論文

査読有り 国際誌
2021年6月

Geometric and dosimetric impact of 3D generative adversarial network-based metal artifact reduction algorithm on VMAT and IMPT for the head and neck region

Radiation Oncology
  • Mitsuhiro Nakamura
  • ,
  • Megumi Nakao
  • ,
  • Keiho Imanishi
  • ,
  • Hideaki Hirashima
  • ,
  • Yusuke Tsuruta

16
1
開始ページ
96
終了ページ
96
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1186/s13014-021-01827-0
出版者・発行元
Springer Science and Business Media LLC

<title>Abstract</title><sec>
<title>Background</title>
We investigated the geometric and dosimetric impact of three-dimensional (3D) generative adversarial network (GAN)-based metal artifact reduction (MAR) algorithms on volumetric-modulated arc therapy (VMAT) and intensity-modulated proton therapy (IMPT) for the head and neck region, based on artifact-free computed tomography (CT) volumes with dental fillings.


</sec><sec>
<title>Methods</title>
Thirteen metal-free CT volumes of the head and neck regions were obtained from The Cancer Imaging Archive. To simulate metal artifacts on CT volumes, we defined 3D regions of the teeth for pseudo-dental fillings from the metal-free CT volumes. HU values of 4000 HU were assigned to the selected teeth region of interest. Two different CT volumes, one with four (m4) and the other with eight (m8) pseudo-dental fillings, were generated for each case. These CT volumes were used as the <italic>Reference</italic>. CT volumes with metal artifacts were then generated from the Reference CT volumes (<italic>Artifacts</italic>). On the Artifacts CT volumes, metal artifacts were manually corrected for using the water density override method with a value of 1.0 g/cm3 (<italic>Water</italic>). By contrast, the CT volumes with reduced metal artifacts using 3D GAN model extension of CycleGAN were also generated (<italic>GAN-MAR</italic>). The structural similarity (SSIM) index within the planning target volume was calculated as quantitative error metric between the Reference CT volumes and the other volumes. After creating VMAT and IMPT plans on the Reference CT volumes, the reference plans were recalculated for the remaining CT volumes.


</sec><sec>
<title>Results</title>
The time required to generate a single GAN-MAR CT volume was approximately 30 s. The median SSIMs were lower in the m8 group than those in the m4 group, and ANOVA showed a significant difference in the SSIM for the m8 group (<italic>p</italic> &lt; 0.05). Although the median differences in D98%, D50% and D2% were larger in the m8 group than the m4 group, those from the reference plans were within 3% for VMAT and 1% for IMPT.


</sec><sec>
<title>Conclusions</title>
The GAN-MAR CT volumes generated in a short time were closer to the Reference CT volumes than the Water and Artifacts CT volumes. The observed dosimetric differences compared to the reference plan were clinically acceptable.


</sec>

リンク情報
DOI
https://doi.org/10.1186/s13014-021-01827-0
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/34092240
PubMed Central
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8182914
URL
https://link.springer.com/content/pdf/10.1186/s13014-021-01827-0.pdf
URL
https://link.springer.com/article/10.1186/s13014-021-01827-0/fulltext.html
ID情報
  • DOI : 10.1186/s13014-021-01827-0
  • eISSN : 1748-717X
  • PubMed ID : 34092240
  • PubMed Central 記事ID : PMC8182914

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