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A clinical study of lung cancer dose calculation accuracy with Monte Carlo simulation

Overview of attention for article published in Radiation Oncology, December 2014
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  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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3 X users

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33 Dimensions

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57 Mendeley
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Title
A clinical study of lung cancer dose calculation accuracy with Monte Carlo simulation
Published in
Radiation Oncology, December 2014
DOI 10.1186/s13014-014-0287-2
Pubmed ID
Authors

Yanqun Zhao, Guohai Qi, Gang Yin, Xianliang Wang, Pei Wang, Jian Li, Mingyong Xiao, Jie Li, Shengwei Kang, Xiongfei Liao

Abstract

BackgroundThe accuracy of dose calculation is crucial to the quality of treatment planning and, consequently, to the dose delivered to patients undergoing radiation therapy. Current general calculation algorithms such as Pencil Beam Convolution (PBC) and Collapsed Cone Convolution (CCC) have shortcomings in regard to severe inhomogeneities, particularly in those regions where charged particle equilibrium does not hold. The aim of this study was to evaluate the accuracy of the PBC and CCC algorithms in lung cancer radiotherapy using Monte Carlo (MC) technology.Methods and materialsFour treatment plans were designed using Oncentra Masterplan TPS for each patient. Two intensity-modulated radiation therapy (IMRT) plans were developed using the PBC and CCC algorithms, and two three-dimensional conformal therapy (3DCRT) plans were developed using the PBC and CCC algorithms. The DICOM-RT files of the treatment plans were exported to the Monte Carlo system to recalculate. The dose distributions of GTV, PTV and ipsilateral lung calculated by the TPS and MC were compared.ResultFor 3DCRT and IMRT plans, the mean dose differences for GTV between the CCC and MC increased with decreasing of the GTV volume. For IMRT, the mean dose differences were found to be higher than that of 3DCRT. The CCC algorithm overestimated the GTV mean dose by approximately 3% for IMRT. For 3DCRT plans, when the volume of the GTV was greater than 100 cm3, the mean doses calculated by CCC and MC almost have no difference. PBC shows large deviations from the MC algorithm. For the dose to the ipsilateral lung, the CCC algorithm overestimated the dose to the entire lung, and the PBC algorithm overestimated V20 but underestimated V5; the difference in V10 was not statistically significant.ConclusionsPBC substantially overestimates the dose to the tumour, but the CCC is similar to the MC simulation. It is recommended that the treatment plans for lung cancer be developed using an advanced dose calculation algorithm other than PBC. MC can accurately calculate the dose distribution in lung cancer and can provide a notably effective tool for benchmarking the performance of other dose calculation algorithms within patients.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Iran, Islamic Republic of 1 2%
United Kingdom 1 2%
Unknown 55 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 25%
Student > Bachelor 7 12%
Researcher 6 11%
Student > Ph. D. Student 4 7%
Student > Doctoral Student 3 5%
Other 11 19%
Unknown 12 21%
Readers by discipline Count As %
Physics and Astronomy 18 32%
Medicine and Dentistry 12 21%
Engineering 4 7%
Nursing and Health Professions 1 2%
Computer Science 1 2%
Other 6 11%
Unknown 15 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 05 December 2019.
All research outputs
#13,185,276
of 22,774,233 outputs
Outputs from Radiation Oncology
#597
of 2,050 outputs
Outputs of similar age
#169,673
of 354,373 outputs
Outputs of similar age from Radiation Oncology
#16
of 87 outputs
Altmetric has tracked 22,774,233 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,050 research outputs from this source. They receive a mean Attention Score of 2.7. This one has gotten more attention than average, scoring higher than 69% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 354,373 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 87 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.