Automated Monte-Carlo re-calculation of proton therapy plans using Geant4/Gate: implementation and comparison to plan-specific quality assurance measurements.


Journal

The British journal of radiology
ISSN: 1748-880X
Titre abrégé: Br J Radiol
Pays: England
ID NLM: 0373125

Informations de publication

Date de publication:
01 Oct 2020
Historique:
pubmed: 30 7 2020
medline: 7 10 2020
entrez: 30 7 2020
Statut: ppublish

Résumé

Software re-calculation of proton pencil beam scanning plans provides a method of verifying treatment planning system (TPS) dose calculations prior to patient treatment. This study describes the implementation of AutoMC, a Geant4 v10.3.3/Gate v8.1 (Gate-RTion v1.0)-based Monte-Carlo (MC) system for automated plan re-calculation, and presents verification results for 153 patients (730 fields) planned within year one of the proton service at The Christie NHS Foundation Trust. A MC beam model for a Varian ProBeam delivery system with four range-shifter options (none, 2 cm, 3 cm, 5 cm) was derived from beam commissioning data and implemented in AutoMC. MC and TPS (Varian Eclipse v13.7) calculations of 730 fields in solid-water were compared to physical plan-specific quality assurance (PSQA) measurements acquired using a PTW Octavius 1500XDR array and PTW 31021 Semiflex 3D ion chamber. TPS and MC showed good agreement with array measurements, evaluated using γ analyses at 3%, 3 mm with a 10% lower dose threshold:>94% of fields calculated by the TPS and >99% of fields calculated by MC had γ ≤ 1 for>95% of measurement points within the plane. TPS and MC also showed good agreement with chamber measurements of absolute dose, with systematic differences of <1.5% for all range-shifter options. Reliable independent verification of the TPS dose calculation is a valuable complement to physical PSQA and may facilitate reduction of the physical PSQA workload alongside a thorough delivery system quality assurance programme. A Gate/Geant4-based MC system is thoroughly validated against an extensive physical PSQA dataset for 730 clinical fields, showing that clinical implementation of MC for PSQA is feasible.

Identifiants

pubmed: 32726141
doi: 10.1259/bjr.20200228
pmc: PMC7548378
doi:

Types de publication

Journal Article Validation Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

20200228

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Auteurs

Adam H Aitkenhead (AH)

Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK.
Division of Cancer Sciences, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK.

Peter Sitch (P)

Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK.

Jenny C Richardson (JC)

Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK.
Division of Cancer Sciences, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK.

Carla Winterhalter (C)

Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK.
Division of Cancer Sciences, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK.

Imran Patel (I)

Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK.

Ranald I Mackay (RI)

Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK.
Division of Cancer Sciences, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK.

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Classifications MeSH