L’hypoxie tumorale est l’une des principales causes de l’agressivité des glioblastomes (GB). Plusieurs études attestent de l’implication de l’isoforme HIF-1α (hypoxia inducible factor-1α) dans la progression de ces tumeurs et dans leur résistance à la radiothérapie (RT). Plus récemment, il a été établi que l’isoforme HIF-2α régule la capacité tumorigénique des cellules souches de GB (CSG). Cependant, le rôle de ce facteur dans la croissance des cellules de GB différenciées et leur réponse à la RT est moins documenté. Dans ce contexte, l’objectif de ce travail a été de renforcer ces connaissances à l’échelle préclinique en utilisant deux approches d’ARN interférence (ARNi) pour moduler l’expression de HIF-2 : cibler directement HIF-2α ou cibler HAF (hypoxia associated factor), un facteur impliqué dans le switch de HIF-1α vers HIF-2α. Les résultats obtenus sur un modèle orthotopique de cellules humaines de GB (U251-MG) différenciées montrent que l’invalidation de HAF conduit à un fort ralentissement de la croissance de ces tumeurs mais indépendamment de HIF-1α ou HIF-2α. L’effet de l’invalidation de HIF-2α serait, quant à lui, dépendant de l’environnement tumoral. En effet, la diminution d’expression de HIF-2α dans les cellules U251 ne modifie pas la croissance tumorale dans un modèle de greffe sous-cutanée, alors que celle-ci favorise la croissance tumorale lorsque les cellules de GB sont implantées en intracérébral. Par comparaison aux tumeurs contrôles, ces tumeurs sont plus invasives et mieux perfusées. In vitro, l’inhibition de l’expression de HIF-2α n’a aucun effet sur la survie des cellules U251 alors qu’elle diminue la mort apoptotique de ces cellules exposées aux rayons X.L’ensemble des données présentées dans cette étude suggère que HAF et HIF-2α pourraient réguler la capacité tumorigénique des cellules de GB différenciées, tout comme observé pour les CSG. En outre, ces résultats soulignent la nécessité de prendre en compte le microenvironnement cellulaire afin de mieux comprendre le comportement de la tumeur dans son environnement hypoxique. / Hypoxia is one of the main causes of glioblastoma (GB) aggressiveness. Various studies attest on the involvement of the HIF-1α isoform (hypoxia inducible factor-1α) in the progression of these tumors and in their resistance to radiation therapy (RT). More recently, it was established that the HIF-2α isoform regulates the tumorigenic capacity of GB stem cells (GSC). However, the role of this factor in the growth of differentiated GB cells and their response to RT is less documented. In this context, the goal of this work was to strengthen this knowledge at the preclinical level by using two RNA interference (RNAi) strategies to modulate the expression of HIF-2: one directly targets HIF-2α, the other one targets HAF (hypoxia associated factor), a factor involved in the switch of HIF-1α to HIF-2α. Our results obtained on an orthotopic model of differentiated human GB (U251-MG) cells showed that the invalidation of HAF leads to a strong slowdown in tumor growth but independently of HIF-1α or HIF-2α. On the other hand, the effect of HIF-2α silencing seems dependent on the tumor environment. Indeed, the extinction ofHIF-2α expression in U251 cells does not modify tumor growth in a subcutaneous model, whereas it promotes tumor growth when GB cells are intracerebrally grafted. Compared to control tumors, these tumors are more invasive and highly perfused. In vitro, the inhibition of HIF-2α expression has no effect on GB cell survival whereas decreasing the X-rays induced apoptotic death.Collectively, these data suggest that HAF and HIF-2α could regulate the tumorigenic capacity of differentiated GB cells, like it does in CSGs. In addition, these results highlight the need to take into account the cellular microenvironment to better understand the behavior of the tumor in its hypoxic environment.

Proton therapy with pencil beam scanning technique is a novel technique to treat cancer patients due to its unique biophysical properties. However, a small error in dose calculation may lead towards undesired greater uncertainties in planed doses. This project aims to create a simulation model of Varian ProBeam Compact using the GEANT4 Monte Carlo simulation tool kit. Experimental data from the first clinical ProBeam Compact system at South Florida Proton Therapy Institute was used to validate the simulation model. A comparison was made between the experimental and simulated Integrated Depth-Dose curves using a 2%/2mm gamma index test with 100% of points passing. The beam spot standard deviation sizes (s!) were compared using percent deviation. All simulated s! matched the experimental s! within 2.5%, except 70 and 80 MeV. The model can be used to develop a more comprehensive model as an independent dose verification tool and further investigate dose distribution. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2020. / FAU Electronic Theses and Dissertations Collection

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第20974号 / 医博第4320号 / 新制||医||1026(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 増永 慎一郎, 教授 高田 穣, 教授 武田 俊一 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

A research report submitted to the Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, in partial fulfillment of the requirements for the degree of Master of Medicine in Diagnostic Radiology Johannesburg 2019 / Introduction: Neonates in a neonatal ICU or high care unit are a high-risk population. Besides a vulnerability to medical and surgical conditions, which often require radiological investigation, they are also at risk from the effects of radiation used in imaging. These risks increase with radiation dose. Numerous studies have assessed the dose due to primary radiation, however few have assessed the secondary radiation dose, and none have quantified the dose over time. Aim: To quantify the secondary radiation dose in our neonatal high care unit in order to determine if additional protective measures from secondary radiation are necessary. Method: A prospective analytic study was undertaken using multiple thermoluminescent devices in a cubicle of a neonatal high care unit, and control dosimeters outside the unit. Dosimeters were deployed for a 4 week period. Simultaneously, data was collected on patient numbers, and the X-rays performed in the unit. Results were compared to reference ranges for primary and secondary radiation (2-3 mSv per annum). Results: The average secondary radiation dose was 0.108mGy (p=0.6553) over 4 weeks, less than the expected background radiation dose of 0.17 – 0.25mGy. There was a large number of patients moving through the unit during the study period (89), with an average of 14 patients in the unit at a time, however this did not result a large number of X-ray exposures. Twenty one percent of patients were in the unit for less than a day, and 49 % were admitted for less than 3 days. Sixteen patients (18%) had X-ray investigations, with a total of 21 investigations and 30 exposures. Thirty percent of primary radiation dose was due to repeat exposures. Patients receiving X-rays had an average of 2 X-ray examinations (range: 1 to 4 studies) performed, with an average Entrance Skin Dose of 196.7µSv (0.197mGy) – range 77 to 554µSv (0.077mGy to 0.554mGy). There was no statistically significant difference between weeks or zones (p=0.1060 and p=0.8237 respectively), and differences in primary radiation doses was likely due to chance. Conclusion: Additional measures to protect patients in the unit from secondary radiation are unnecessary. There was a low probability of patients having a radiological investigation in the neonatal high care unit, and secondary radiation doses were not measurably higher than background radiation. / TL (2019)

Background and Objectives We investigate three statistical and methodological issues within the context of non-inferiority randomized controlled trials (RCTs), specifically those of radiotherapy regimens for the prevention of local recurrence in patients with early stage breast cancer who have undergone breast conserving surgery. These issues are: (1) the analysis of multiple time-to-event outcomes in non-inferiority RCTs; (2) the interim analysis of a binary outcome that is repeatedly assessed at pre-specified times; and (3) determining the optimal analysis population for dealing with crossovers in non-inferiority RCTs. Methods Issue 1: We investigated and compared the properties of four statistical models (proportional hazards model, competing risk model, marginal model and frailty model) for analyzing radiotherapy non-inferiority RCTs of patients with early stage breast cancer who are at risk for and may experience multiple failure types. We applied the four methods to data from an existing trial in which subjects with breast cancer could experience local recurrence (the primary outcome), distant recurrence, death, or a combination of these events. In addition, we compared these models using simulated examples of similar non-inferiority trials with varying hazards of each failure type. Issue 2: We investigated and compared the properties of three methods for estimating the event proportions for an interim analysis in RCTs with a binary outcome that is repeatedly assessed at pre-specified times. Generally, interim analyses are performed after half or more of the subjects have completed full follow-up. However, depending on the duration of accrual relative to the length of follow-up, this may be inefficient, since there is a possibility that the trial will have completed accrual prior to the interim analysis. We focussed our simulations on situations where delaying the interim analysis until half or more of subjects have completed full follow-up is an inefficient approach. The methods include: 1) estimation of the event proportion based on subjects who have been followed for a pre-specified time (less than the full follow-up duration) or who experienced the outcome; 2) estimation of the event proportion based on all available data from subjects randomized by the time of the interim analysis; and 3) the Kaplan-Meier approach to estimate the event proportion. We varied the risk of the outcome, the treatment effect and the probability of an event occurring at each pre-specified time. We compared the three methods in terms of overall type I and II errors, as well as the probability of stopping early for benefit. Issue 3: We explored the effect of subject crossover from the experimental to the standard radiotherapy arm prior to treatment initiation on the intention-to-treat, per-protocol, as-treated and combined intention-to-treat and per-protocol analysis in non-inferiority RCTs of radiotherapy for the prevention of local recurrence in patients with early stage breast cancer. We varied the non-inferiority margin, the percent of subjects who cross over and evaluated random and non-random crossover. The main comparison of the methods was done using overall type I error. In addition, we compared the methods based on estimate bias and standard error of the estimate. Results and Conclusions Issue 1: All four models produced similar results for the existing trial (i.e. non-inferiority was observed regardless of the method used). Simulations showed that the event-specific methods yielded contrasting results when the distribution of distant recurrence or death differed between treatment groups. We conclude that multiple models should be used as part of a comprehensive analysis. Issue 2: We showed that conducting an interim analysis when a considerable number of subjects have completed a portion of their full follow-up duration is an efficient approach under certain scenarios where event distribution probabilities are similar between treatment groups. Under these specific scenarios, all three methods preserved the type I and II errors. In these cases, we recommend using the Kaplan-Meier method because it incorporates all the available data and has greater probability of early stopping. Issue 3: The as-treated analysis had the best performance in terms of type I error rate. However, it can be recommended only in scenarios where crossover is random. It performed poorly in scenarios with greater than 2% non-random crossover. The intention-to-treat and per-protocol analysis performed poorly under both random and non-random crossover scenarios. / Thesis / Doctor of Philosophy (PhD)

Cancer is a group of deadly diseases, to which one treatment method is radiotherapy. Recent studies indicate advantages of delivering so-called FLASH treatments using ultra-high dose rates (> 40 Gy/s), with a normal tissue sparing FLASH effect. Delivering a high dose in a short time imposes requirements on both the treatment machine and the treatment plan. To see as much of the FLASH effect as possible, the delivery pattern should be optimized, which is the focus of this thesis. The optimization method was applied to 17 lung plans, and the results show that a local-search-based optimization achieves overall good results, achieving a mean FLASH coverage of 31.7 % outside of the CTV after a mean optimization time of 8.75 s. This is faster than published results using a genetic algorithm.

Clinical studies suggest radiation dose and dose rate cause increased failure of medical implants however, little evidence supports this claim and due to the complexity of an in vivo environment, separating variable implants is difficult. Before beginning to understand material changes in vivo, a systematic study of silicone and polyurethane exposed to radiation is needed to verify whether radiation is a major variable contributing to material changes. This research fills a gap within the current literature by investigating low dose therapeutic radiation and varying dose rates at sterilization dose and answers questions on whether radiation in an aqueous environment alone is enough to significantly alter material properties. This is the first research to apply a water environment to therapeutic doses and the first to investigate a range of dose rates for clinical applications. Biomedical grade silicone and polyurethane films will be exposed to both types of radiation in an aqueous environment separately and analyzed for changes. The limited current literature combined with standards for biomedical devices will be used to characterize changes seen in materials. The first strategy used to explore the compliance of biomedical grade polymers employs low doses of therapeutic radiation ranging between 0 Gy and 80 Gy. Analysis of these low doses results in confirming cellular, mechanical and chemical stability of silicone and polyurethane. The second strategy used to investigate silicone and polyurethane exposed materials to 25 kGy (sterilization dose) of gamma irradiation at varying dose rates (3.2 - 833 Gy/min). Results from these studies conclude that varying the dose rate causes slight changes in both materials but not significant enough to alter bulk material properties. In conclusion, the results from this research reveal that both silicone and polyurethane maintain their stability at low doses and varying dose rates of irradiation while in an aqueous environment. This indicates that increased failure rates seen in silicone and polyurethane materials in vivo when exposed to radiation cannot be contributed to radiation alone. With the highly complex environment medical devices are exposed to in vivo, each variable that may contribute to failure should be investigated individually before combining to fully understand the mechanisms of material failure. This study indicates that the environment may play a larger role in material change and there is a need for updates to medical device standards. / PHD / Clinical studies suggest radiation dose and dose rate cause increased failure of medical implants however, little evidence supports this claim and due to the complexity of a human environment, separating factors contributing to failure is difficult. Before beginning to understand material changes, a study of silicone and polyurethane exposed to radiation is needed to verify whether radiation is a major variable contributing to material changes. The results from this research reveal that both silicone and polyurethane maintain their stability at low doses and varying dose rates of irradiation while in water environment. This indicates that increased failure rates seen in silicone and polyurethane materials in clinical settings when exposed to radiation cannot be contributed to radiation alone. With the highly complex environment medical devices are exposed, each factor that may contribute to failure should be investigated individually before combining to fully understand the mechanisms of material failure. This study indicates that the environment may play a larger role in material change and there is a need for updates to medical device standards.

Yes / Consultant posts were developed to strengthen strategic leadership whilst maintaining front line service responsibilities and clinical expertise. The nursing profession has attempted to develop tools to enable individuals to evaluate their own practice and consider relevant measurable outcomes. This study evaluated the feasibility of transferring such a nursing ‘toolkit’ to another health profession. Method: This evaluation was structured around a one-day workshop where a nurse consultant impact toolkit was appraised and tested within the context of consultant radiographic practice. The adapted toolkit was subsequently validated using a larger sample at a national meeting of consultant radiographers. Results: There was broad agreement that the tools could be adopted for use by radiographers although several themes emerged in relation to perceived gaps within the nursing template, confirming the initial exercise. This resulted in amendments to the original scope and a proposed new evaluation tool. Conclusion: The impact toolkit could help assess individual and collaborat ive role impact at a local and national level. The framework provides consultant radiographers with an opportunity to understand and highlight the contribution their roles have on patients, staff, their organisation and the wider profession.

Thesis (MScIng)--University of Stellenbosch, 2004. / Please refer to full text for abstract.

published_or_final_version / Clinical Oncology / Doctoral / Doctor of Philosophy