709 resultados para IMRT QA
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Mode of access: Internet.
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Mode of access: Internet.
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PHAR-QA, funded by the European Commission, is producing a framework of competences for pharmacy practice. The framework is in line with the EU directive on sectoral professions and takes into account the diversity of the pharmacy profession and the on-going changes in healthcare systems (with an increasingly important role for pharmacists), and in the pharmaceutical industry. PHAR-QA is asking academia, students and practicing pharmacists to rank competences required for practice. The results show that competences in the areas of drug interactions, need for drug treatment and provision of information and service were ranked highest whereas those in the areas of ability to design and conduct research and development and production of medicines were ranked lower. For the latter two categories, industrial pharmacists ranked them higher than did the other five groups
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Background and objectives: The goal of the PHAR-QA (Qualityassurance in European pharmacy education and training) project isthe production of a European framework of competences for pharmacypractice. This PHAR-QA framework (www.phar-qa.eu) will beEuropean and consultative i.e. it will be used for harmonization—butwill not to replace existing national QA systems.Methods: Using the proposals for competences produced by the previousPHARMINE(Pharmacy education in Europe; www.pharmine.eu) project, together with those of other sources, the authors produced a listof 68 personal and patient care competencies. Using internet surveytools the stakeholders—European pharmacy community (universitydepartment staff and students, community, hospital and industrialpharmacists, as well as pharmacists working in clinical biology andother branches, together with representatives of chambers and associations)—were invited to rank the proposals and add comments.Results and conclusions: Pharmacology and pharmacotherapy togetherwith competences such as ‘‘supply of appropriate medicinestaking into account dose, correct formulation, concentration, administrationroute and timing’’ ranked high. Other topics such as ‘‘currentknowledge of design, synthesis, isolation, characterisation and biologicalevaluation of active substances’’ ranked lower.Implications for practice: In the short term, it is anticipated that thissurvey will stimulate a productive discussion on pharmacy educationand practice by the various stakeholders. In the long term, thisframework could serve as a European model framework of competencesfor pharmacy practice.Acknowledgements: With the support of the Lifelong Learningprogramme of the European Union: 527194-LLP-1-2012-1-BEERASMUS-EMCR. This publication reflects the views only of theauthors; the Commission cannot be held responsible for any usewhich may be made of the information contained therein.
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Knowledge-based radiation treatment is an emerging concept in radiotherapy. It
mainly refers to the technique that can guide or automate treatment planning in
clinic by learning from prior knowledge. Dierent models are developed to realize
it, one of which is proposed by Yuan et al. at Duke for lung IMRT planning. This
model can automatically determine both beam conguration and optimization ob-
jectives with non-coplanar beams based on patient-specic anatomical information.
Although plans automatically generated by this model demonstrate equivalent or
better dosimetric quality compared to clinical approved plans, its validity and gener-
ality are limited due to the empirical assignment to a coecient called angle spread
constraint dened in the beam eciency index used for beam ranking. To eliminate
these limitations, a systematic study on this coecient is needed to acquire evidences
for its optimal value.
To achieve this purpose, eleven lung cancer patients with complex tumor shape
with non-coplanar beams adopted in clinical approved plans were retrospectively
studied in the frame of the automatic lung IMRT treatment algorithm. The primary
and boost plans used in three patients were treated as dierent cases due to the
dierent target size and shape. A total of 14 lung cases, thus, were re-planned using
the knowledge-based automatic lung IMRT planning algorithm by varying angle
spread constraint from 0 to 1 with increment of 0.2. A modied beam angle eciency
index used for navigate the beam selection was adopted. Great eorts were made to assure the quality of plans associated to every angle spread constraint as good
as possible. Important dosimetric parameters for PTV and OARs, quantitatively
re
ecting the plan quality, were extracted from the DVHs and analyzed as a function
of angle spread constraint for each case. Comparisons of these parameters between
clinical plans and model-based plans were evaluated by two-sampled Students t-tests,
and regression analysis on a composite index built on the percentage errors between
dosimetric parameters in the model-based plans and those in the clinical plans as a
function of angle spread constraint was performed.
Results show that model-based plans generally have equivalent or better quality
than clinical approved plans, qualitatively and quantitatively. All dosimetric param-
eters except those for lungs in the automatically generated plans are statistically
better or comparable to those in the clinical plans. On average, more than 15% re-
duction on conformity index and homogeneity index for PTV and V40, V60 for heart
while an 8% and 3% increase on V5, V20 for lungs, respectively, are observed. The
intra-plan comparison among model-based plans demonstrates that plan quality does
not change much with angle spread constraint larger than 0.4. Further examination
on the variation curve of the composite index as a function of angle spread constraint
shows that 0.6 is the optimal value that can result in statistically the best achievable
plans.
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Purpose: To investigate the effect of incorporating a beam spreading parameter in a beam angle optimization algorithm and to evaluate its efficacy for creating coplanar IMRT lung plans in conjunction with machine learning generated dose objectives.
Methods: Fifteen anonymized patient cases were each re-planned with ten values over the range of the beam spreading parameter, k, and analyzed with a Wilcoxon signed-rank test to determine whether any particular value resulted in significant improvement over the initially treated plan created by a trained dosimetrist. Dose constraints were generated by a machine learning algorithm and kept constant for each case across all k values. Parameters investigated for potential improvement included mean lung dose, V20 lung, V40 heart, 80% conformity index, and 90% conformity index.
Results: With a confidence level of 5%, treatment plans created with this method resulted in significantly better conformity indices. Dose coverage to the PTV was improved by an average of 12% over the initial plans. At the same time, these treatment plans showed no significant difference in mean lung dose, V20 lung, or V40 heart when compared to the initial plans; however, it should be noted that these results could be influenced by the small sample size of patient cases.
Conclusions: The beam angle optimization algorithm, with the inclusion of the beam spreading parameter k, increases the dose conformity of the automatically generated treatment plans over that of the initial plans without adversely affecting the dose to organs at risk. This parameter can be varied according to physician preference in order to control the tradeoff between dose conformity and OAR sparing without compromising the integrity of the plan.
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Le cancer pulmonaire est la principale cause de décès parmi tous les cancers au Canada. Le pronostic est généralement faible, de l'ordre de 15% de taux de survie après 5 ans. Les déplacements internes des structures anatomiques apportent une incertitude sur la précision des traitements en radio-oncologie, ce qui diminue leur efficacité. Dans cette optique, certaines techniques comme la radio-chirurgie et la radiothérapie par modulation de l'intensité (IMRT) visent à améliorer les résultats cliniques en ciblant davantage la tumeur. Ceci permet d'augmenter la dose reçue par les tissus cancéreux et de réduire celle administrée aux tissus sains avoisinants. Ce projet vise à mieux évaluer la dose réelle reçue pendant un traitement considérant une anatomie en mouvement. Pour ce faire, des plans de CyberKnife et d'IMRT sont recalculés en utilisant un algorithme Monte Carlo 4D de transport de particules qui permet d'effectuer de l'accumulation de dose dans une géométrie déformable. Un environnement de simulation a été développé afin de modéliser ces deux modalités pour comparer les distributions de doses standard et 4D. Les déformations dans le patient sont obtenues en utilisant un algorithme de recalage déformable d'image (DIR) entre les différentes phases respiratoire générées par le scan CT 4D. Ceci permet de conserver une correspondance de voxels à voxels entre la géométrie de référence et celles déformées. La DIR est calculée en utilisant la suite ANTs («Advanced Normalization Tools») et est basée sur des difféomorphismes. Une version modifiée de DOSXYZnrc de la suite EGSnrc, defDOSXYZnrc, est utilisée pour le transport de particule en 4D. Les résultats sont comparés à une planification standard afin de valider le modèle actuel qui constitue une approximation par rapport à une vraie accumulation de dose en 4D.
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Aim - To evaluate the deviations in prostatectomy patients treated with IMRT in order to calculate appropriate margins to create the PTV. Background - Defining inappropriate margins can lead to underdosing in target volumes and also overdosing in healthy tissues, increasing morbidity. Material and methods - 223 CBCT images used for alignment with the CT planning scan based on bony anatomy were analyzed in 12 patients treated with IMRT following prostatectomy. Shifts of CBCT images were recorded in three directions to calculate the required margin to create PTV. Results and discussion - The mean and standard deviation (SD) values in millimetres were −0.05 ± 1.35 in the LR direction, −0.03 ± 0.65 in the SI direction and −0.02 ± 2.05 the AP direction. The systematic error measured in the LR, SI and AP direction were 1.35 mm, 0.65 mm, and 2.05 mm with a random error of 2.07 mm; 1.45 mm and 3.16 mm, resulting in a PTV margin of 4.82 mm; 2.64 mm, and 7.33 mm, respectively. Conclusion - With IGRT we suggest a margin of 5 mm, 3 mm and 8 mm in the LR, SI and AP direction, respectively, to PTV1 and PTV2. Therefore, this study supports an anisotropic margin expansion to the PTV being the largest expansion in the AP direction and lower in SI.
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Le cancer pulmonaire est la principale cause de décès parmi tous les cancers au Canada. Le pronostic est généralement faible, de l'ordre de 15% de taux de survie après 5 ans. Les déplacements internes des structures anatomiques apportent une incertitude sur la précision des traitements en radio-oncologie, ce qui diminue leur efficacité. Dans cette optique, certaines techniques comme la radio-chirurgie et la radiothérapie par modulation de l'intensité (IMRT) visent à améliorer les résultats cliniques en ciblant davantage la tumeur. Ceci permet d'augmenter la dose reçue par les tissus cancéreux et de réduire celle administrée aux tissus sains avoisinants. Ce projet vise à mieux évaluer la dose réelle reçue pendant un traitement considérant une anatomie en mouvement. Pour ce faire, des plans de CyberKnife et d'IMRT sont recalculés en utilisant un algorithme Monte Carlo 4D de transport de particules qui permet d'effectuer de l'accumulation de dose dans une géométrie déformable. Un environnement de simulation a été développé afin de modéliser ces deux modalités pour comparer les distributions de doses standard et 4D. Les déformations dans le patient sont obtenues en utilisant un algorithme de recalage déformable d'image (DIR) entre les différentes phases respiratoire générées par le scan CT 4D. Ceci permet de conserver une correspondance de voxels à voxels entre la géométrie de référence et celles déformées. La DIR est calculée en utilisant la suite ANTs («Advanced Normalization Tools») et est basée sur des difféomorphismes. Une version modifiée de DOSXYZnrc de la suite EGSnrc, defDOSXYZnrc, est utilisée pour le transport de particule en 4D. Les résultats sont comparés à une planification standard afin de valider le modèle actuel qui constitue une approximation par rapport à une vraie accumulation de dose en 4D.
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Nowadays the idea of injecting world or domain-specific structured knowledge into pre-trained language models (PLMs) is becoming an increasingly popular approach for solving problems such as biases, hallucinations, huge architectural sizes, and explainability lack—critical for real-world natural language processing applications in sensitive fields like bioinformatics. One recent work that has garnered much attention in Neuro-symbolic AI is QA-GNN, an end-to-end model for multiple-choice open-domain question answering (MCOQA) tasks via interpretable text-graph reasoning. Unlike previous publications, QA-GNN mutually informs PLMs and graph neural networks (GNNs) on top of relevant facts retrieved from knowledge graphs (KGs). However, taking a more holistic view, existing PLM+KG contributions mainly consider commonsense benchmarks and ignore or shallowly analyze performances on biomedical datasets. This thesis start from a propose of a deep investigation of QA-GNN for biomedicine, comparing existing or brand-new PLMs, KGs, edge-aware GNNs, preprocessing techniques, and initialization strategies. By combining the insights emerged in DISI's research, we introduce Bio-QA-GNN that include a KG. Working with this part has led to an improvement in state-of-the-art of MCOQA model on biomedical/clinical text, largely outperforming the original one (+3.63\% accuracy on MedQA). Our findings also contribute to a better understanding of the explanation degree allowed by joint text-graph reasoning architectures and their effectiveness on different medical subjects and reasoning types. Codes, models, datasets, and demos to reproduce the results are freely available at: \url{https://github.com/disi-unibo-nlp/bio-qagnn}.
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Dois experimentos foram conduzidos para determinar a composição química, os valores de energia e os coeficientes de digestibilidade dos aminoácidos, do farelo de arroz integral (FAI) e da quirera de arroz (QA). No primeiro estudo, foram utilizadas 144 aves, com 21 dias de idade, machos, linhagem Cobb, que tiveram suas excretas totalmente coletadas para determinação da energia metabolizável aparente (EMA) e energia metabolizável aparente corrigida (EMAn). O delineamento experimental foi inteiramente casualizado, com três tratamentos e seis repetições, com oito aves cada. No segundo experimento, foi utilizado o método de alimentação forçada para a determinação dos coeficientes de digestibilidade dos aminoácidos. O delineamento foi inteiramente casualizado, com dois alimentos e um jejum e seis repetições com um galo cada. Os valores de MS, PB, EE, FB, EMA e EMAn foram, respectivamente, para FAI: 88,6%; 11,8%; 15,3%; 10,2%; 2968kcal kg-1 e 2804kcal kg-1 e para QA: 93,5%; 9,1%; 0,73%; 0,45%; 3338kcal kg-1 e 3239kcal kg-1. Os valores médios encontrados dos coeficientes de digestibilidade de aminoácidos essenciais e não essenciais foram, respectivamente, de 75,9% e 73,9%, para FAI, e 77,9% e 76,5%, para QA. Embora tenham apresentado níveis inferiores de energia, FAI e a QA podem ser utilizados nas rações de aves em substituição ao milho, uma vez que tiveram níveis maiores de proteína bruta e aminoácidos digestíveis.
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Purpose: To compare the sparing potential of cerebral hemispheres with intensity-modulated radiotherapy (IMRT) and three-dimensional conformal radiotherapy (3D-CRT) for whole-ventricular irradiation (WVI) and conventional whole-brain irradiation (WBI) in the management of localized central nervous system germ cell tumors (CNSGCTs). Methods and Materials: Ten cases of patients with localized CNSGCTs and submitted to WVI by use of IMRT with or without a ""boost"" to the primary lesion were selected. For comparison purposes, similar treatment plans were produced by use of 3D-CRT (WVI with or without boost) and WBI (opposed lateral fields with or without boost), and cerebral hemisphere sparing was evaluated at dose levels ranging from 2 Gy to 40 Gy. Results: The median prescription dose for WVI was 30.6 Gy (range, 25.2-37.5 Gy), and that for the boost was 16.5 Gy (range, 0-23.4 Gy). Mean irradiated cerebral hemisphere volumes were lower for WVI with IMRT than for 3D-CRT and were lower for WVI with 3D-CRT than for WBI. Intensity-modulated radiotherapy was associated with the lowest irradiated volumes, with reductions of 7.5%, 12.2%, and 9.0% at dose levels., compared with 3D-CRT. Intensity-modulated radiotherapy provided of 20, 30, and 40 Gy, respectively statistically significant reductions of median irradiated volumes at all dose levels (p = 0.002 or less). However, estimated radiation doses to peripheral areas of the body were 1.9 times higher with IMRT than with 3D-CRT. Conclusions: Although IMRT is associated with increased radiation doses to peripheral areas of the body, its use can spare a significant amount of normal central nervous system tissue compared with 3D-CRT or WBI in the setting of CNSGCT treatment. (C) 2010 Elsevier Inc.
Gestão da qualidade na tradução: implementação de processos de controlo e avaliação dos Projectos de
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Orientação: Manuel F. Moreira da Silva
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Introdução: Este trabalho tem como principal objectivo comparar os efeitos secundários agudos da Radioterapia por Intensidade Modulada (IMRT) e a Radioterapia Tridimensional Conformada (3 D-CRT) no carcinoma de Próstata; Materiais e métodos: Foram observados os processos clínicos de 30 doentes e analisados os efeitos colaterais da RT ocorridos no decurso do tratamento. Resultados: A percentagem de toxicidade aguda dermatológica foi superior no grupo tratado com 3D-CRT. Nenhum doente apresentou toxicidade aguda grave. Conclusões: O tamanho reduzido da amostra e a ausência de valores estatisticamente significativos, não permite concluir a influência da técnica de RT no desenvolvimento de efeitos secundários agudos.