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dc.contributor.authorBedford, JLen_US
dc.contributor.authorTsang, HSen_US
dc.contributor.authorNill, Sen_US
dc.contributor.authorOelfke, Uen_US
dc.identifier.citationMedical physics, 2019, 46 (12), pp. 5421 - 5433
dc.description.abstractPurpose The use of dynamic arcs for delivery of stereotactic body radiation therapy (SBRT) on Cyberknife is investigated, with a view to improving treatment times. This study investigates the required modeling of robot and multileaf collimator (MLC) motion between control points in the trajectory and then uses this to develop an optimization method for treatment planning of a dynamic arc with Cyberknife. The resulting plans are compared in terms of dose-volume histograms and estimated treatment times with those produced by a conventional beam arrangement. Methods Five SBRT patient cases (prostate A - conventional, prostate B - brachytherapy-type, lung, liver, and partial left breast) were retrospectively studied. A suitable arc trajectory with control points spaced at 5° was proposed and treatment plans were produced for typical clinical protocols. The optimization consisted of a fluence optimization, segmentation, and direct aperture optimization using a gradient descent method. Dose delivered by the moving MLC was either taken to be the dose delivered discretely at the control points or modeled using effective fluence delivered between control points. The accuracy of calculated dose was assessed by recalculating after optimization using five interpolated beams and 100 interpolated apertures between each optimization control point. The resulting plans were compared using dose-volume histograms and estimated treatment times with those for a conventional Cyberknife beam arrangement. Results If optimization is performed based on discrete doses delivered at the arc control points, large differences of up to 40% of the prescribed dose are seen when recalculating with interpolation. When the effective fluence between control points is taken into account during optimization, dosimetric differences are <2% for most structures when the plans are recalculated using intermediate nodes, but there are differences of up to 15% peripherally. Treatment plan quality is comparable between the arc trajectory and conventional body path. All plans meet the relevant clinical goals, with the exception of specific structures which overlap with the planning target volume. Median estimated treatment time is 355 s (range 235-672 s) for arc delivery and 675 s (range 554-1025 s) for conventional delivery. Conclusions The method of using effective fluence to model MLC motion between control points is sufficiently accurate to provide for accurate inverse planning of dynamic arcs with Cyberknife. The proposed arcing method produces treatment plans with comparable quality to the body path, with reduced estimated treatment delivery time.
dc.format.extent5421 - 5433
dc.subjectRadiotherapy Dosage
dc.subjectRadiotherapy Planning, Computer-Assisted
dc.subjectModels, Biological
dc.titleTreatment planning optimization with beam motion modeling for dynamic arc delivery of SBRT using Cyberknife with multileaf collimation.
dc.typeJournal Article
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfMedical physics
pubs.notesNot known
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Radiotherapy Physics Modelling
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Radiotherapy treatment planning
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Radiotherapy treatment planning/Radiotherapy treatment planning (hon.)
pubs.organisational-group/ICR/Primary Group/Royal Marsden Clinical Units
pubs.embargo.termsNot known
icr.researchteamRadiotherapy Physics Modellingen_US
icr.researchteamRadiotherapy treatment planningen_US
dc.contributor.icrauthorBedford, James Len
dc.contributor.icrauthorOelfke, Uween
dc.contributor.icrauthorNill, Simeonen

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