I-131 SPECT/CT is a useful tool to characterize atypical or CF on WBS by differentiating thyroid remnant or cancer from physiologic activity or nonthyroid pathology. In the past, uptake on a WBS that was not explicable as physiologic activity was identified as putative or possible thyroid cancer and generally was treated with I-131. Now, by identifying activity in some possible cancer sites as not thyroid cancer, SPECT/CT can reduce inappropriate treatment with I-131. SPECT/CT of WBS performed after ablative doses of 131-I is useful in determining the nature of CF and therefore likely providing prognostic information.

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...

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