9 research outputs found

    Study of preoperative radiotherapy for sarcomas of the extremities with intensity-modulation, image-guidance and small safety-margins (PREMISS).

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    Background The aim of the trial is to demonstrate that with the use of modern IMRT/IGRT and reduction of safety margins postoperative wound complications can be reduced. Methods/ Design The trial is designed as a prospective, monocentric clinical phase II trial. The treatment is performed with helical IMRT on the Tomotherapy HiArt System© or with RapidArc© IMRT as available. All treatments are performed with 6 MV photons and daily online CT-based IGRT. A dose of 50 Gy in 2 Gy single fractions (5 fractions per week) is prescribed. Restaging including MRI of the primary tumor site as well as CT of the thorax/abdomen is planned 4 weeks after RT. PET-examinations or any other imaging can be performed as required clinically. In cases of R1 resection, brachytherapy is anticipated in the 2nd postoperative week. Brachytherapy catheters are implanted into the tumor bed depending on the size and location of the lesion. Surgery is planned 5–6 weeks after completion of neoadjuvant RT. All patients are seen for a first follow-up visit 2 weeks after wound healing is completed, thereafter every 3 months during the first 2 years. The endpoints of the study are evaluated in detail during the first (2 weeks) and second (3 months) follow-up. Functional outcome and QOL are documented prior to treatment and at year 1 and 2. Treatment response and efficacy will be scored according to the RECIST 1.1 criteria. A total patient number of 50 with an expected 20 % rate of wound complications were calculated for the study, which translates into a 95 % confidence interval of 10.0-33.7 % for wound complication rate in a binomial distribution. Discussion The present study protocol prospectively evaluates the use of IMRT/IGRT for neoadjuvant RT in patients with soft tissue sarcomas of the extremity with the primary endpoint wound complications, which is the major concern with this treatment sequence. Besides complications rates, local control rates and survival rates, as well as QOL, functional outcome and treatment response parameters (imaging and pathology) are part of the protocol. The data of the present PREMISS study will enhance the current literature and support the hypothesis that neoadjuvant RT with IMRT/IGRT offers an excellent risk-benefit ratio in this patient population. Trial registration NCT01552239 &nbsp

    Using stochastic dynamic programming to determine optimal fire management for Banksia ornata

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    1. A model of the population dynamics of Banksia ornata was developed, using stochastic dynamic programming (a state-dependent decision-making tool), to determine optimal fire management strategies that incorporate trade-offs between biodiversity conservation and fuel reduction. 2. The modelled population of B. ornata was described by its age and density, and was exposed to the risk of unplanned fires and stochastic variation in germination success. 3. For a given population in each year, three management strategies were considered: (i) lighting a prescribed fire; (ii) controlling the incidence of unplanned fire; (iii) doing nothing. 4. The optimal management strategy depended on the state of the B. ornata population, with the time since the last fire (age of the population) being the most important variable. Lighting a prescribed fire at an age of less than 30 years was only optimal when the density of seedlings after a fire was low (< 100 plants ha(-1)) or when there were benefits of maintaining a low fuel load by using more frequent fire. 5. Because the cost of management was assumed to be negligible (relative to the value of the persistence of the population), the do-nothing option was never the optimal strategy, although lighting prescribed fires had only marginal benefits when the mean interval between unplanned fires was less than 20-30 years

    Quantum optics with quantum dots

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    Area Policy and Area Strategies: The Origins and Lessons of the British Experience

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