The markerless lung target tracking AAPM Grand Challenge (MATCH) results

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DOI

  • Marco Mueller, University of Sydney
  • ,
  • Per Poulsen
  • Rune Hansen
  • ,
  • Wilko Verbakel, University of Amsterdam
  • ,
  • Ross Berbeco, Dana-Farber Cancer Institute
  • ,
  • Dianne Ferguson, Dana-Farber Cancer Institute
  • ,
  • Shinichiro Mori, National Institute of Radiological Sciences
  • ,
  • Lei Ren, Duke University
  • ,
  • John C. Roeske, Loyola University Chicago
  • ,
  • Lei Wang, Stanford University
  • ,
  • Pengpeng Zhang, Memorial Sloan-Kettering Cancer Center
  • ,
  • Paul Keall, University of Sydney

Purpose: Lung stereotactic ablative body radiotherapy (SABR) is a radiation therapy success story with level 1 evidence demonstrating its efficacy. To provide real-time respiratory motion management for lung SABR, several commercial and preclinical markerless lung target tracking (MLTT) approaches have been developed. However, these approaches have yet to be benchmarked using a common measurement methodology. This knowledge gap motivated the MArkerless lung target Tracking CHallenge (MATCH). The aim was to localize lung targets accurately and precisely in a retrospective in silico study and a prospective experimental study. Methods: MATCH was an American Association of Physicists in Medicine sponsored Grand Challenge. Common materials for the in silico and experimental studies were the experiment setup including an anthropomorphic thorax phantom with two targets within the lungs, and a lung SABR planning protocol. The phantom was moved rigidly with patient-measured lung target motion traces, which also acted as ground truth motion. In the retrospective in silico study a volumetric modulated arc therapy treatment was simulated and a dataset consisting of treatment planning data and intra-treatment kilovoltage (kV) and megavoltage (MV) images for four blinded lung motion traces was provided to the participants. The participants used their MLTT approach to localize the moving target based on the dataset. In the experimental study, the participants received the phantom experiment setup and five patient-measured lung motion traces. The participants used their MLTT approach to localize the moving target during an experimental SABR phantom treatment. The challenge was open to any participant, and participants could complete either one or both parts of the challenge. For both the in silico and experimental studies the MLTT results were analyzed and ranked using the prospectively defined metric of the percentage of the tracked target position being within 2 mm of the ground truth. Results: A total of 30 institutions registered and 15 result submissions were received, four for the in silico study and 11 for the experimental study. The participating MLTT approaches were: Accuray CyberKnife (2), Accuray Radixact (2), BrainLab Vero, C-RAD, and preclinical MLTT (5) on a conventional linear accelerator (Varian TrueBeam). For the in silico study the percentage of the 3D tracking error within 2 mm ranged from 50% to 92%. For the experimental study, the percentage of the 3D tracking error within 2 mm ranged from 39% to 96%. Conclusions: A common methodology for measuring the accuracy of MLTT approaches has been developed and used to benchmark preclinical and commercial approaches retrospectively and prospectively. Several MLTT approaches were able to track the target with sub-millimeter accuracy and precision. The study outcome paves the way for broader clinical implementation of MLTT. MATCH is live, with datasets and analysis software being available online at https://www.aapm.org/GrandChallenge/MATCH/ to support future research.

OriginalsprogEngelsk
TidsskriftMedical Physics
Vol/bind49
Nummer2
Sider (fra-til)1161-1180
Antal sider20
ISSN0094-2405
DOI
StatusUdgivet - feb. 2022

Bibliografisk note

Funding Information:
The MATCH organizing committee adhered to the AAPM Working Group on Grand Challenges (WGGC) policy ( https://www.aapm.org/GrandChallenge/documents/ChallengeOrganizerGuidance.pdf ). To adhere to this policy and maintain the integrity of the challenge and confidence in the results a governance statement was developed (see the Appendix). Specific author conflicts of interest are: Paul Keall is an inventor on patent application PCT/AU2016/000086 that is related to markerless tumor tracking. This patent and associated intellectual property were assigned by the University of Sydney to ASTO CT. Ross Berbeco has been supported by a research grant from Varian Medical Systems. John Roeske has received speaker's honoraria from Varian Medical Systems outside the scope of this work. Wilko Verbakel received research funding and speakers honoraria/travel expenses from Varian Medical Systems outside the current research. All other authors report no conflict.

Funding Information:
We would like to thank the AAPM for their support of the MATCH. We acknowledge Scandidos for supporting the experimental study with HexaMotion platforms. We thank Nichole Maughan, Parag Parikh, and Lakshmi Santanam from Washington University for providing the patient‐measured lung target motion traces, and Calypso/Varian for funding the lung target motion traces data collection. We thank Esben Worm from Aarhus University Hospital for treatment planning for the in silico study, and Toon Roggen from Varian Medical Systems for the file conversion of the in silico dataset. We further acknowledge the 3D InnovationLab of Amsterdam UMC and Oceanz for their support of the phantom manufacturing. The MATCH organizers want to thank the participants Lee Goddard and Kyoungkeun Jeong from the Montefiore Medical Centre, Alanah Bergman and Marie‐Laure Camborde from the BC Cancer Centre, Irene Redaelli and Anna Martinotti from the Centro Diagnostico Italiano, Guangpei Chen from the Medical College of Wisconsin, Cynthia Chuang and Dante Capaldi from Stanford University, Sharareh Fakhraei and Parham Alaei from the University of Minnesota, Adam Briggs and Jeremy Booth from the Royal North Shore Hospital Sydney, Vanessa Panettieri from the Alfred Hospital Melbourne, and Toon Roggen and Stefan Scheib from Varian iLab. Marco Mueller acknowledges funding support from the Cancer Institute NSW Translational Program Grant scheme. Paul Keall acknowledges funding support from the Australian Government NHMRC Senior Principal Research Fellowship and Investigator Grant schemes. John Roeske was supported by the National Cancer Institute of the National Institutes of Health under award number R01‐CA207483. Ross Berbeco acknowledges funding support from the National Cancer Institute of the National Institutes of Health under award number R01‐CA188446.

Funding Information:
We would like to thank the AAPM for their support of the MATCH. We acknowledge Scandidos for supporting the experimental study with HexaMotion platforms. We thank Nichole Maughan, Parag Parikh, and Lakshmi Santanam from Washington University for providing the patient-measured lung target motion traces, and Calypso/Varian for funding the lung target motion traces data collection. We thank Esben Worm from Aarhus University Hospital for treatment planning for the in silico study, and Toon Roggen from Varian Medical Systems for the file conversion of the in silico dataset. We further acknowledge the 3D InnovationLab of Amsterdam UMC and Oceanz for their support of the phantom manufacturing. The MATCH organizers want to thank the participants Lee Goddard and Kyoungkeun Jeong from the Montefiore Medical Centre, Alanah Bergman and Marie-Laure Camborde from the BC Cancer Centre, Irene Redaelli and Anna Martinotti from the Centro Diagnostico Italiano, Guangpei Chen from the Medical College of Wisconsin, Cynthia Chuang and Dante Capaldi from Stanford University, Sharareh Fakhraei and Parham Alaei from the University of Minnesota, Adam Briggs and Jeremy Booth from the Royal North Shore Hospital Sydney, Vanessa Panettieri from the Alfred Hospital Melbourne, and Toon Roggen and Stefan Scheib from Varian iLab. Marco Mueller acknowledges funding support from the Cancer Institute NSW Translational Program Grant scheme. Paul Keall acknowledges funding support from the Australian Government NHMRC Senior Principal Research Fellowship and Investigator Grant schemes. John Roeske was supported by the National Cancer Institute of the National Institutes of Health under award number R01-CA207483. Ross Berbeco acknowledges funding support from the National Cancer Institute of the National Institutes of Health under award number R01-CA188446.

Publisher Copyright:
© 2021 American Association of Physicists in Medicine.

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