Evidence map›Paper›PMID 37431706›Full record

ArticleJournal of applied clinical medical physics2023

Comparison of dynamic tumor tracking error measurement methods for robotic radiosurgery.

Kohei Okawa

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Mathematical Modeling Support for Lung Cancer Therapy-A Short Review.International journal of molecular sciences · 2023
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4 · The record

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5 · Who and what money

Authors and funding

1 author.

Kohei OkawaFaculty of Health Sciences, Butsuryo College of Osaka, Sakai, Osaka, Japan.ORCID https://orcid.org/0000-0002-2805-0427

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDynamic tumor motion tracking is used in robotic radiosurgery for targets subject to respiratory motion, such as lung and liver cancers. Different methods of measuring tracking error have been reported, but the differences among these methods have not been studied, and the optimal method is unknown. PURPOSE: The purpose of this study was to assess and compare tracking errors encountered with individual patients using different evaluation methods for method optimization.

methodsWe compared the beam's eye view (BEV), machine learning (ML), log (addition error: AE), and log (root sum square: RSS) methods. Log (AE) and log (RSS) were calculated from log files. These tracking errors were compared, and the optimal evaluation method was ascertained. A t-test was performed to evaluate statistically significant differences. Here, the significance level was set at 5%.

resultsThe mean values of BEV, log (AE), log (RSS), and ML were 2.87, 3.91, 2.91, and 3.74 mm, respectively. The log (AE) and ML were higher than BEV (p < 0.001), and log (RSS) was equivalent to the BEV, suggesting that the log (RSS) calculated with the log file method can substitute for the BEV calculated with the BEV method. As RSS error calculation is simpler than BEV calculation, using it may improve clinical practice throughput.

conclusionThis study clarified differences among three tracking error evaluation methods for dynamic tumor tracking radiotherapy using a robotic radiosurgery system. The log (RSS) calculated by the log file method was found to be the best alternative to BEV method, as it can calculate tracking errors more easily than the BEV method.

Indexed as

Lung NeoplasmsRadiosurgeryRobotic Surgical ProceduresHumansLungMotionRadiotherapy Planning, Computer-AssistedCyberKnifedynamic tumor trackingtracking error

Identifiers

PMID37431706
PMCPMC10402666

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