Evaluation of the effect of user-guided deformable image registration of thoracic images on registration accuracy among users

Yujiro Nakajima, Noriyuki Kadoya, Takayuki Kanai, Masahide Saito, Satoshi Kito, Shimpei Hashimoto, Katsuyuki Karasawa, Keiichi Jingu

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

User-guided deformable image registration (DIR) has allowed users to actively participate in the DIR process and is expected to improve DIR accuracy. The purpose of this study was to evaluate the time required for and effect of user-guided DIR on registration accuracy for thoracic images among users. In this study, 4-dimensional computed tomographic images of 10 thoracic cancer patients were used. The dataset for these patients was provided by DIR-Lab (www.dir-lab.com) and included a coordinate list of anatomical landmarks (300 bronchial bifurcations). Four medical physicists from different institutions performed DIR between peak-inhale and peak-exhale images with/without the user-guided DIR tool, Reg Refine, implemented in MIM Maestro (MIM software, Cleveland, OH). DIR accuracy was quantified by using target registration errors (TREs) for 300 anatomical landmarks in each patient. The average TREs with user-guided DIR in the 10 images by the 4 medical physicists were 1.48, 1.80, 3.46, and 3.55 mm, respectively, whereas the TREs without user-guided DIR were 3.28, 3.45, 3.56, and 3.28 mm, respectively. The average times taken by the 4 physicists to use the user-guided DIR were 10.0, 6.7, 7.1, and 8.0 min, respectively. This study demonstrated that user-guided DIR can improve DIR accuracy and requires only a moderate amount of time (<10 min). However, 2 of the 4 users did not show much improvement in DIR accuracy, which indicated the necessity of training prior to use of user-guided DIR.

Original languageEnglish
Pages (from-to)206-212
Number of pages7
JournalMedical Dosimetry
Volume45
Issue number3
DOIs
Publication statusPublished - 2020 Sept 1

Keywords

  • 4DCT data
  • Deformable image registration
  • Lung
  • Validation

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