Current radiopharmaceuticals最新文献

Radiopharmaceuticals are in the diagnosis and treatment of cancerous and noncancerous diseases, and a hope for optimistic effort in the field of nuclear medicine. They play a crucial role in clinical nuclear medicine by providing a tool to comprehend human disease and create efficient treatments. A detailed analysis is provided regarding the crux of molecular imaging including PET and SPECT overview for the detection of cancers. For a specified understanding of radiation therapy, topics include ranging from the selection of radionuclide to its development and manufacture, and dosage requirements to establishing the importance of I- 131 Radiotherapy in thyroid cancer. In this review, we also discussed the current state of the art of nuclear medicine in thyroid cancer, including the role of radioiodine (RAI) therapeutic scans in the diagnosis of differentiated thyroid cancer. In addition, we established a brief outlook into the current status of the research in thyroid cancer and discussed the future directions in this field.

Background: Employees may be exposed to different kinds of ionizing radiation at work. When ionizing radiation interacts with human cells, it can cause damage to the cells and genetic material. Therefore, one of the scientists' primary objectives has always been to create the best radiation-shielding materials. Glass could offer promising shielding material resulting from the high flexibility of composition, simplicity of production, and good thermal stability.

Materials and methods: The melt-quenching technique was used to create a glass having the following formula: 50% P₂O₅+20% Na₂O+20% Fe₂O₃+10% X, where X = As₂O₃, SrO, BaO, CdO, and Sb₂O₃ mol %. The impact of the different heavy metal additions on the structure of the glass networks was studied using FTIR spectroscopy. Glass's ability to attenuate neutrons and/or charged particles has been theoretically investigated. The performance of the developed glass as a shield was examined by a comparison against commercial glass (RS 253 G18), ordinary concrete (OC), and water (H₂O).

Results: For charged particle radiations (Electrons, Protons, and Alpha), the shielding parameters like the mass stopping power, the projected range, and the effective atomic number were evaluated, where S5/Sb glass achieves the best performance. In the case of Neutrons, the results values reveal that S3/Ba glass ( Σ_R = 0.105) is the best-modified glass for neutron shielding.

Conclusion: Among all the investigated glasses, S5/Sb glass composition has a smaller range and provides superior protection against charged particles. In contrast, the S3/Ba glass composition is a superior choice for shielding against neutron radiation.

Immunotherapy has emerged as a very considerable and potent therapeutic method in which immune inhibitors have gained a lot of attention in the curative field of various cancers. Under certain circumstances, when radiotherapy is accompanied by immunotherapy, the efficacy of the therapeutic procedure increases. Irradiated tumor cells follow a pathway called immunogenic cell death, which targets tumor associated antigens. The application of radiolabeled antibodies under the concept of "radioimmunotherapy" (RIT) makes the synergistic targeted therapeutic effect possible. Since antibodies themselves are cytotoxic, they can kill the cells that not only bind but are within the path length of their radiation emissions. RIT can be categorized as a substantial progress in nuclear medicine. The main concept of RIT includes targeting specified tumor-expressing antibodies. The mentioned purpose is achievable by formulation of radiolabeled antibodies, which could be injected intravenously or directly into the tumor, as well as compartmentally into a body cavity such as the peritoneum, pleura, or intrathecal space. RIT has demonstrated very optimistic therapeutic outcomes in radioresistant solid tumors. Wide ranges of efforts are accomplished in order to improve clinical trial accomplishments. In this review, we intend to summarize the performed studies on RIT and their importance in medicine.

Background: Head and Neck Squamous Cell Carcinoma (HNSCC) is a malignant tumor with a high degree of malignancy, invasiveness, and metastasis rate. Radiotherapy, as an important adjuvant therapy for HNSCC, can reduce the postoperative recurrence rate and improve the survival rate. Identifying the genes related to HNSCC radiotherapy resistance (HNSCC-RR) is helpful in the search for potential therapeutic targets. However, identifying radiotherapy resistance-related genes from tens of thousands of genes is a challenging task. While interactions between genes are important for elucidating complex biological processes, the large number of genes makes the computation of gene interactions infeasible.

Methods: We propose a gene selection algorithm, RGIE, which is based on ReliefF, Gene Network Inference with Ensemble of Trees (GENIE3) and Feature Elimination. ReliefF was used to select a feature subset that is discriminative for HNSCC-RR, GENIE3 constructed a gene regulatory network based on this subset to analyze the regulatory relationship among genes, and feature elimination was used to remove redundant and noisy features.

Results: Nine genes (SPAG1, FIGN, NUBPL, CHMP5, TCF7L2, COQ10B, BSDC1, ZFPM1, GRPEL1) were identified and used to identify HNSCC-RR, which achieved performances of 0.9730, 0.9679, 0.9767, and 0.9885 in terms of accuracy, precision, recall, and AUC, respectively. Finally, qRT-PCR validated the differential expression of the nine signature genes in cell lines (SCC9, SCC9-RR).

Conclusion: RGIE is effective in screening genes related to HNSCC-RR. This approach may help guide clinical treatment modalities for patients and develop potential treatments.

Background: Patients undergoing radiotherapy are prone to radiation-induced gastrointestinal injury. Piperine is an alkaloid component in black pepper with a unique chemopreventive activity against oxidative stress-related damage in healthy tissues. The purpose of this study was to investigate the effects of piperine on intestinal damage.

Methods: In this study, mice were divided into eight groups: including the control, piperine (10, 25, and 50 mg/kg), radiation (6 Gy), and piperine+radiation (10, 25 and 50 mg/kg + 6 Gy) groups. The radioprotective effects of piperine were evaluated by biochemical (MDA, GSH, and PC) and histopathological assessments in colon tissues.

Results: The 10 mg/kg dose of piperine significantly reduced the levels of oxidative stress biomarkers compared to the group that received only radiation. In addition, pre-treatment with 10 mg/kg piperine diminished the histopathological changes like vascular congestion in the submucosa, while the dose of 50 mg/kg led to the infiltration of inflammatory cells.

Conclusion: Based on this study, it is concluded that piperine, at low dose, with its antioxidant properties, could reduce the colon damage caused by radiation.

Background: Radiation exposure has been linked to the development of brain damage and cognitive impairment, but the protective effect and mechanism of Lycium barbarum pills (LBP) on radiation-induced neurological damage remains to be clarified.

Methods: Behavioral tests and immunohistochemical studies were conducted to evaluate the protective effects of LBP extract (10 g/kg orally daily for 4 weeks) against radiation-induced damage on neurogenesis and cognitive function in Balb/c mice exposed to 5.5 Gy X-ray acute radiation.

Results: The results showed that the LBP extract significantly improved body weight loss, locomotor activity and spatial learning and memory. Immunohistochemical tests revealed that the LBP extract prevented the loss of proliferating cells, newly generated neurons and interneurons, especially in the subgranular area of the dentate gyrus.

Conclusion: The findings suggest that LBP is a potential neuroprotective drug for mitigating radiation-induced neuropsychological disorders.

Introduction: C-X-C Chemokine receptor type 4 (CXCR4) is often overexpressed or overactivated in different types and stages of cancer disease. Therefore, it is considered a promising target for imaging and early detection of primary tumors and metastasis. In the present research, a new cyclo-peptide radiolabelled with ^99mTc, ^99mTc-Cyclo [D-Phe-D-Tyr-Lys (HYNIC)- D-Arg-2-Nal-Gly-Lys(iPr)], was designed based on the parental LY251029 peptide, as a potential in vivo imaging agent of CXCR4-expressing tumors.

Methods: The radioligand was successfully prepared using the method of Fmoc solid-phase peptide synthesis and was evaluated in biological assessment. Molecular docking findings revealed high affinity (binding energy of -9.7 kcal/mol) and effective interaction of Cyclo [D-Phe- D-Tyr-Lys (HYNIC)-D-Arg-2-Nal-Gly-Lys(iPr)] in the binding pocket of CXCR4 receptor (PDB code: 3OE0) as well.

Result: The synthesized peptide and its purity were assessed by both reversed-phase high-performance liquid chromatography (RP-HPLC) and mass spectroscopy. High stability (95%, n = 3) in human serum and favorable affinity (Kd = 28.70 ± 13.56 nM and Bmax = 1.896 ± 0.123 fmol/mg protein) in the B16-F10 cell line resulted. Biodistribution evaluation findings and planar image interpretation of mice both showed high affinity and selectivity of the radiotracer to the CXCR4 receptors.

Conclusion: Therefore, the findings indicate this designed radioligand could be used as a potential SPECT imaging agent in highly proliferated CXCR4 receptor tumors.

Background: Prostate-specific membrane antigen (PSMA) is an ideal target for molecular imaging and targeted radionuclide therapy in prostate cancer. Consequently, various PSMA ligands were developed. Some of these molecules are functionalized with a chelator that can host radiometals, such as ⁶⁸Ga for PET imaging. The ⁶⁸Ga radiolabeling step benefits from process automation, making it more robust and reducing radiation exposure.

Objective: To design a single automated radiolabeling protocol for the GMP-compliant preparation of [⁶⁸Ga]Ga-PSMA-11, transposable to the production of [⁶⁸Ga]Ga-PSMA-617 and [⁶⁸Ga]Ga-PSMA-I&T.

Methods: A GAIA^® synthesis module and a GALLIAD^® generator were used. Radio-TLC and radio-HPLC methods were validated for radiochemical purity (RCP) determination. Three [⁶⁸Ga]Ga-PSMA-11 validation batches were produced and thoroughly tested for appearance and pH, radionuclide identity and purity, RCP, stability, residual solvent and sterility. Minimal modifications were made to the reagents and disposables for optimal application to other PSMA ligands.

Results: [⁶⁸Ga]Ga-PSMA-11 for clinical application was produced in 27 min. The 3 validation batches met the quality criteria expected by the European Pharmacopoeia to allow routine production. For optimal transposition to PSMA-617, the solid phase extraction cartridge was changed to improve purification of the radiolabeled product. For application to PSMA-I&T, the buffer solution initially used was replaced by HEPES 2.7 M to achieve good radiochemical yields. Residual HEPES content was checked in the final product and was below the Ph. Eur. threshold.

Conclusion: A single automated radiolabeling method on the GAIA^® module was developed and implemented for ⁶⁸Ga radiolabeling of 3 PSMA ligands, with slight adjustments for each molecule.

Introduction: Low-energy proximal femur fractures in elderly patients result from factors, like osteoporosis and falls. These fractures impose high rates of economic and social costs. In this study, we aimed to build predictive models by applying machine learning (ML) methods on radiomics features to predict low-energy proximal femur fractures.

Methods: Computed tomography scans of 40 patients (mean ± standard deviation of age = 71 ± 6) with low-energy proximal femur fractures (before a fracture occurs) and 40 individuals (mean ± standard deviation of age = 73 ± 7) as a control group were included. The regions of interest, including neck, trochanteric, and intertrochanteric, were drawn manually. The combinations of 25 classification methods and 8 feature selection methods were applied to radiomics features extracted from ROIs. Accuracy and the area under the receiver operator characteristic curve (AUC) were used to assess ML models' performance.

Results: AUC and accuracy values ranged from 0.408 to 1 and 0.697 to 1, respectively. Three classification methods, including multilayer perceptron (MLP), sequential minimal optimization (SMO), and stochastic gradient descent (SGD), in combination with the feature selection method, SVM attribute evaluation (SAE), exhibited the highest performance in the neck (AUC = 0.999, 0.971 and 0.971, respectively; accuracy = 0.988, 0.988, and 0.988, respectively) and the trochanteric (AUC = 1, 1 and 1, respectively; accuracy = 1, 1 and 1, respectively) regions. The same methods demonstrated the highest performance for the combination of the 3 ROIs' features (AUC = 1, 1 and 1, respectively; accuracy =1, 1 and 1, respectively). In the intertrochanteric region, the combination methods, MLP + SAE, SMO + SAE, and SGD + SAE, as well as the combination of the SAE method and logistic regression (LR) classification method exhibited the highest performance (AUC = 1, 1, 1 and 1, respectively; accuracy= 1, 1, 1 and 1, respectively).

Conclusion: Applying machine learning methods to radiomics features is a powerful tool to predict low-energy proximal femur fractures. The results of this study can be verified by conducting more research on bigger datasets.