for the detection of gastroenteropancreatic neuroendocrine tumors (GEP-NET). Initially, it was obtained using a 68Ge/68Ga generator.

Objective: The increasing cost of good manufacturing practice-compliant generators has led to the need to find alternative ways of producing Gallium-68 (68Ga). The goal of this work is to show the production optimization of [68Ga]Ga-DOTA-TOC via cyclotron, derived from three years of experience.

Methods: The production of [68Ga]GaCl3 via the 68Zn(p,n)68Ga reaction was optimized using a PETtrace 800 cyclotron (equipped with ZnO liquid target) and synthesis of [68Ga]Ga-DOTATOC was performed by FASTlab2 developer system according to the Guidelines on Good Radiopharmacy Practice (cGRPP). Quality control process was validated according to the current specific monograph (2482) of the European Pharmacopoeia (Ph. Eur.) before clinical use.

Results: [68Ga]Ga-DOTA-TOC was produced in 40 minutes; ten validation batches met the quality criteria expected by the Ph. Eur. The synthesis process has involved many issues due to the use of acidic reagents and related corrosion of some components of the cyclotron and developer system, resulting in 12.2% failed syntheses and a target breakdown after 11 months. In the troubleshooting section are reported the main issues, their causes and the strategies used to solve them. Thanks to these strategies, the number of failed syntheses has decreased and today, we have achieved a 0% failure rate.

Conclusion: Liquid target production of [68Ga]Ga-DOTA-TOC, once consolidated, instead of 68Ge/68Ga generator has many advantages.

Introduction: Presently, heavy particle ion radiation therapy is commonly utilized for the treatment of deep-seated malignancies, such as brain tumors. In addition to tumor treatment, these particles may negatively impact healthy nerve cells. Therefore, it is essential to investigate the radiobiological effects of these radiations on cells. Simulation studies that model the radiation of heavy particles and the exact geometrical configuration of nerve cells are essential and effective in evaluating potential cellular damage.

Materials and methods: The NEURON software was employed in Geant4 code to simulate an individual nerve cell (ID no: NMO 06176) and a network of ten neural cells subjected to bombardment by Ti48 ion particles at an energy of 600 MeV/u.

Results: The absorbed energy differs among several components of individual cells and neural networks, including the soma and dendrites. The absorbed doses from Ti48 radiation in individual nerve cells and dendritic networks surpass those in the cell body, and this ratio remains consistent as the dosage escalates. The decrease in the initial length of dendrites in both individual cells and neuronal networks intensifies with increased dosages.

Conclusion: The diminution of dendritic length due to Ti48 radiation is more significant within the cellular network compared to isolated nerve cells.

Introduction: GLP-1 receptor agonists (GLP-1 RA) are drugs used to treat diabetes by enhancing insulin sensitivity and secretion. Recent studies suggest their potential anti-cancer effects, including anti-inflammatory and antioxidant properties. This study evaluates the combined effects of GLP-1 RAs and radiotherapy (RT) on breast cancer progression in a BALB/c mouse model.

Materials and methods: In this study, BALB/c mice were injected with 4T1 breast cancer cells to induce tumors. The mice were randomly assigned to five groups: control, placebo, GLP-1 RA, RT, and combined GLP-1 RA with RT. Histological and immunohistochemical analyses were performed on the tumor tissues to assess changes in morphology and protein expression related to inflammation and apoptosis. In vitro, cell viability assays were also conducted on 4T1 cells to evaluate the effects of GLP-1 RA and RT.

Results: The combination of GLP-1 RA and RT resulted in significant tumor size reduction compared to the other treatment groups. Histological analysis showed improved tissue morphology, with restored healthy appearance in tumors treated with both GLP-1 RA and radiotherapy. Immunohistochemical staining revealed changes in the expression of apoptosis-related proteins. In vitro assays demonstrated that the combined treatment significantly decreased the viability of 4T1 breast cancer cells.

Conclusion: This study concludes that the GLP-1 RAs and RT combination enhances tumor control and improves histological outcomes in a breast cancer model. This approach offers a promising strategy for patients with coexisting diabetes and breast cancer, potentially improving treatment efficacy and patient outcomes.

Background: The ideal [131I]Sodium Iodide activity for intermediate-risk thyroid cancer treatment is still uncertaindue to the high heterogeneity of this disease in these patients.

Objective: The objective of this study is to compare the biochemical responses to radioiodine therapy (RIT) of intermediate-risk thyroid cancer patients administered [131I]Sodium Iodide at 3700 MBq (100 mCi) and 5550 MBq (150 mCi) activities.

Methods: A retrospective study was conducted by reviewing the medical records of intermediate- risk thyroid cancer patients who received RIT between 2016 and 2020 at a reference cancer hospital in Brazil. Sociodemographic and clinical data were evaluated at the time of diagnosis. Clinical data during two years of follow-up were reviewed, and biochemical responses were determined according to the American Thyroid Association (ATA, 2015 version). Responses to 3700 MBq (100 mCi) and 5550 MBq (150 mCi) of [131I]Sodium Iodide were compared.

Results: No significant statistical differences were observed concerning the biochemical therapeutic responses of patients treated with 3700 MBq or 5550 MBq (p = 0.088). The presence of nodal metastasis and positive pre-RIT thyroglobulin did not influence biochemical responses to radioiodine.

Conclusion: Intermediate risk thyroid-cancer patients presented similar therapeutic responses to 3700 MBq and 5550 MBq [131I]Sodium Iodide activities.

By integrating the sensitivity of nuclear medicine and the precision of nanotechnology, mankind can explore the very promising nuclear nanomedicine technology. Such integration enabled the imaging of biological processes at the molecular level which is a blessing to modern disease management. The present work is an effort to highlight the multifaceted applications of radiolabelled nanomaterials across various imaging modalities, formulation assessment, drug development, regulatory considerations, and therapeutic interventions. The present work highlights the application of radiolabelled nanomaterials for molecular imaging. The single-photon emission computed tomography (SPECT), positron emission tomography (PET); and hybrid multimodalities, along with their key features, are inherent parts of this discussion. The discussion continues with the assessment procedures of new formulations and their implications for drug delivery and the associated regulatory affairs. Cell tracking strategies that allow real-time monitoring of cellular behaviour in vivo; and radionuclide therapy with targeted and precise treatment are explained with the comparison of different strategies. This is followed by the explanation of how the drug delivery systems incorporating molecular imaging radiotracers enable tracking of in vivo drug behavior, further facilitating optimization of dosage forms and therapeutic efficacy. Thus, this manuscript provides a comprehensive overview of the utilization of radiolabelling strategies across the spectrum of drug formulation, delivery, and regulatory aspects, which is a way forward to future projections in nuclear nanomedicine. In conclusion, the emergence of nuclear nanomedicines is a disease management breakthrough in modern healthcare systems. This innovative approach not only provides tailored diagnostics but also offers innovative therapeutic solutions.

RNA-binding proteins (RBPs) regulate gene expression at the post-transcriptional level and are important factors in cancer progression and response to various therapeutic strategies. Radioresistance, an obstacle caused due to various intrinsic and extrinsic factors, remains a major hindrance in the treatment of cancer and could lead to tumor recurrence. Though research is being conducted on the cause and association of radioresistance with various cellular and environmental factors, there remains much to be explored and discovered. The roles of several RNA-binding proteins in tumor progression and metastasis are well documented. In addition, recent studies suggest the connection between Cancer Stem Cells (CSCs) and chemoresistance. We and others have extensively studied the regulatory role of RBPs in regulating CSCs. Resistance to radiation therapy and the involvement of RBPs in this process is under-studied. In this review, we have provided an updated compilation of the significant role played by RBPs in radioresistance.

Background: Strategies for predicting the recurrence of nasopharyngeal carcinoma need to be further development and validation. We developed a recurrence prediction model based on the fusion of multi-omics features from pre-treatment conventional magnetic resonance sequences (CE-T1W) in nasopharyngeal carcinoma (NPC) patients to predict posttreatment recurrence.

Methods: We employed a deep unsupervised stacked denoising autoencoder (stacked denoising autoencoder, SDAE) and multi-omics feature fusion method to develop an NPC recurrence prediction model. Data and magnetic resonance images from 184 patients with newly diagnosed nasopharyngeal carcinoma (NPC), confirmed by pathological examination and who underwent radical comprehensive treatment, were collected. Propensity score matching (relapse: no recurrence = 1:1) was used to balance clinical factors that might influence recurrence, resulting in 136 matched cases. SDAE was utilized to extract deep features, combined with the fusion features of radiomics (Radiomics) features and clinical features, using support vector machine (SVM), multilayer perceptron (MLP), logistic regression (LR) and random forest (RF) machine learning methods to build models. The mean area under the curve (AUC), accuracy, sensitivity, and specificity of each model were compared to evaluate their performance in predicting recurrence.

Results: After parameter adjustment, 12 machine learning models based on different fusion features were developed. Model 1 (Radiomics+AutoEncoder+Clinical+SVM) achieved better prediction performance, with a mean AUC, accuracy, sensitivity, and specificity of 0.89 (95% CI: 0.84- 0.93), 81.5%, 67.3% and 97.9%, respectively. Model 2 (Radiomics+ AutoEncoder+SVM), Model 3 (Radiomics+SVM), Model 4 (Radiomics+ AutoEncoder+Clinical+MLP), Model 5 (Radiomics+Auto Encoder+MLP), Model 6 (Radiomics+MLP), Model 7 (Radiomics+AutoEncoder+Clinical+LR), Model 8 (Radiomics+AutoEncoder+LR), Model 9 (Radiomics+LR), Model 10 (Radiomics+Auto Encoder+Clinical+RF), Model 11 (Radiomics+AutoEncoder+RF), Model 12 (Radiomics+RF) achieved AUCs of 0.87, 0.87, 0.82, 0.80, 0.82, 0.82, 0.78, 0.80, 0.81, 0.80, and 0.82, respectively.

Conclusion: The SVM model for predicting the recurrence of nasopharyngeal carcinoma based on radiomics+autoEncoder+clinical fusion features established by CE-T1WI of nasopharyngeal carcinoma patients before treatment, achieved good predictive performance and is relatively reliable, which can provide more information and help for clinical diagnosis and treatment decisions and interventions.

Background: A promising material used in radiation synovectomy of small joints is hydroxyapatite, labeled with 177Lu. During the design and production of radiopharmaceuticals, the condition of the radiolabeling process directly influences the radiochemical yield and consequently the quality of the final product so this process necessitates precise optimization.

Methods: In this investigation, a central composite design based on response surface methodology and artificial neural networks modeling coupled with genetic algorithm technique is applied to build predictive models and explore key parameters' effect in hydroxyapatite's radiolabeling process with 177Lu radionuclide. The variables that directly affected the labeling reaction were the initial 177Lu radioactivity, pH, radiolabeling reaction time, and temperature.

Results: Based on the validation data set, the statistical values demonstrate that the artificial neural networks model performs better than the response surface methodology model. The artificial neural networks model has a small mean squared error (9.08 artificial neural networks < 12.36 response surface methodology) and a high coefficient of determination (R2: 0.99 artificial neural networks > 0.93 response surface methodology). The optimum conditions to achieve maximum radiochemical yield based on response surface methodology using artificial neural networks modeling coupled with genetic algorithm were at the initial radioactivity of 177Lu radionuclide = 0.082 Gigabecquerel (GBq), pH = 6.75, time= 22 (min), and temperature = 37.8 (oC) Conclusion: The ability to generate more data with fewer experiments for optimization and improved production is a pertinent advantage of multivariate optimization methods over traditional methods in radiation-related activities. The central composite design and artificial neural network- genetic algorithm optimization approaches are successfully utilized to create prediction models and investigate the impact of critical variables in the radiolabeling of hydroxyapatite with 177Lu radionuclide.

Background: Many studies have reported Translocator Protein (TSPO) overexpression in many neurological disorders. Carbon-11[11C]PBR28 is a widely used TSPO Positron Emission Tomography (PET) radiopharmaceutical. We have compared HPLC-based purification with cartridge-based purification and performed PET-MR imaging in ALS patients.

Methods: [11C]PBR28 has been synthesized using an HPLC-based and cartridge-based purification technique in the FX2C chemistry module. All necessary quality controls were performed and compared. We injected 350 ± 20 MBq of the [11C]PBR28 intravenously into human patients (n = 6) diagnosed with amyotrophic lateral syndrome (ALS) and performed simultaneous PETMR dynamic imaging.

Results: The radiochemical purity was greater than 95% with both methods. The radiochemical yield was 11.8 ± 3.3%, and molar activity was 253 ± 20.9 GBq/μmol with a total synthesis time of 25 ± 2 min in the HPLC-based purification method. Whereas the radiochemical yield was 53.0 ± 3.6%, and molar activity was 885 ± 17.7 GBq/μmol with a total synthesis time of 12 ± 2 min in the cartridge-based purification method. We have compared PET-MR imaging of ALS limb onset (n =3) with ALS bulbar and limb onset (n =3), and there was a difference in time activity curves. The activity was higher in the precentral gyrus and cerebellum at 2.5 ± 0.5 min in bulbar cases with an SUV of 2.3 ± 0.3, whereas ALS limb onset showed the highest uptake at 0.5 ± 0.2 min with an SUV of 1.5 ± 0.2.

Conclusion: The cartridge-based method provided higher radiochemical yield and molar activity.

Objective: The Ga68-DOTATATE PET/CT scan is an alternative imaging modality for the follow-up of children with neuroblastoma when the I123-MIBG scan was negative or weak. Somatostatin receptors (SSR) can be expressed in neuroblastoma lesions, and when this happens, targeting these receptors may be a good alternative to treating this disease in addition to conventional treatments. Our aim is to focus on the interpretation of one of the physiological tracer uptake sites, the uncinate process of the pancreas, using DW-MRI scans.

Methods: We present and discuss 4 cases with neuroblastoma for a technical note. Imaging scans for SSR were performed using Ga68-DOTATATE PET/CT, and all showed varying degrees of increased uptake at the uncinate process of the pancreas on PET/CT images. We also performed a DW-MRI study to distinguish physiologic uptake in this region of the pancreas from metastatic involvement.

Results: Two of them showed diffusion restriction, with one of them also showing multiple masses within the liver. The other 2 children with high pancreatic uncinate process uptake did not exhibit any findings that indicated pancreatic involvement in the disease, based on DW-MRI images and clinical findings.

Conclusion: We recommend comparing DW-MRI scans and SSR-PET/CT scans to determine the true state of physiologically elevated SSR concentration and consequently indicate increased uptake on the images. The radiotracer concentration at the high uptake site did not appear to correlate with malignant involvement of the organ. The higher number of patients may allow a statistical comparison of the tracer with malignancy status.