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  • 1
    In: Radiation Oncology, Springer Science and Business Media LLC, Vol. 15, No. 1 ( 2020-12)
    Abstract: This work aims at clinically validating a graphical tool developed for treatment plan assessment, named SPIDERplan, by comparing the plan choices based on its scoring with the radiation oncologists (RO) clinical preferences. Methods SPIDERplan validation was performed for nasopharynx pathology in two steps. In the first step, three ROs from three Portuguese radiotherapy departments were asked to blindly evaluate and rank the dose distributions of twenty pairs of treatment plans. For plan ranking, the best plan from each pair was selected. For plan evaluation, the qualitative classification of ‘Good’, ‘Admissible with minor deviations’ and ‘Not Admissible’ were assigned to each plan. In the second step, SPIDERplan was applied to the same twenty patient cases. The tool was configured for two sets of structures groups: the local clinical set and the groups of structures suggested in international guidelines for nasopharynx cancer. Group weights, quantifying the importance of each group and incorporated in SPIDERplan, were defined according to RO clinical preferences and determined automatically by applying a mixed linear programming model for implicit elicitation of preferences. Intra- and inter-rater ROs plan selection and evaluation were assessed using Brennan-Prediger kappa coefficient. Results Two-thirds of the plans were qualitatively evaluated by the ROs as ‘Good’. Concerning intra- and inter-rater variabilities of plan selection, fair agreements were obtained for most of the ROs. For plan evaluation, substantial agreements were verified in most cases. The choice of the best plan made by SPIDERplan was identical for all sets of groups and, in most cases, agreed with RO plan selection. Differences between RO choice and SPIDERplan analysis only occurred in cases for which the score differences between the plans was very low. A score difference threshold of 0.005 was defined as the value below which two plans are considered of equivalent quality. Conclusion Generally, SPIDERplan response successfully reproduced the ROs plan selection. SPIDERplan assessment performance can represent clinical preferences based either on manual or automatic group weight assignment. For nasopharynx cases, SPIDERplan was robust in terms of the definitions of structure groups, being able to support different configurations without losing accuracy.
    Type of Medium: Online Resource
    ISSN: 1748-717X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
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  • 2
    Online Resource
    Online Resource
    Elsevier BV ; 2014
    In:  Physica Medica Vol. 30 ( 2014), p. e21-
    In: Physica Medica, Elsevier BV, Vol. 30 ( 2014), p. e21-
    Type of Medium: Online Resource
    ISSN: 1120-1797
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2014
    detail.hit.zdb_id: 1122650-X
    detail.hit.zdb_id: 2110535-2
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  • 3
    Online Resource
    Online Resource
    Wiley ; 2016
    In:  Medical Physics Vol. 43, No. 3 ( 2016-03), p. 1083-1095
    In: Medical Physics, Wiley, Vol. 43, No. 3 ( 2016-03), p. 1083-1095
    Abstract: The planning of an intensity modulated radiation therapy treatment requires the optimization of the fluence intensities. The fluence map optimization (FMO) is many times based on a nonlinear continuous programming problem, being necessary for the planner to define a priori weights and/or lower bounds that are iteratively changed within a trial‐and‐error procedure until an acceptable plan is reached. In this work, the authors describe an alternative approach for FMO that releases the human planner from trial‐and‐error procedures, contributing for the automation of the planning process. Methods: The FMO is represented by a voxel‐based convex penalty continuous nonlinear model. This model makes use of both weights and lower/upper bounds to guide the optimization process toward interesting solutions that are able to satisfy all the constraints defined for the treatment. All the model's parameters are iteratively changed by resorting to a fuzzy inference system. This system analyzes how far the current solution is from a desirable solution, changing in a completely automated way both weights and lower/upper bounds. The fuzzy inference system is based on fuzzy reasoning that enables the use of common‐sense rules within an iterative optimization process. The method is built in two stages: in a first stage, an admissible solution is calculated, trying to guarantee that all the treatment planning constraints are being satisfied. In this first stage, the algorithm tries to improve as much as possible the irradiation of the planning target volumes. In a second stage, the algorithm tries to improve organ sparing, without jeopardizing tumor coverage. Results: The proposed methodology was applied to ten head‐and‐neck cancer cases already treated in the Portuguese Oncology Institute of Coimbra (IPOCFG) and signalized as complex cases. IMRT treatment was considered, with 7, 9, and 11 equidistant beam angles. It was possible to obtain admissible solutions for all the patients considered and with no human planner intervention. The results obtained were compared with the optimized solution using a similar optimization model but with human planner intervention. For the vast majority of cases, it was possible to improve organ sparing and at the same time to assure better tumor coverage. Conclusions: Embedding a fuzzy inference system into FMO allows human planner reasoning to be used in the guidance of the optimization process toward interesting regions in a truly automated way. The proposed methodology is capable of calculating high quality plans within reasonable computational times and can be an important contribution toward fully automated radiation therapy treatment planning.
    Type of Medium: Online Resource
    ISSN: 0094-2405 , 2473-4209
    Language: English
    Publisher: Wiley
    Publication Date: 2016
    detail.hit.zdb_id: 1466421-5
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  • 4
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2014
    In:  Central European Journal of Operations Research Vol. 22, No. 3 ( 2014-9), p. 431-455
    In: Central European Journal of Operations Research, Springer Science and Business Media LLC, Vol. 22, No. 3 ( 2014-9), p. 431-455
    Type of Medium: Online Resource
    ISSN: 1435-246X , 1613-9178
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2014
    detail.hit.zdb_id: 1178875-6
    detail.hit.zdb_id: 2093829-9
    SSG: 3,2
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  • 5
    Online Resource
    Online Resource
    Elsevier BV ; 2022
    In:  European Journal of Operational Research Vol. 302, No. 1 ( 2022-10), p. 270-279
    In: European Journal of Operational Research, Elsevier BV, Vol. 302, No. 1 ( 2022-10), p. 270-279
    Type of Medium: Online Resource
    ISSN: 0377-2217
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 1501061-2
    detail.hit.zdb_id: 243003-4
    SSG: 3,2
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  • 6
    In: Medical Physics, Wiley, Vol. 43, No. 10 ( 2016-10), p. 5514-5526
    Abstract: The inverse planning of an intensity‐modulated radiation therapy (IMRT) treatment requires decisions regarding the angles used for radiation incidence, even when arcs are used. The possibility of improving the quality of treatment plans by an optimized selection of the beam angle incidences—beam angle optimization (BAO)—is seldom done in clinical practice. The inclusion of noncoplanar beam incidences in an automated optimization routine is even more unusual. However, for some tumor sites, the advantage of considering noncoplanar beam incidences is well known. This paper presents the benefits of using a derivative‐free multistart framework for the optimization of the noncoplanar BAO problem. Methods Multistart methods combine a global strategy for sampling the search space with a local strategy for improving the sampled solutions. The proposed global strategy allows a thorough exploration of the continuous search space of the highly nonconvex BAO problem. To avoid local entrapment, a derivative‐free method is used as local procedure. Additional advantages of the derivative‐free method include the reduced number of function evaluations required to converge and the ability to use multithreaded computing. Twenty nasopharyngeal clinical cases were selected to test the proposed multistart framework. The planning target volumes included the primary tumor, the high and low risk lymph nodes. Organs‐at‐risk included the spinal cord, brainstem, optical nerves, chiasm, parotids, oral cavity, brain, thyroid, among others. For each case, a setup with seven equispaced beams was chosen and the resulting treatment plan, using a multicriteria optimization framework, was then compared against the coplanar and noncoplanar plans using the optimal beam setups obtained by the derivative‐free multistart framework. Results The optimal noncoplanar beam setup obtained by the derivative‐free multistart framework leads to high quality treatment plans with better target coverage and with improved organ sparing compared to treatment plans using equispaced or optimal coplanar beam angle setups. The noncoplanar treatment plans achieved, e.g., an average reduction in the mean dose of the oral cavity of 6.1 Gy and an average reduction in the maximum‐dose of the brainstem of 7 Gy when compared to the equispaced treatment plans. Conclusions The noncoplanar BAO problem is an extremely challenging multimodal optimization problem that can be successfully addressed through a thoughtful exploration of the continuous highly nonconvex BAO search space. The proposed framework is capable of calculating high quality treatment plans and thus can be an interesting alternative toward automated noncoplanar beam selection in IMRT treatment planning which is nowadays the natural trend in treatment planning.
    Type of Medium: Online Resource
    ISSN: 0094-2405 , 2473-4209
    Language: English
    Publisher: Wiley
    Publication Date: 2016
    detail.hit.zdb_id: 1466421-5
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  • 7
    In: Physica Medica, Elsevier BV, Vol. 64 ( 2019-08), p. 210-221
    Type of Medium: Online Resource
    ISSN: 1120-1797
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2019
    detail.hit.zdb_id: 1122650-X
    detail.hit.zdb_id: 2110535-2
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  • 8
    Online Resource
    Online Resource
    Wiley ; 2019
    In:  International Transactions in Operational Research Vol. 26, No. 3 ( 2019-05), p. 908-928
    In: International Transactions in Operational Research, Wiley, Vol. 26, No. 3 ( 2019-05), p. 908-928
    Abstract: Intensity‐modulated radiation therapy (IMRT) is a modern radiotherapy modality that uses a multileaf collimator to enable the irradiation of the patient with nonuniform maps of radiation from a set of distinct beam irradiation directions. The aim of IMRT is to eradicate all cancerous cells by irradiating the tumor with a prescribed dose while simultaneously sparing, as much as possible, the neighboring tissues and organs. The optimal choice of beam irradiation directions—beam angle optimization (BAO)—can play an important role in IMRT treatment planning by improving organ sparing and tumor coverage, increasing the treatment plan quality. Typically, the BAO search is guided by the optimal value of the fluence map optimization (FMO)—the problem of obtaining the most appropriate radiation intensities for each beam direction. In this paper, a new score to guide the BAO search is introduced and embedded in a parallel multistart derivative‐free optimization framework that is detailed for the extremely challenging continuous BAO problem. For the set of 10 clinical nasopharyngeal tumor cases considered, treatment plans obtained for optimized beam directions clearly outperform the benchmark treatment plans obtained considering equidistant beam directions typically used in clinical practice. Furthermore, treatment plans obtained considering the proposed score clearly improve the quality of the plans resulting from the use of the optimal value of the FMO problem to guide the BAO search.
    Type of Medium: Online Resource
    ISSN: 0969-6016 , 1475-3995
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 2019815-2
    SSG: 3,2
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  • 9
    Online Resource
    Online Resource
    Elsevier BV ; 2015
    In:  Physica Medica Vol. 31, No. 7 ( 2015-11), p. 747-756
    In: Physica Medica, Elsevier BV, Vol. 31, No. 7 ( 2015-11), p. 747-756
    Type of Medium: Online Resource
    ISSN: 1120-1797
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2015
    detail.hit.zdb_id: 1122650-X
    detail.hit.zdb_id: 2110535-2
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  • 10
    In: Reports of Practical Oncology and Radiotherapy, VM Media Group sp. z o.o
    Type of Medium: Online Resource
    ISSN: 2083-4640 , 1507-1367
    Language: Unknown
    Publisher: VM Media Group sp. z o.o
    Publication Date: 2021
    detail.hit.zdb_id: 2494467-1
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