Evidence map›Paper›PMID 34913495›Full record

ArticleMedical physics2022

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

Marco Mueller, Per Poulsen, Rune Hansen, Wilko Verbakel, Ross Berbeco, Dianne Ferguson, Shinichiro Mori, Lei Ren, John C Roeske, Lei Wang and 2 more

Open access · bronzeAbstract read
In one paragraph

Article in Medical physics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
5.8field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 31 citations in OpenAlex.

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  13. Digital twins for chronic lung diseases.European respiratory review : an official journal of the European Respiratory Society · 2024
    Review
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  17. Biomedical advances and future prospects of high-precision three-dimensional radiotherapy and four-dimensional radiotherapy.Proceedings of the Japan Academy. Series B, Physical and biological sciences · 2023
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 8 institutions in 4 countries.

Marco MuellerACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia.
Per PoulsenDanish Center for Particle Therapy and Department of Oncology, Aarhus University Hospital, Aarhus, Denmark.
Rune HansenDepartment of Medical Physics, Aarhus University Hospital, Aarhus, Denmark.
Wilko VerbakelAmsterdam University Medical Centers, Location VUmc, Amsterdam, Netherlands.
Ross BerbecoDepartment of Radiation Oncology, Brigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA.
Dianne FergusonDepartment of Radiation Oncology, Brigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA.
Shinichiro MoriResearch Center for Charged Particle Therapy, National Institute of Radiological Sciences, Chiba, Japan.
Lei RenDepartment of Radiation Oncology, Duke University Medical Center, Durham, North Carolina, USA.
John C RoeskeDepartment of Radiation Oncology, Loyola University Medical Center, Maywood, Illinois, USA.
Lei WangDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, California, USA.
Pengpeng ZhangDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Paul KeallACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia.
Aarhus University Hospital · DKHarvard University · USSydney Institute of Marine Science · AUAmsterdam University Medical Centers · NLDuke Medical Center · USLoyola University Medical Center · USMemorial Sloan Kettering Cancer Center · USStanford University · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
A novel flat-panel detector for advanced on-board radiation therapy imagingR01CA188446 · NCI · DANA-FARBER CANCER INST · PI BERBECO, ROSS I., FUEGLISTALLER, RONY · 2014 to 2024
$7.2M
Markerless Motion Tracking of Lung Tumors Using Dual Energy ImagingR01CA207483 · NCI · LOYOLA UNIVERSITY CHICAGO · PI LEHMANN, MATHIAS, ROESKE, JOHN · 2017 to 2025
$2.2M
Australian Government NHMRC Senior Principal Research Fellowship and Investigator GrantCalypso/VarianCancer Institute NSW Translational Program GrantNational Cancer Institute of the National Institutes of Health R01-CA207483NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA188446NCI NIH HHS R01 CA207483
6 · The paper itself

Abstract

purposeLung 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.

methodsMATCH 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.

resultsA 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%.

conclusionsA 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.

Indexed as

Lung NeoplasmsRadiotherapy, Intensity-ModulatedHumansLungPhantoms, ImagingProspective StudiesRadiotherapy Planning, Computer-AssistedRetrospective StudiesThoraxadaptive radiotherapylung SABRpersonalized treatmenttumor motiontumor tracking

Identifiers

PMID34913495
PMCPMC8828678
OpenAlexW4200222522

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.