First experimental evaluation of multi-target multileaf collimator tracking during volumetric modulated arc therapy for locally advanced prostate cancer.


Journal

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
ISSN: 1879-0887
Titre abrégé: Radiother Oncol
Pays: Ireland
ID NLM: 8407192

Informations de publication

Date de publication:
07 2021
Historique:
received: 03 02 2021
revised: 27 04 2021
accepted: 02 05 2021
pubmed: 11 5 2021
medline: 28 7 2021
entrez: 10 5 2021
Statut: ppublish

Résumé

Locally advanced and oligometastatic cancer patients require radiotherapy treatment to multiple independently moving targets. There is no existing commercial solution that can simultaneously track and treat multiple targets. This study experimentally implemented and evaluated a real-time multi-target tracking system for locally advanced prostate cancer. Real-time multi-target MLC tracking was integrated with 3D x-ray image guidance on a standard linac. Three locally advanced prostate cancer treatment plans were delivered to a static lymph node phantom and dynamic prostate phantom that reproduced three prostate trajectories. Treatments were delivered using multi-target MLC tracking, single-target MLC tracking, and no tracking. Doses were measured using Gafchromic film placed in the dynamic and static phantoms. Dosimetric error was quantified by the 2%/2 mm gamma failure rate. Geometric error was evaluated as the misalignment between target and aperture positions. The multi-target tracking system latency was measured. The mean (range) gamma failure rates for the prostate and lymph nodes, were 18.6% (5.2%, 28.5%) and 7.5% (1.1%, 13.7%) with multi-target tracking, 7.9% (0.7%, 15.4%) and 37.8% (18.0%, 57.9%) with single-target tracking, and 38.1% (0.6%, 75.3%) and 37.2% (29%, 45.3%) without tracking. Multi-target tracking had the lowest geometric error with means and standard deviations within 0.2 ± 1.5 for the prostate and 0.0 ± 0.3 mm for the lymph nodes. The latency was 730 ± 20 ms. This study presented the first experimental implementation of multi-target tracking to independently track prostate and lymph node displacement during VMAT. Multi-target tracking reduced dosimetric and geometric errors compared to single-target tracking and no tracking.

Identifiants

pubmed: 33971194
pii: S0167-8140(21)06223-X
doi: 10.1016/j.radonc.2021.05.001
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

212-220

Informations de copyright

Copyright © 2021 Elsevier B.V. All rights reserved.

Auteurs

Emily A Hewson (EA)

ACRF Image X Institute, University of Sydney School of Health Sciences, Sydney, Australia. Electronic address: emily.hewson@sydney.edu.au.

Andrew Dipuglia (A)

Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, Australia.

John Kipritidis (J)

Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, Australia.

Yuanyuan Ge (Y)

Nelune Comprehensive Cancer Centre, Prince of Wales Hospital, Sydney, Australia.

Ricky O'Brien (R)

ACRF Image X Institute, University of Sydney School of Health Sciences, Sydney, Australia.

Stephanie Roderick (S)

Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, Australia.

Linda Bell (L)

Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, Australia.

Per R Poulsen (PR)

Department of Oncology and Danish Center for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark.

Thomas Eade (T)

Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, Australia.

Jeremy T Booth (JT)

Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, Australia; School of Physics, University of Sydney, Australia.

Paul J Keall (PJ)

ACRF Image X Institute, University of Sydney School of Health Sciences, Sydney, Australia.

Doan T Nguyen (DT)

ACRF Image X Institute, University of Sydney School of Health Sciences, Sydney, Australia; Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, Australia; School of Biomedical Engineering, University of Technology Sydney, Australia.

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Classifications MeSH