Background and purpose: Current automated radiotherapy planning solutions do not allow for the intuitive exploration of different treatment options during protocol calibration. This work introduces an automated planning solution, which aims to address this problem through incorporating Pareto navigation techniques into the calibration process. Materials and methods: For each tumour site a set of planning goals is defined. Utilising Pareto navigation techniques an operator calibrates the solution through intuitively exploring different treatment options: selecting the optimum balancing of competing planning goals for the given site. Once calibrated, fully automated plan generation is possible, with specific algorithms implemented to ensure trade-off balancing of new patients is consistent with that during calibration. Using the proposed methodology the system was calibrated for prostate and seminal vesicle treatments. The resultant solution was validated through quantitatively comparing the dose distribution of automatically generated plans (VMAT Auto) against the previous clinical plan, for ten randomly selected patients. Results: VMAT Auto yielded statistically significant improvements in: PTV conformity indices, high dose bladder metrics, mean bowel dose, and the majority of rectum dose metrics. Of particular note was the reduction in mean rectum dose (median 25.1 Gy vs. 27.5 Gy), rectum V 24.3Gy (median 41.1% vs. 46.4%), and improvement in the conformity index for the primary PTV (median 0.86 vs. 0.79). Dosimetric improvements were not at the cost of other dose metrics. Conclusions: An automated planning methodology with a Pareto navigation based calibration has been developed, which enables the complex balancing of competing trade-offs to be intuitively incorporated into automated protocols.

a b s t r a c tBackground and purpose: Current automated planning methods do not allow for the intuitive exploration of clinical trade-offs during calibration. Recently a novel automated planning solution, which is calibrated using Pareto navigation principles, has been developed to address this issue. The purpose of this work was to clinically validate the solution for prostate cancer patients with and without elective nodal irradiation. Materials and methods: For 40 randomly selected patients (20 prostate and seminal vesicles (PSV) and 20 prostate and pelvic nodes (PPN)) automatically generated volumetric modulated arc therapy plans (VMAT Auto ) were compared against plans created by expert dosimetrists under clinical conditions (VMAT Clinical ) and no time pressures (VMAT Ideal ). Plans were compared through quantitative comparison of dosimetric parameters and blind review by an oncologist. Results: Upon blind review 39/40 and 33/40 VMAT Auto plans were considered preferable or equal to VMAT Clinical and VMAT Ideal respectively, with all deemed clinically acceptable. Dosimetrically, VMAT Auto , VMAT Clinical and VMAT Ideal were similar, with observed differences generally of low clinical significance. Compared to VMAT Clinical , VMAT Auto reduced hands-on planning time by 94% and 79% for PSV and PPN respectively. Total planning time was significantly reduced from 22.2 mins to 14.0 mins for PSV, with no significant reduction observed for PPN. Conclusions: A novel automated planning solution has been evaluated, whose Pareto navigation based calibration enabled clinical decision-making on trade-off balancing to be intuitively incorporated into automated protocols. It was successfully applied to two sites of differing complexity and robustly generated high quality plans in an efficient manner. Ó 2019 The Authors. Published by Elsevier B.V. Radiotherapy and Oncology 141 (2019) 220-226 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) treatment plan generation is a complex process, traditionally performed manually by medical physicists or specialist dosimetrists. Manual methods can be time consuming and dependent on the treatment planner's experience [1]. A solution to this problem is automated planning, where high quality plans are generated autonomously with minimal operator interaction [2][3][4][5][6][7][8][9].A key challenge in automated planning is incorporating treatment planners' or oncologists' clinical experience and decisionmaking within the autonomous process. A number of different methods have been employed: knowledge based planning (KBP) utilises databases of previous clinical plans to correlate the relationship between patient geometry and the resultant dose distribution, which then informs the optimisation of new patients [3,[10][11][12][13]; sequential e-constraint planning (ec) optimises plans based on a list of clinically prioritised goals [2,7,8,[14][15...

Current energy demands and future energy needs are a growing industry which at present attracts a large amount of research and investment of which nuclear energy is an integral part. Eight new nuclear stations are proposed to be developed in the UK over the next ten years to meet this demand. In order for nuclear energy to sustain growth and development, nuclear decommissioning of first and second generation power stations needs to be addressed in the U.K. and worldwide. Presently the UK has 36 graphite moderated reactors as a result of the UK military and civil programs, which over the next twenty years will close. This will result in ∼99’000 tonnes of irradiated graphite waste for which no current national decommissioning strategy exists. The main issues associated with this waste are the large volume and activation products associated. By far the greatest inventory is from 3H and 14C. An EU Euroatom FP7 Program; CARBOWASTE was established in 2008 with the aim of developing treatment and disposal options for graphite.This research is based within CARBOWASTE, the main objectives are to understand the mechanisms involved in the production, location and removal of radioisotopes from nuclear graphite. Computed X-ray Tomography (CT) will be used in order to quantify the initial porosity in conjunction with thermal treatment (ex situ) in order to eventually identify the location of 14C within the matrix of irradiated graphite, through the preferential chemically controlled oxidation of graphite. Unirradiated Pile Grade A graphite samples have been laser and manually marked in order align the samples prior to and post thermal treatment to determine the degree of porosity changes and weight loss under a range of thermal oxidation parameters.