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Optimization of training periods for the estimation model of three-dimensional target positions using an external respiratory surrogate

Overview of attention for article published in Radiation Oncology, April 2018
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Title
Optimization of training periods for the estimation model of three-dimensional target positions using an external respiratory surrogate
Published in
Radiation Oncology, April 2018
DOI 10.1186/s13014-018-1019-9
Pubmed ID
Authors

Hiraku Iramina, Mitsuhiro Nakamura, Yusuke Iizuka, Takamasa Mitsuyoshi, Yukinori Matsuo, Takashi Mizowaki, Ikuo Kanno

Abstract

During therapeutic beam irradiation, an unvisualized three-dimensional (3D) target position should be estimated using an external surrogate with an estimation model. Training periods for the developed model with no additional imaging during beam irradiation were optimized using clinical data. Dual-source 4D-CBCT projection data for 20 lung cancer patients were used for validation. Each patient underwent one to three scans. The actual target positions of each scan were equally divided into two equal parts: one for the modeling and the other for the validating session. A quadratic target position estimation equation was constructed during the modeling session. Various training periods for the session-i.e., modeling periods (TM)-were employed: TM ∈ {5,10,15,25,35} [s]. First, the equation was used to estimate target positions in the validating session of the same scan (intra-scan estimations). Second, the equation was then used to estimate target positions in the validating session of another temporally different scan (inter-scan estimations). The baseline drift of the surrogate and target between scans was corrected. Various training periods for the baseline drift correction-i.e., correction periods (TCs)-were employed: TC ∈ {5,10,15; TC ≤ TM} [s]. Evaluations were conducted with and without the correction. The difference between the actual and estimated target positions was evaluated by the root-mean-square error (RMSE). The range of mean respiratory period and 3D motion amplitude of the target was 2.4-13.0 s and 2.8-34.2 mm, respectively. On intra-scan estimation, the median 3D RMSE was within 1.5-2.1 mm, supported by previous studies. On inter-scan estimation, median elapsed time between scans was 10.1 min. All TMs exhibited 75th percentile 3D RMSEs of 5.0-6.4 mm due to baseline drift of the surrogate and the target. After the correction, those for each TMs fell by 1.4-2.3 mm. The median 3D RMSE for both the 10-s TM and the TC period was 2.4 mm, which plateaued when the two training periods exceeded 10 s. A widely-applicable estimation model for the 3D target positions during beam irradiation was developed. The optimal TM and TC for the model were both 10 s, to allow for more than one respiratory cycle. UMIN000014825 . Registered: 11 August 2014.

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Mendeley readers

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The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 3 11%
Student > Ph. D. Student 3 11%
Student > Doctoral Student 2 7%
Professor 2 7%
Other 2 7%
Other 5 18%
Unknown 11 39%
Readers by discipline Count As %
Medicine and Dentistry 10 36%
Physics and Astronomy 3 11%
Nursing and Health Professions 1 4%
Neuroscience 1 4%
Engineering 1 4%
Other 0 0%
Unknown 12 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 April 2018.
All research outputs
#20,481,952
of 23,043,346 outputs
Outputs from Radiation Oncology
#1,693
of 2,072 outputs
Outputs of similar age
#288,447
of 327,380 outputs
Outputs of similar age from Radiation Oncology
#30
of 47 outputs
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