Evaluating the Radioactive Waste Produced per Patient by Radiopharmaceutical Sources and Measuring the Radioactive Contamination of Surfaces and Staff at the Bushehr Nuclear Medicine Department.

Background: Nuclear medicine is an integral and developing field in diagnosing and treating diseases. Monitoring individuals' protection and radiation contamination in the workplace is vital for preserving working environments. Objective: This study aimed to monitor the nuclear medicine department's personnel, environment, and wastes to determine the level of occupational radiation and environmental pollution in Bushehr's nuclear medicine department. Material and Methods: In this cross-sectional study, the initial activity of each radioisotope, radiopharmaceutical, and radioactive waste was measured using a "well counter" daily for three months. Three irradiators' absorbed doses were measured using a direct reading dosimeter. The contamination was determined using an indirect wipe test method on various surfaces. A Geiger Müller dosimeter was employed to examine personnel's hands, clothing, and footwear. Results: The highest activity was observed in technetium waste (1118.31 mCi). Every irradiator received a lower absorption dose than the International Commission on Radiological Protection (ICRP) standard threshold. The majority of contamination was associated with the exercise test room (0.04 Bq/cm2) and its work surface (0.013 Bq/cm2), which were both below the threshold (0.5 Bq/cm2). Staff monitoring indicated that two nurses (10 and 11 individuals) had the highest contamination rate (23.7%). Conclusion: Daily assessment of the type, activity, and method of radiopharmaceutical administration to the patient is advantageous for waste management. Surface contamination monitoring can significantly contribute to the estimation of the level of radiation pollution in the environment.

Artificial intelligence in automatic classification of invasive ductal carcinoma breast cancer in digital pathology images.

Background: Breast cancer is one of the most causes of death in women. Early diagnosis and detection of Invasive Ductal Carcinoma (IDC) is an important key for the treatment of IDC. Computer-aided approaches have great potential to improve diagnosis accuracy. In this paper, we proposed a deep learning-based method for the automatic classification of IDC in whole slide images (WSI) of breast cancer. Furthermore, different types of deep neural networks training such as training from scratch and transfer learning to classify IDC were evaluated. Methods: In total, 277524 image patches with 50×50-pixel size form original images were used for model training. In the first method, we train a simple convolutional neural network (named it baseline model) on these images. In the second approach, we used the pre-trained VGG-16 CNN model via feature extraction and fine-tuning for the classification of breast pathology images. Results: Our baseline model achieved a better result for the automatic classification of IDC in terms of F-measure and accuracy (83%, 85%) in comparison with original paper on this data set and achieved a comparable result with a new study that introduced accepted-rejected pooling layer. Also, transfer learning via feature extraction yielded better results (81%, 81%) in comparison with handcrafted features. Furthermore, transfer learning via feature extraction yielded better classification results in comparison with the baseline model. Conclusion: The experimental results demonstrate that using deep learning approaches yielded better results in comparison with handcrafted features. Also, using transfer learning in histopathology image analysis yielded significant results in comparison with training from scratch in much less time.

Detection of MUC1-expressing ovarian cancer by C595 monoclonal antibody-conjugated SPIONs using MR imaging.

The aim of this study is to find out the development and application of MUC1-expressing ovarian cancer (OVCAR3) by C595 monoclonal antibody-conjugated superparamagnetic iron oxide nanoparticles (SPIONs) using MR imaging. At the end, its use as a nanosized contrast agent MR imaging probe for ovarian cancer detection was investigated. The strategy is to use SPIONs attached to C595 mAb that binds to the MUC1, to specifically detect ovarian cancer cells. Anticancer effects and MR imaging parameters of the prepared nanoconjugate was investigated both under in vitro and in vivo experiments. The characterization of nanoconjugate includes its size, cell toxicity, flow cytometry, Prussian blue staining test and its cellular uptake as well as its biodistribution, and MR imaging was also investigated. The findings of the study showed good tumor accumulation and detection, no in vivo toxicity, and potential selective antiovarian cancer activity. Overall, based on the findings SPIONs-C595 nanosized probe is a selective ovarian molecular imaging modality. Further subsequent clinical trials appear warranted.

Functionalized magnetic nanoparticles for the detection and quantitative analysis of cell surface antigen.

Cell surface antigens as biomarkers offer tremendous potential for early diagnosis, prognosis, and therapeutic response in a variety of diseases such as cancers. In this research, a simple, rapid, accurate, inexpensive, and easily available in vitro assay based on magnetic nanoparticles and magnetic cell separation principle was applied to identify and quantitatively analyze the cell surface antigen expression in the case of prostate cancer cells. Comparing the capability of the assay with flow cytometry as a gold standard method showed similar results. The results showed that the antigen-specific magnetic cell separation with antibody-coated magnetic nanoparticles has high potential for quantitative cell surface antigen detection and analysis.

Synthesis and in vitro evaluation of MR molecular imaging probes using J591 mAb-conjugated SPIONs for specific detection of prostate cancer.

Carcinoma of the prostate is the most frequent diagnosed malignant tumor in men and is the second leading cause of cancer-related death in this group. The cure rate of prostate cancer is highly dependent on the stage of disease at the diagnosis and early detection is key to designing effective treatment strategies. The objective of the present study is to make a specific MR imaging probe for targeted imaging of cancer cells. We take advantage of the fact that many types of prostate cancer cells express high levels of prostate-specific membrane antigen (PSMA) on their cell surface. The imaging strategy is to use superparamagnetic iron oxide nanoparticles (SPIONs), attached to an antibody (J591) that binds to the extracellular domain of PSMA, to specifically enhance the contrast of PSMA-expressing prostate cancer cells. Conjugation of mAb J591 to commercial SPIONs was achieved using a heterobifunctional linker, sulfo-SMCC. Two types of prostate cancer cell lines were chosen for experiments: LNCaP (PSMA+) and DU145 (PSMA-). MRI and cell uptake experiments demonstrated the high potential of the synthesized nanoprobe as a specific MRI contrast agent for detection of PSMA-expressing prostate cancer cells.

Superparamagnetic iron oxide-C595: Potential MR imaging contrast agents for ovarian cancer detection.

Superparamagnetic iron oxide nanoparticles (SPIONs), have played an important role in the promotion of image contrast in magnetic resonance imaging modality. The objective of present study is describing SPIONs conjugated with C595 monoclonal antibody (mAb) against MUC1-expressing ovarian cancer (OVCAR3) cell. Magnetic resonance imaging parameters of the prepared nanoconjugate was investigated in vitro: characterization, cell toxicity, flow cytometry, Prussian blue staining, and cellular uptake as well as biodistribution and magnetic resonance signal intensities under in vivo conditions were also investigated. Magnetic resonance imaging and biodistribution results showed good tumor accumulation and detection, no cytotoxicity, and potential selective as anti-ovarian cancer. In conclusion, based on the findings SPIONs-C595 nanosized-probe is potentially, a selective ovarian molecular imaging tool. Further subsequent in vivo studies and clinical trials are warranted.

The correlation between high background radiation and blood level of the trace elements (copper, zinc, iron and magnesium) in workers of Mahallat's hot springs.

BACKGROUND: Blood trace elements of people who are living or working in areas with high radioactivity have an important role in vital processes. The scope of this work is to measure the concentrations of blood trace elements of permanent workers in Mahallat's hot springs. MATERIALS AND METHODS: In this study, 30 persons of hot springs permanent workers in Mahallat (mean background dose: 21.6 mSv) were selected as a sample group and 30 persons with similar social class who received a normal background dose and were not engaged in any type of radiation work were selected as a control group. Five milliliters of blood sample was taken from each person and after preparation of the samples, the concentration of copper, iron, zinc and magnesium was measured with atomic absorption spectrometry. RESULTS: The average concentration of copper, iron, zinc and magnesium in the irradiated group was 0.67±0.11, 1.54±0.41, 1.76±0.34 and 19.78±1.42, respectively and in the control group, was 0.78±0.06, 1.06±0.15, 0.85±0.05 and 20.34±0.57, respectively. Values of copper and magnesium in workers were found to be less than that of the control group. The mean concentration of iron and zinc in permanent workers was significantly more than that of the control group (P<0.05). Overall, no meaningful statistical correlation was found between the concentration of magnesium among the permanent presence in the area (P>0.05). CONCLUSIONS: The results showed that increases in the average concentrations of Zn and Fe and decreases in the concentration of Cu of workers was observed. The finding also showed that the probability of chronic exposure effects on body trace element concentrations was increases and each value of the doses could be dangerous.