Development and application of a set of mesh-based and age-dependent Chinese family phantoms for radiation protection dosimetry: Preliminary Data for external photon beams

A group of mesh-based and age-dependent family phantoms for Chinese populations were developed in this study. We implemented a method for deforming original RPI-AM and RPI-AF models into phantoms of different ages: 5, 10 ,15 and adult. More than 120 organs for each model were processed to match with the values of the Chinese reference parameters within 0.5%. All of these phantoms were then converted to voxel format for Monte Carlo simulations. Dose coefficients for adult models were counted to compare with those of RPI-AM and RPI-AF. The results show that there are significant differences between absorbed doses of RPI phantoms and these of our adult phantoms at low energies. Comparisons for the dose coefficients among different ages and genders were also made. it was found that teenagers receive more radiation doses than adults under the same irradiation condition. This set of phantoms can be utilized to estimate dosimetry for Chinese population for radiation protection, medical imaging, and radiotherapy

Monte Carlo calculations for reporting patient organ doses from interventional radiology

This paper describes a project to generate organ dose data for the purposes of extending VirtualDose software from CT imaging to interventional radiology (IR) applications. A library of 23 mesh-based anthropometric patient phantoms were involved in Monte Carlo simulations for database calculations. Organ doses and effective doses of IR procedures with specific beam projection, filed of view (FOV) and beam quality for all parts of body were obtained. Comparing organ doses for different beam qualities, beam projections, patients’ ages and patient’s body mass indexes (BMIs) which generated by VirtualDose-IR, significant discrepancies were observed. For relatively long time exposure, IR doses depend on beam quality, beam direction and patient size. Therefore, VirtualDose-IR, which is based on the latest anatomically realistic patient phantoms, can generate accurate doses for IR treatment. It is suitable to apply this software in clinical IR dose management as an effective tool to estimate patient doses and optimize IR treatment plans

Discutindo a educação ambiental no cotidiano escolar: desenvolvimento de projetos na escola formação inicial e continuada de professores

A presente pesquisa buscou discutir como a Educação Ambiental (EA) vem sendo trabalhada, no Ensino Fundamental e como os docentes desta escola compreendem e vem inserindo a EA no cotidiano escolar., em uma escola estadual do município de Tangará da Serra/MT, Brasil. Para tanto, realizou-se entrevistas com os professores que fazem parte de um projeto interdisciplinar de EA na escola pesquisada. Verificou-se que o projeto da escola não vem conseguindo alcançar os objetivos propostos por: desconhecimento do mesmo, pelos professores; formação deficiente dos professores, não entendimento da EA como processo de ensino-aprendizagem, falta de recursos didáticos, planejamento inadequado das atividades. A partir dessa constatação, procurou-se debater a impossibilidade de tratar do tema fora do trabalho interdisciplinar, bem como, e principalmente, a importância de um estudo mais aprofundado de EA, vinculando teoria e prática, tanto na formação docente, como em projetos escolares, a fim de fugir do tradicional vínculo “EA e ecologia, lixo e horta”.Facultad de Humanidades y Ciencias de la Educació

Influencing Factors of Total Skin Irradiation With Helical Tomotherapy

PurposeTo investigate the influencing factors of total skin irradiation (TSI) with helical tomotherapy for guiding the clinical selection of the suitable parameters and optimizing the plan quality and efficiency.Materials and MethodsSix patients with mycosis fungoides (MF) who received TSI were retrospectively selected. They were all dressed with 5 mm thick diving suits during the CT scan and treatment as a bolus to increase the superficial dose through buildup. The dose prescription was 24 Gy in 20 fractions and 5 times per week. During the planned pretreatment, Ring0, Ring1, Ring2, Ring3, and Ring4 of 1 cm thick away from the planning target volume (PTV) at the distances of 0, 1, 2, 3, and 4 cm and other normal tissues (NTs) were generated, respectively. The auxiliary structures were completely blocked during planning; while the field widths were 5 and 2.5 cm, the pitches were 0.287 and 0.215, the modulation factors were 4 and 3, and the other parameters remained consistent. Finally, the dose parameters of PTV and auxiliary structures, as well as the beam on time (BOT) and gantry period, were compared and analyzed.Resultswhen the auxiliary structures were completely blocked with distance to PTV (dPTV) above 3 cm were used, the mean dose (Dmean), conformity index (CI), and heterogeneity index (HI) of the PTV met the clinical requirements. As the dPTV gradually increased, the BOT decreased while the volume of normal tissue that received excessive radiation increased correspondingly. If the dPTV was less than 3 cm, the clinical requirements were not met. The field widths (FWs), pitches, and modulation factors (MFs) had no effect on PTVmean and the HI. The FW of 2.5 cm was slightly better than 5 cm for the CI. The FW and MF had a significant impact on the BOT, which gradually increased with decreasing FW and increasing MF. Pitch had no effect on the BOT.ConclusionDuring planning with TSI patients, dPTV is the key factor that has a significant influence on the plan quality. We found that the plan with the dPTV above 3 cm can meet clinical objectives. The BOT increases as the dPTV increases. The FWs also have an effect on the CI and BOT. Therefore, it is necessary to comprehensively balance these factors to optimize the quality and efficiency of the plan. We also found that different MFs and pitches have no obvious effect on the results.</jats:sec

Correlation between TCM Syndromes and Type 2 Diabetic Comorbidities Based on Fully Connected Neural Network Prediction Model

Objective. To predict the major comorbidities of type 2 diabetes based on the distribution characteristics of syndromes, and to explore the relationship between TCM syndromes and comorbidities of type 2 diabetes. Methods. Based on the electronic medical record data of 3413 outpatient visits from 995 type 2 diabetes patients with comorbidities, descriptive statistical methods were used to analyze the basic characteristics of the population, the distribution characteristics of comorbidities, and TCM syndromes. A neural network model for the prediction of type 2 diabetic comorbidities based on TCM syndromes was constructed. Results. Patients with TCM syndrome of blood amassment in the lower jiao were diagnosed with renal insufficiency with 95% test sensitivity. The patients with spleen deficiency combined with ascending counterflow of stomach qi and cold-damp patterns were diagnosed with gastrointestinal lesions with 92% sensitivity. The patients with TCM syndrome group of spleen heat and exuberance of heart fire were diagnosed as type 2 diabetes complicated with hypertension with a sensitivity of 91%. In addition, the prediction accuracy of combined neuropathy, heart disease, liver disease, and lipid metabolism disorder reached 70∼90% in TCM syndrome groups. Conclusion. The fully connected neural network model study showed that syndrome characteristics are highly correlated with type 2 diabetes comorbidities. Syndrome location is commonly in the heart, spleen, stomach, lower jiao, meridians, etc., while syndrome pattern manifests in states of deficiency, heat, phlegm, and blood stasis. The different combinations of disease location and disease pattern reflect the syndrome characteristics of different comorbidities forming the characteristic syndrome group of each comorbidity. Major comorbidities could be predicted with a high degree of accuracy through TCM syndromes. Findings from this study may have further implementations to assist with the diagnosis, treatment, and prevention of diabetic comorbidities at an early stage.</jats:p