Prediction of conical collimator collision for stereotactic radiosurgery

Park, Jeong Hoon; McDermott, Ryan; Kim, Sangroh; Huq, M. Saiful

doi:10.1002/acm2.12963

Cited by 1 publication

(2 citation statements)

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“…Numerous collision detection frameworks using different methodologies have been reported for both photon and proton external beam therapy 17–30 . In general, the treatment head (gantry) and the patient support (table or chair) are modeled with varying degrees of details, that is, from a simple set of connected vertices to actual computer‐aided design files 18,26,27,31 .…”

Section: Introductionmentioning

confidence: 99%

“…Numerous collision detection frameworks using different methodologies have been reported for both photon and proton external beam therapy. 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 In general, the treatment head (gantry) and the patient support (table or chair) are modeled with varying degrees of details, that is, from a simple set of connected vertices to actual computer‐aided design files. 18 , 26 , 27 , 31 The patient has also been represented by a simple geometry like an ellipse 17 or a column, 32 , 33 or skipped for simplicity.…”

Section: Introductionmentioning

confidence: 99%

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A quantitative framework for patient‐specific collision detection in proton therapy

Northway,

Vallejo,

Liu

et al. 2023

J Applied Clin Med Phys

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BackgroundBeam modifying accessories for proton therapy often need to be placed in close proximity of the patient for optimal dosimetry. However, proton treatment units are larger in size and as a result the planned treatment geometry may not be achievable due to collisions with the patient. A framework that can accurately simulate proton treatment geometry is desired.PurposeA quantitative framework was developed to model patient‐specific proton treatment geometry, minimize air gap, and avoid collisions.MethodsThe patient's external contour is converted into the International Electrotechnique Commission (IEC) gantry coordinates following the patient's orientation and each beam's gantry and table angles. All snout components are modeled by three‐dimensional (3D) geometric shapes such as columns, cuboids, and frustums. Beam‐specific parameters such as isocenter coordinates, snout type and extension are used to determine if any point on the external contour protrudes into the various snout components. A 3D graphical user interface is also provided to the planner to visualize the treatment geometry. In case of a collision, the framework's analytic algorithm quantifies the maximum protrusion of the external contour into the snout components. Without a collision, the framework quantifies the minimum distance of the external contour from the snout components and renders a warning if such distance is less than 5 cm.ResultsThree different snout designs are modeled. Examples of potential collision and its aversion by snout retraction are demonstrated. Different patient orientations, including a sitting treatment position, as well as treatment plans with multiple isocenters, are successfully modeled in the framework. Finally, the dosimetric advantage of reduced air gap enabled by this framework is demonstrated by comparing plans with standard and reduced air gaps.ConclusionImplementation of this framework reduces incidence of collisions in the treatment room. In addition, it enables the planners to minimize the air gap and achieve better plan dosimetry.

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Section: Introductionmentioning

confidence: 99%