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First direct machine-specific parameters incorporated in Spot-scanning Proton Arc (SPArc) optimization algorithm.

Gang Liu1,2,3, Qingkun Fan4, Lewei Zhao5

  • 1Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Medical Physics
|February 10, 2024
PubMed
Summary
This summary is machine-generated.

A new Spot-scanning Proton Arc (SPArc) optimization algorithm (SPArcDMPO) improves treatment efficiency by directly incorporating machine constraints. This novel method reduces delivery time and gantry momentum changes, facilitating clinical implementation of proton arc therapy.

Keywords:
machine parameteroptimizationproton arc

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Medical Imaging and Imaging-Guided Therapy

Background:

  • Spot-scanning Proton Arc (SPArc) therapy offers superior plan quality but faces challenges in deliverability and efficiency.
  • Current research focuses on optimizing SPArc for practical clinical application.

Purpose of the Study:

  • To develop a novel SPArc optimization algorithm (SPArcDMPO) that directly integrates machine-specific parameters for improved deliverability and efficiency.
  • To address challenges in generating efficient SPArc plans for proton therapy systems with massive gantries.

Main Methods:

  • A SPArc delivery sequence model (DSMarc) was created using machine parameters from the IBA ProteusONE® system.
  • The SPArcDMPO algorithm iteratively adjusts control point delivery speeds based on DSMarc, allowing users to pre-define arc delivery time.
  • Ten patient cases were used to compare SPArcDMPO plans against original SPArc plans, analyzing delivery time, time differentials, and gantry velocity variations.

Main Results:

  • SPArcDMPO plans achieved similar plan quality to original SPArc plans while significantly reducing the time differential between dynamic arc delivery and static irradiation (30.55% to 14.67%).
  • Total variations in gantry velocity during dynamic arc delivery were substantially mitigated with SPArcDMPO (14.73 to 4.28 degree/s).
  • The algorithm effectively minimized gantry momentum changes, easing mechanical demands on the proton gantry.

Conclusions:

  • The SPArcDMPO algorithm enables clinical users to generate SPArc plans that meet mechanical constraints and allow direct control over arc treatment speed and gantry momentum.
  • This advancement facilitates the routine clinical implementation of proton arc therapy within treatment planning systems.