Journal of Radiation Research and Applied Sciences最新文献

Cell division cycle associated 7 (CDCA7) functions in Myc-mediated tumorigenesis. Glycosylation, which is frequently altered in malignancies, is regulated by polypeptide N-acetylgalactosaminyltransferase 6 (GALNT6) and is crucial for cancer growth. However, their prognostic value and biological roles in bladder cancer (BLCA) remain unknown. The primary objective of this research is to investigate the potential applications of cutting-edge nanomaterials in the therapeutic management of bladder cancer. A key focus of the study is to thoroughly examine the influence and involvement of the CDCA7 and GALNT6 genes in the treatment process. We assessed clinicopathological traits and prognostic value of CDCA7 and GALNT6 in BLCA.CDCA7 and GALNT6 were overexpressed in BLCA tissues from TCGA-BLCA datasets. Changes in BLCA were associated with DNA-binding transcription activator activity, mitotic cell cycle phase changes, transcription regulator complex, p53 signaling pathway, cell cycle, and pathways associated with transcriptional dysregulation in cancer. Survival analysis showed that they were crucial to the incidence and prognosis of BLCA. The expression levels of CDCA7 and GALNT6 were significantly correlated with the therapeutic effect of nanomaterials, and their down-regulation could enhance the anti-tumor effect of nanomaterials. Patients with BLCA who expressed high CDCA7 and GALNT6 levels had poorer disease outcome compared with patients with low levels.These findings have new implications for precision therapy and individualized risk stratification that will benefit patients with BLCA.

This paper presents a comprehensive simulation and calculation study of the radiation attenuation parameters for a newly developed bismuth boro tellurite glass system. Through advanced computational modeling and theoretical analysis, linear and mass attenuation coefficients (μ and μ/ρ), and other key radiation attenuation parameters of the studied glass system are thoroughly investigated across a range of photon energies. Utilizing state-of-the-art simulation techniques and theoretical models, the radiation shielding effectiveness of the glass system is evaluated, offering insights into its potential applications in radiation protection and shielding. We found that the Σ_R values for fast neutrons are 0.10013, 0.10221, 0.10953, 0.11347 and 0.11383 cm⁻¹ for BTBiBV-1, BTBiBV-2, BTBiBV-3, BTBiBV-4, and BTBiBV-5, respectively. The results of this study contribute to the understanding of the radiation attenuation properties of bismuth boro tellurite glasses and provide valuable information for their utilization in various fields, including medical imaging, nuclear power, and industrial radiography. Additionally, accurate modeling and characterization of attenuation parameters across different photon energies are crucial for designing effective radiation protection strategies and ensuring the safety of personnel and equipment in radiation environments.

Drug delivery with photodynamic therapy may improve breast cancer treatment. Drug delivery based polymeric nanoparticles, especially those made from natural polysaccharides, are promising cancer treatment carriers due to their biocompatibility and potential. This study involved the synthesis of Koliphore-elp35/Folic Acid-conjugated (KoliFA) nanoparticles for the concurrent delivery of paclitaxel and the photosensitizer indocyanine green (ICG) to breast cancer cells, aiming to improve the effectiveness of combined chemotherapy and PDT by using near-infrared (NIR) laser to activate the treatment. The cancer MCF-7 and normal MCF-10 breast cell lines were exposed to the nanoparticle formulation. The MTT assay evaluated the cytotoxic effects and established the IC₅₀ values. The result showed that KoliFA is a near sphere-shaped particle with the average size of core KoliFA 390 nm and a layer of FA on the outer side of the nanoparticles its size increased to 1372 nm after loading PTX, and the zeta potential of KoliFA −12.5 mV decreased to −11mV after loading. The cytotoxicity of the KoliFA-PTX-ICG in MCF-7 cells increased, and reducing IC₅₀ to 9.360 μg/ml compared to MCF-10 cells, this decrease suggests that PDT effect of ICG is a key factor in improving treatment efficacy by increasing ROS generation and increased sensitivity to treatment. Flow cytometry indicated increased apoptosis in MCF-7 cells after treatment with KoliFA-PTX-ICG + NIR laser. This study demonstrated that the KoliFA-PTX-ICG could be a promising platform for combination chemo-photodynamic therapy for breast cancer treatment.

Gastric examination is a common endoscopic procedure that can be used to assess stomach diseases and lesions. However, because the stomach examination requires the use of radiation imaging technology, patients are exposed to radiation risks. Therefore, the aim of this study is to develop a specialized database of endoscopy and integrate it with an image annotation platform to achieve effective control of gastric examination radiation. An image labeling platform was developed to label gastric lesions and structures, annotate and label endoscopic images, and describe the details of gastric lesions more comprehensively and accurately. A complete radiation imaging control system for gastric examination was formed by integrating professional database and image labeling platform. Through this integrated system, doctors can quickly access the endoscopy images in the database when performing stomach exams, and label lesions on the image labeling platform to more accurately evaluate the lesions and structure of the stomach, while reducing the number of times patients undergo radiation examinations. The results show that the radiation imaging of gastric examination can be effectively controlled through the integration of endoscopy database and image annotation platform. This integrated system helps to improve the accuracy and safety of the examination, and has important clinical application value for both doctors and patients.

Objectives

To evaluate the image quality and radiation dose in thoracic-abdominal-pelvic computed tomography enhancement using ATVM (Automatic Tube Voltage Modulation)coupled with AIIR versus routine tube voltage combined with Karl-3D IR. The optimal noise level for the AIIR in thoracic-abdominal-pelvic CT enhancement was also determined.

Methods

Group A was scanned using ATVM, and images were reconstructed using AIIR with 1–5 noise levels. Group B was scanned and reconstructed using the fixed tube voltage (120 kVp) combined with Karl 3D level 5 IR. The image quality of the reconstructed images of AIIR with 1–5 noise levels were compared and the best image reconstruction noise level for AIIR was preferred. Image quality and radiation dose were statistically analyzed for group A (best image reconstruction noise level for AIIR) and group B.

Results

AIIR level 3 is the optimal noise level for CT-enhanced image reconstruction of the thorax, abdomen, and pelvis. The mean SNR, CNR, and subjective evaluation of AIIR level 3 Group A images were better than those of Karl 3D level 5 Group B images (p < 0.05). The mean SSDE and the mean ED of the AIIR Group A patients were reduced by 46% and 41%, respectively, compared with those of Group B.

Conclusions

ATVM technology combined with the AIIR algorithm improved image quality and reduced patient radiation dose in thoracic-abdominal-pelvic CT scans. The optimal noise level for the reconstruction of high-quality arterial and venous-phase images was AIIR level 3.

Background

Pancreatic cancer is a devastating disease with a poor prognosis, and radiation therapy plays a crucial role in its treatment and management. Conventional radiation therapy (RT) techniques have limitations in delivering adequate doses to the tumor while sparing surrounding normal tissues. However, modern RT techniques such as intensity-modulated radiation therapy (IMRT), volumetric modulated arc therapy (VMAT), and stereotactic body radiation therapy (SBRT) have led to the development of novel approaches that can reduce toxicity. The incorporation of advanced imaging modalities, like four-dimensional computed tomography (4D-CT) and magnetic resonance imaging (MRI), enables enhancement of tumor control and improves conformality and treatment outcomes. Additionally, using flattening filter-free (FFF) beams can further enhance treatment efficiency and efficacy.

Purpose

This study aims to compare two different VMAT techniques using two different treatment planning systems (TPSs), Monaco and Eclipse, in the treatment of pancreatic cancer II stage infiltrating duct carcinoma patients using an FFF photon beam.

Materials and methods

20 pancreatic cancer II stage infiltrating duct carcinoma patients were retrospectively analyzed, and each patient's plans were designed using the two TPSs. The dose distribution of the target using 6 MV FFF for TrueBeam-Varian and organs at risk (OARs) were compared. The monitor unit (MU), treatment time, conformity (CI), and homogeneity (HI) indices were also evaluated.

Results

For pancreatic cancer patients, the mean dose of the planning target volume (PTV) in the Monaco plan was lower than the Eclipse plan. The plan evaluation parameters in Monaco and Eclipse were similar without significant differences (p-value = 0.152). The Monaco plan was better than the Eclipse plan regarding mean dose and V15Gy of the kidneys; the spinal cord was lowest in the Monaco plan, and the maximum dose and V45Gy of the spinal cord were 592.1 cGy and 1.37% lower than the Eclipse plan, respectively.

Conclusion

The VMAT Monaco plan is a favorable TPS for pancreatic cancer patients, providing improved sparing of critical organs while maintaining adequate target coverage.

In breast cancer, early diagnosis and treatment method hold paramount significance for the augmented survival rates. Through a comprehensive dataset including clinical and genomic information, this study assesses the diverse analytical techniques used in breast cancer classification by the employment of four different machine learning algorithms. There were notable differences in classification findings, emphasizing the necessity of using adept analytical tools to improve the accuracy of breast cancer classification. Among individual algorithms, LGBM has the highest F1 score of 99.2% and a remarkable accuracy of 98.9%. Ensembles comprising AdaBoost, GBM, and RGF outperformed individual techniques with an astonishing 99.5% accuracy. The best ensemble algorithms prioritize features like worst texture, worst concave points, mean concave points, and mean texture, crucial for the classification. The examination of the advantages of ensemble learning methods, which combine predictions from many classifiers to improve classification performance, is at the heart of this the study. In particular, it is revealed how the k-fold and stratified shuffle split cross-validation methods differ in the classification results, providing clinicians a thorough understanding of the clinical ramifications to decipher the complex facets of breast cancer classification and identify crucial tumor traits that can distinguish malignant from benign cases.

In this paper, when the life test is truncated at a pre-determined time, new acceptance sampling plans (ASP) are developed based on percentile lifetime as a quality parameter for the extended generalized exponential distribution (EGED). An inspection of a representative sample of goods or materials from a big lot or batch is used in quality control testing under acceptance sampling plans to assess whether the lot satisfies predetermined quality requirements. For the suggested new acceptance sampling plans, the minimum sample sizes needed to emphasize the determined lifetime percentile are obtained for a given customer's risk. The sample plans' operating characteristic function values and the producer's risk are built at various quality levels for some distribution parameters. Some numerical examples are presented to show how the suggested ASP can be used. A genuine industrial data set from a top Korean automobile is fitted to the EGED relative to other competitors and the applicability of the suggested ASP is illustrated. It is found that the suggested ASP for the EGED can be applied by the researchers in production engineering fields.

A contrast agent is clinically employed to aid the visualization of organs and structures when imaged by radiation based diagnostic imaging modalities. Iodinated contrast agents have been used for decades, but they carry a heightened risk of adverse allergy reactions and contrast-induced nephropathy. This study investigated the contrast enhancement characteristics of gold nanoparticles (AuNPs) through diverse cancer diagnostic imaging modalities as a potential alternative to the iodine-based contrasts. Solutions of 1.9 nm and 15 nm AuNPs, ranging from 3 to 20 mM concentrations, were prepared, alongside a low osmolar non-ionic iodine contrast agent as a control. All samples were scanned and imaged using x-ray computed tomography scanner (CT-Scan), digital mammography, digital radiography, and fluoroscopy modalities. The contrast-to-noise ratio (CNR) was measured to study the relationship between the size, the concentrations, and the influence of the tube voltage over the image contrast enhancement efficacy of the agents. A lower concentration of AuNPs produced lower CNR values. In addition, the 1.9 nm size of AuNPs caused lower CNR than the 15 nm AuNPs when tested with the highest concentration of 20 mM. High CT's HU values for both sizes of AuNPs indicated substantial contrast enhancement compare to iodine. Although the 15 nm AuNPs might set off higher CNR, a better quality of image contrast enhancement was also observed compared to the 1.9 nm AuNPs. The findings also suggested that the contrast enhancement by AuNPs is highly dependent on the modalities' type and x-rays energy. In conclusion, AuNPs could be applied as a contrast agent in various diagnostic imaging modalities representing promising approach in cancer detection particularly in cases of patients having adverse reactions towards the iodine based contrast agents.

Background

X-ray imaging has been applied in various fields. However, the noise in X-ray images reduces the image quality and affects subsequent detection.

Aims

A denoising method is developed to solve the problem of the Poisson-Gaussian mixed noise caused by X-ray imaging.

Method

ology: A new threshold function and an improved threshold are proposed in this paper. Furthermore, an improved denoising method, namely the improved generalized Anscombe with shearlet transform (improved GA-ST), is developed based on the above proposed algorithms. After theoretical derivation, experiments and parameter analysis, the proposed method is applied to actual X-ray images.

Results

The results show that the new threshold function is continuous, asymptotic, and has no inherent deviation, which solves the problems existing in traditional threshold functions. In addition, the improved GA-ST method can reduce Poisson-Gaussian mixed noise at different levels. As for actual X-ray images, the improved GA-ST method outperforms the other methods, and the BRISQUE descent ratios all exceed 25%.

Conclusions

The improved GA-ST method proposed in this paper can effectively reduce the noise in X-ray images and meet the requirements of actual applications based on MATLAB platform.