Collision prediction for intracranial stereotactic radiosurgery planning: An easy-to-implement analytical solution

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

BACKGROUND

Beam 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.

PURPOSE

A quantitative framework was developed to model patient-specific proton treatment geometry, minimize air gap, and avoid collisions.

METHODS

The 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.

RESULTS

Three 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.

CONCLUSION

Implementation 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.

Design of a 3D patient-specific collision avoidance virtual framework for half-gantry proton therapy system

Introduction

This study presents a comprehensive collision avoidance framework based on three‐dimension (3D) computer‐aided design (CAD) modeling, a graphical user interface (GUI) as peripheral to the radiation treatment planning (RTP) environment, and patient‐specific plan parameters for intensity‐modulated proton therapy (IMPT).

Methods

A stand‐alone software application was developed leveraging the Varian scripting application programming interface (API) for RTP database object accessibility. The Collision Avoider software models the Hitachi ProBeat‐V half gantry design and the Kuka robotic couch with triangle mesh structures. Patient‐specific plan parameters are displayed in the collision avoidance software for potential proximity evaluation. The external surfaces of the patients and the immobilization devices are contoured based on computed tomography (CT) images. A “table junction‐to‐CT‐origin” (JCT) measurement is made for every patient at the time of CT simulation to accurately provide reference location of the patient contours to the treatment couch. Collision evaluations were performed virtually with the program during treatment planning to prevent four major types of collisional events: collisions between the gantry head and the treatment couch, gantry head and the patient's body, gantry head and the robotic arm, and collisions between the gantry head and the immobilization devices.

Results

The Collision Avoider software was able to accurately model the proton treatment delivery system and the robotic couch position. Commonly employed clinical beam configuration and JCT values were investigated. Brain and head and neck patients require more complex gantry and patient positioning system configurations. Physical measurements were performed to validate 3D CAD model geometry. Twelve clinical proton treatment plans were used to validate the accuracy of the software. The software can predict all four types of collisional events in our clinic since its full implementation in 2020.

Conclusion

A highly efficient patient‐specific collision prevention program for scanning proton therapy has been successfully implemented. The graphical program has provided accurate collision detection since its inception at our institution.