Highlights
- •Comprehensive automation of intra-cranial proton treatment planning system.
- •Automatic beams’ geometry selection based on intra-cranial target localization.
- •Beams’ geometry derived from previous planning experience and heterogeneity index.
- •Wish list approach is employed to a benchmark dose distribution for plan optimization.
- •Feasibility of the system in terms of time to generate clinical plans within OARs clinical constrains.
Abstract
Purpose
To evaluate the feasibility of comprehensive automation of an intra-cranial proton
treatment planning.
Materials and methods
Class solution (CS) beam configuration selection allows the user to identify predefined
beam configuration based on target localization; automatic CS (aCS) will then explore
all the possible CS beam geometries. Ten patients, already used for the evaluation
of the automatic selection of the beam configuration, have been also employed to training
an algorithm based on the computation of a benchmark dose exploit automatic general
planning solution (GPS) optimization with a wish list approach for the planning optimization.
An independent cohort of ten patients has been then used for the evaluation step between
the clinical and the GPS plan in terms of dosimetric quality of plans and the time
needed to generate a plan.
Results
The definition of a beam configuration requires on average 22 min (range 9–29 min).
The average time for GPS plan generation is 18 min (range 7–26 min). Median dose differences
(GPS-Manual) for each OAR constraints are: brainstem −1.60 Gy, left cochlea −1.22 Gy,
right cochlea −1.42 Gy, left eye 0.55 Gy, right eye −2.33 Gy, optic chiasm −1.87 Gy,
left optic nerve −4.45 Gy, right optic nerve −2.48 Gy and optic tract −0.31 Gy. Dosimetric
CS and aCS plan evaluation shows a slightly worsening of the OARs values except for
the optic tract and optic chiasm for both CS and aCS, where better results have been
observed.
Conclusion
This study has shown the feasibility and implementation of the automatic planning
system for intracranial tumors. The method developed in this work is ready to be implemented
in a clinical workflow.
Keywords
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Article info
Publication history
Published online: December 17, 2022
Accepted:
November 25,
2022
Received in revised form:
November 4,
2022
Received:
April 26,
2022
Identification
Copyright
© 2022 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights reserved.
