Document Type

Conference Proceeding

Publication Date

Spring 2022

Publication Title

International Journal of Particle Therapy

Abstract

Purpose: To address the challenges of generating a deliverable and efficient spot-scanning proton arc (SPArc) plan for a proton therapy system. We developed a novel SPArc optimization algorithm (SPArcDMSP) by directly incorporating machinespecific parameters such as mechanical constraints and delivery sequence. Method and Material: A SPArc delivery sequence model (DSMarc) was built based on the machine-specific parameters of the prototype arc delivery system IBA ProteusONEt. The SPArcDMSP resamples and adjusts each control point’s delivery speed based on the DSMarc calculation through the iterative approach (Fig1). Users could set the expected delivery time and gantry max acceleration as a mechanical constraint during the optimization. Four cases (brain, liver, head neck, liver, and lung cancer) were selected to test SPArcDMSP. Two kinds of SPArc plans were generated using the same planning objective functions:(1) SPArcDMSP plan meeting the maximum allowable gantry acceleration speed(0.6deg/s2);(2) SPArcDMSP-userspeed plan with a user pre-defined delivery time and acceleration speed , 0.1deg/s^2. Arc delivery sequence such as gantry speed, delivery time was simulated based on the DSMarc and was compared. Results: With a similar objective value, number of energy layers, and spots, both SPArcDMSP and SPArcDMSP-userspeed plans could be delivered continuously within the 61 degree tolerance window.The SPArcDMSP-user-speed plan could minimize the gantry momentum change based on users’ preference (Fig 2). Conclusions: For the first time, the clinical users could generate a SPArc plan by directly optimize the arc treatment speed and momentum changes of the gantry. This work paved the roadmap for the clinical implementation of proton arc therapy in the treatment planning system.

Volume

8

Issue

4

First Page

98

Comments

Particle Therapy Co-Operative Group North America (PTCOG-NA) 7th Annual Conference, Virtual, September 18-20, 2021.

DOI

10.14338/IJPT-22-PTCOG-NA-8.4

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