Fully automated, multi-criterial planning for Volumetric Modulated Arc Therapy – An international multi-center validation for prostate cancer

Heijmen, B.; Voet, P.; Fransen, D.; Penninkhof, J.; Milder, Maaike T. W.; Akhiat, Hafid; Bonomo, Pierluigi; Casati, M.; Georg, Dietmar; Goldner, Gregor; Henry, Ann; Lilley, J.; Lohr, Frank; Marrazzo, L.; Pallotta, S.; Pellegrini, Roberto; Seppenwoolde, Yvette; Simontacchi, Gabriele; Steil, Volker; Stieler, Florian; Wilson, Stuart D.; Breedveld, S.

doi:10.1016/j.radonc.2018.06.023

Cited by 66 publications

(71 citation statements)

References 18 publications

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“…In the plan generation for a patient, the objective functions are sequentially minimized in order of assigned priority while avoiding violations of imposed constraints. Wish-lists are created in iterative tuning procedures that ensure automatic generation of treatment plans maximally complying with the clinical planning aims, including their tradeoffs [12,13]. Initially, the goal of a wish-list creation is mimicking the MANplan quality.…”

Section: Introductionmentioning

confidence: 99%

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First system for fully-automated multi-criterial treatment planning for a high-magnetic field MR-Linac applied to rectal cancer

et al. 2020

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Section: Introductionmentioning

confidence: 99%

“…Initially, the goal of a wish-list creation is mimicking the MANplan quality. Subsequently, the process has an intrinsic drive to beat the MANplan quality [12,13]. Many studies have demonstrated superiority of Erasmus-iCycle AUTOplans over MANplans generated with conventional trial-and-error planning [9,[14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

First system for fully-automated multi-criterial treatment planning for a high-magnetic field MR-Linac applied to rectal cancer

et al. 2020

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“…When comparing to previously published studies, for the tumour site of PSV a thorough summary has recently been presented by Heijmen et al [26]; with 12 studies identified as demonstrating small differences between automated and manual plans [2,10,18,[27][28][29][30][31][32][33][34][35], and only their more recent multi-centre study showing the overall dosimetric superiority of automation through reduced rectum doses [26]. For PPN, to the authors' knowledge two studies have been published.…”

Section: Discussionmentioning

confidence: 98%

Evaluating the application of Pareto navigation guided automated radiotherapy treatment planning to prostate cancer

Wheeler

Chu

Holmes

et al. 2019

Radiotherapy and Oncology

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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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“…Merely applying a machine learning algorithm that will generate the same contour on multiple occasions does not mean that the contours are optimal, particularly for target structures. Similarly, although planning is increasingly automated [8], the optimization process requires insight when using tuning structures and selecting beam angles to ensure the most elegant and creative solution. The issue here is that retaining the necessary human oversight of the creative aspects of contouring and autoplanning could negate the significant time saving that this technology offers in the first place.…”

Section: Creativity In Radiotherapymentioning

confidence: 99%

Artificial Intelligence in Radiotherapy: A Philosophical Perspective

Bridge

Bridge²

2019

Journal of Medical Imaging and Radiation Sciences

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The increasing uptake of machine learning solutions for segmentation and planning leaves no doubt that artificial intelligence (AI) will soon be providing input into a range of radiotherapy procedures. Although this promises to deliver increased speed and accuracy, the future role of AI in relation to radiotherapy should be thought through carefully. There is currently a gap between published developments and widespread adoption, which provides some space to prepare the workforce and to consider the implications on practice. It is rare to find philosophical input into a medical journal, but the advent of AI makes this perspective increasingly important. Philosophical insight can help explore the potential impact of AI, in particular, on human creativity and oversight. Without this perspective, we run the risk of focusing solely on the immediate logistical impact on patients and departments. This commentary identifies three key aspects of radiotherapy that the authors feel would suffer most under AI control: creativity, innovation, and patient safety, which all demand uniquely human attributes. The article also provides insight from a philosophical perspective with regard to human consciousness, ethics, and empathy. Philosophically we should, perhaps, retain ethical concerns about the widening role of AI in radiotherapy beyond simple quantitative interpretation and image processing. As developments continue, we have time to determine how our roles will evolve and to establish a framework for ensuring appropriate human input into patient care. Most importantly, we must start to embed a philosophical approach to adoption of AI technology from the outset if we are to prepare ourselves for the challenge that lies ahead.

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Fully automated, multi-criterial planning for Volumetric Modulated Arc Therapy – An international multi-center validation for prostate cancer

Cited by 66 publications

References 18 publications

First system for fully-automated multi-criterial treatment planning for a high-magnetic field MR-Linac applied to rectal cancer

First system for fully-automated multi-criterial treatment planning for a high-magnetic field MR-Linac applied to rectal cancer

Evaluating the application of Pareto navigation guided automated radiotherapy treatment planning to prostate cancer

Artificial Intelligence in Radiotherapy: A Philosophical Perspective

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