A study of quantitative indicators for slice sorting in cine-mode 4DCT
- Abstract
- The uncertainties of four-dimensional computed tomography (4DCT), also called as residual motion artefacts (RMA), induced from irregular respiratory patterns can degrade the quality of overall radiotherapy. This study aims to quantify and reduce those uncertainties. A comparative study on quantitative indicators for RMA was performed, and based on this, we proposed a new 4DCT sorting method that is applicable without disrupting the current clinical workflow. In addition to the default phase sorting strategy, both additional amplitude information from external surrogates and the quantitative metric for RMA, investigated in this study, were introduced. The comparison of quantitative indicators and the performance of the proposed sorting method were evaluated via 10 cases of breath-hold (BH) CT and 30 cases of 4DCT. It was confirmed that N-RMSD (normalised root-mean-square-deviation) was best matched to the visual standards of our institute's regime, manual sorting method, and could accurately represent RMA. The performance of the proposed method to reduce 4DCT uncertainties was improved by about 18.8% in the averaged value of N-RMSD compared to the default phase sorting method. To the best of our knowledge, this is the first study that evaluates RMA indicators using both BHCT and 4DCT with visual-criteria-based manual sorting and proposes an improved 4DCT sorting strategy based on them.
- Author(s)
- Changhwan Kim; Hojae Kim; Sung-Woo Kim; Youngmoon Goh; Min-Jae Park; Hojin Kim; Chiyoung Jeong; Byungchul Cho; Eun Kyung Choi; Sang-Wook Lee; Sang Min Yoon; Su Ssan Kim; Jin-Hong Park; Jinhong Jung; Si Yeol Song; Jungwon Kwak
- Issued Date
- 2022
- Type
- Article
- Keyword
- Algorithms; Clinical medicine; Comparative studies; Evaluation; Methodology; Methods; Physical sciences; Radiotherapy; Respiration; Tomography; Uncertainty
Workflow
- DOI
- 10.1371/journal.pone.0272639
- URI
- https://oak.ulsan.ac.kr/handle/2021.oak/14957
- Publisher
- PLOS ONE
- Language
- 한국어
- ISSN
- 1932-6203
- Citation Volume
- 17
- Citation Number
- 8
- Citation Start Page
- 1
- Citation End Page
- 24
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Appears in Collections:
- Medicine > Nursing
- 공개 및 라이선스
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