論文

査読有り
2022年3月

Dosiomic feature comparison between dose-calculation algorithms used for lung stereotactic body radiation therapy.

Radiological physics and technology
  • Takanori Adachi
  • Mitsuhiro Nakamura
  • Ryo Kakino
  • Hideaki Hirashima
  • Hiraku Iramina
  • Yusuke Tsuruta
  • Tomohiro Ono
  • Nobutaka Mukumoto
  • Yuki Miyabe
  • Yukinori Matsuo
  • Takashi Mizowaki
  • 全て表示

15
1
開始ページ
63
終了ページ
71
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1007/s12194-022-00651-9

To evaluate the reproducibility of dose-based radiomic (dosiomic) features between dose-calculation algorithms for lung stereotactic body radiation therapy (SBRT). We analyzed 105 patients with early-stage non-small cell lung cancer who underwent lung SBRT between March 2011 and December 2017. Radiation doses of 48, 60, and 70 Gy were prescribed to the isocenter in 4-8 fractions. Dose calculations were performed using X-ray voxel Monte Carlo (XVMC) on the iPlan radiation treatment planning system (RTPS). Thereafter, the radiation doses were recalculated using the Acuros XB (AXB) and analytical anisotropic algorithm (AAA) on the Eclipse RTPS while maintaining the XVMC-calculated monitor units and beam arrangements. A total of 6808 dosiomic features were extracted without preprocessing (112 shape, 144 first-order, and 600 texture features) or with wavelet filters to eight decompositions (1152 first-order and 4800 texture features). Features with absolute pairwise concordance correlation coefficients-|CCcon|-values exceeding or equaling 0.85 were considered highly reproducible. Subgroup analyses were performed considering the wavelet filters and prescribed doses. The numbers of highly reproducible first-order and texture features were 34.8%, 26.9%, and 31.0% for the XVMC-AXB, XVMC-AAA, and AXB-AAA pairs, respectively. The maximum difference between the mean |CCcon| values was 0.70 and 0.11 for the subgroup analyses of wavelet filters and prescribed dose, respectively. The application of wavelet filter-based dosiomic analyses may be limited when using different types of dose-calculation algorithms for lung SBRT.

リンク情報
DOI
https://doi.org/10.1007/s12194-022-00651-9
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/35067904
ID情報
  • DOI : 10.1007/s12194-022-00651-9
  • PubMed ID : 35067904

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