Introduction et objectif : La prescription des traitements en radiothérapie est basée sur l'analyse de la répartition de dose calculée par le TPS. Un changement d'algorithme de calcul doit être précédé d'une analyse dosimétrique complète, afin que les impacts cliniques soient maitrisés. Nous présentons une méthodologie de mise en œuvre d'un nouveau TPS. Matériel et méthodologie : Nous avons utilisé 5 algorithmes de calcul de dose. Nous avons comparé 6 plans de traitement avec des configurations identiques : patient, énergie, balistique. Nous avons comparé 12 localisations tumorales : 5 poumons, 1 œsophage, 1 sein, 3 ORL, 1 encéphales et 1 prostate. Le principe de méthodologie est basé sur deux critères d'analyse : 1.Critère d'analyse dosimétrique : nous avons classé les outils d'analyse en 3 catégories : analyse liée à la dose de traitement, analyse liée à la distribution de dose et analyse liée à la répartition de la dose 2.Critère d'analyse statistique : nous avons considéré que nous avons 5 séries de mesure liée à 5 algorithmes. Nous avons considéré les valeurs dosimétriques calculées par l'ancien algorithme comme valeurs de référence. Le test de comparaison statistique utilisé était un Wilcoxon pour série apparié avec un seuil de signification de 5% et un intervalle de confiance à 95%. Résultats et discussion : Nous avons trouvé des écarts pour tous les paramètres comparés dans cette étude. Ces écarts dépendent de la localisation de la tumeur et de l'algorithme de calcul. La maîtrise statistique des résultats nous permet, d'une part de diagnostiquer et interpréter les écarts dosimétriques observés et d'autre part, de déterminer si les écarts sont significatifs. Conclusion : Nous proposons une méthodologie qui permet de quantifier d'éventuels écarts dosimétriques lors d'un changement d'algorithme. L'analyse statistique permet de s'assurer que les résultats sont significatifs. / Background and purpose The validation of a treatment plan is based on the analysis of dose distributions. The dose distributions are calculated by algorithms implanted in TPS. So, the changing of an algorithm must be preceded by a complete dosimetric analysis in order to provide a method for controlling the clinical impact of this change. We present in this study the methodology used for implementing a new TPS in our clinic. Materials and methods We used five algorithms for dose calculation: Clarkson, PBC, Batho Power Law, modified Batho and EqTAR. We compared six treatment plans with identical configurations: 2 plans without heterogeneity correction and 4 with density correction. We have compared nine tumours locations: 5 lungs, 1 oesophagus, 1 breast, 3head and neck, 1 brain and 1 prostate. We compared the following parameters: monitors units, HDV, isodoses, covering index, index of homogeneity, conformity index, geometric index and gamma index for 2D and 3D. We analyzed the results using a statistical evaluation and the method plot box. Results and discussion The gamma index 3D and histogram gamma generated for a CT slice can be used to compare various algorithms and radiotherapy plans. We found a difference in all parameters compared when the algorithm is changed. For example, we found a 5% difference in monitors units and 7% in dose for the pulmonary cancer case, when we change from PBC to EqTAR .This may leads to an increased of 30% in the complication rate. The statistical evaluation serves as a rapid interpretation and diagnostic of dosimetric differences and allows the determination of the significance of these differences. Conclusion We proposed a methodology that allows the quantification of dosimetric variation during the change of calculation algorithm in radiotherapy. This methodology provides a valuable technique for quantitative comparison of various algorithms and radiotherapy plans

Utilizing a Criminal Event Perspective, the analyses of this dissertation test a variety of relationships to the dependent variable: the Criminal Lethality Index. Data from the National Incident-Based Reporting System, the Census and American Community Survey, the American Trauma Society, and data derived from the Census’s mapping TIGER files are combined to create a database of 190 cities. This database is used to test road network connectivity (Gama Index), medical resources, criminal covariates and Social Disorganization variables in relation to a city’s Criminal Lethality Index. OLS regression demonstrates a significant and negative relationship between a city’s Gama Index and its Criminal Lethality Index. In addition, percent male, percent black, median income and percent of the population employed in diagnosing and treating medical professions were all consistently positively related to Criminal Lethality. The percent of males 16 to 24, percent of single parent households, and Concentrated Disadvantage Index were all consistently and negatively related to Criminal Lethality. Given these surprising results, additional diagnostic regressions are run using more traditional dependent variables such as the number of murders in a city and the proportion of aggravated assaults with major injuries per 100,000 population. These reveal the idiosyncratic nature of utilizing the Criminal Lethality Index. This dependent variable has proven useful in some circumstances and counterintuitive in others. The source of the seemingly unintuitive results is the fact that certain factors only reduce murders but many factors impact both murder and aggravated assaults, thereby creating difficultly when trying to predict patterns in Criminal Lethality

Em radioterapia, o espectro de energia é o componente mais importante dos feixes de elétrons. Espectros de energia de elétrons são relevântes para o cálculo acurado da dose, aplicações do sistema de planejamento e simulações realistas. Reconstrução inversa consiste na derivação do espectro de energia de elétrons a partir de curvas de porcentagem de dose em profundidade utilizando um apropiado modelo matemático. Reconstrução inversa é considerada a melhor dentre muitas abordagens porque: i) não requer nenhum equipamento suplementar ou do conhecimento detalhado da geometria e composição do cabeçote do acelerador; ii) equipamentos para a medição de curvas de porcentagem de dose em profundidade estão disponíveis em qualquer clínica e iii) é computacionalmente rápida. Neste trabalho, usou-se o método de reconstrução inversa baseado na sinergia recozimento simulado generalizado-regularização de Tikhonov. A validação da reconstrução foi realizada através do índice gama sob critérios clínicos de aceitação restritivos. Resultados mostraram que os espectros de energia reconstruídos reproduzem com precisão a porcentagem de dose em profundidade clínica bem como valores de dose fora do eixo central. Assim, concluí-se que o método empregado é ecaz para reconstruir espectros de energia que representam efetivamente espectros de energia do acelerador que atingem na supercie do fantoma. Consequentemente, sob certos limites, eles poderiam auxiliar em simulações realistas do tratamento. / In radiotherapy, energy spectrum is the most critical component of any electron beam. Knowledge of energy spectrum is important for accurate dose calculation, treatment planning applications and realistic simulations. Inverse reconstruction derives energy spectrum from the measured percentage depth dose using an appropriate mathematical model. There are several advantages to using inverse reconstruction: i) it does not require any supplementary equipment or detailed knowledge of the geometry head and composition; ii) the equipment for measurement of the percentage depth dose is standard and already available in any clinic and iii) it is computationally fast. In this work, we used the inverse reconstruction method based on the synergy simulated annealing generalized-Tikhonov regularization. Validation of inverse reconstruction was done by comparing the measured and reconstructed percentage depth dose via the gamma index. Results show the reconstructed electron energy spectra accurately reproduce the clinical dose percentage as well as o-axis dose values. Therefore, it was concluded that the method employed is eective to reconstruct energy spectra that eectively represent accelerator energy spectra reaching the phantom surface. Consequently, under certain limits, they could aid in realistic simulations of treatment.

Em radioterapia, o espectro de energia é o componente mais importante dos feixes de elétrons. Espectros de energia de elétrons são relevântes para o cálculo acurado da dose, aplicações do sistema de planejamento e simulações realistas. Reconstrução inversa consiste na derivação do espectro de energia de elétrons a partir de curvas de porcentagem de dose em profundidade utilizando um apropiado modelo matemático. Reconstrução inversa é considerada a melhor dentre muitas abordagens porque: i) não requer nenhum equipamento suplementar ou do conhecimento detalhado da geometria e composição do cabeçote do acelerador; ii) equipamentos para a medição de curvas de porcentagem de dose em profundidade estão disponíveis em qualquer clínica e iii) é computacionalmente rápida. Neste trabalho, usou-se o método de reconstrução inversa baseado na sinergia recozimento simulado generalizado-regularização de Tikhonov. A validação da reconstrução foi realizada através do índice gama sob critérios clínicos de aceitação restritivos. Resultados mostraram que os espectros de energia reconstruídos reproduzem com precisão a porcentagem de dose em profundidade clínica bem como valores de dose fora do eixo central. Assim, concluí-se que o método empregado é ecaz para reconstruir espectros de energia que representam efetivamente espectros de energia do acelerador que atingem na supercie do fantoma. Consequentemente, sob certos limites, eles poderiam auxiliar em simulações realistas do tratamento. / In radiotherapy, energy spectrum is the most critical component of any electron beam. Knowledge of energy spectrum is important for accurate dose calculation, treatment planning applications and realistic simulations. Inverse reconstruction derives energy spectrum from the measured percentage depth dose using an appropriate mathematical model. There are several advantages to using inverse reconstruction: i) it does not require any supplementary equipment or detailed knowledge of the geometry head and composition; ii) the equipment for measurement of the percentage depth dose is standard and already available in any clinic and iii) it is computationally fast. In this work, we used the inverse reconstruction method based on the synergy simulated annealing generalized-Tikhonov regularization. Validation of inverse reconstruction was done by comparing the measured and reconstructed percentage depth dose via the gamma index. Results show the reconstructed electron energy spectra accurately reproduce the clinical dose percentage as well as o-axis dose values. Therefore, it was concluded that the method employed is eective to reconstruct energy spectra that eectively represent accelerator energy spectra reaching the phantom surface. Consequently, under certain limits, they could aid in realistic simulations of treatment.