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电影模式 4DCT 中体素分类的定量指标研究。

A study of quantitative indicators for slice sorting in cine-mode 4DCT.

机构信息

Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Republic of Korea.

Department of Radiation Oncology, Yonsei Cancer Center, Seoul, Republic of Korea.

出版信息

PLoS One. 2022 Aug 26;17(8):e0272639. doi: 10.1371/journal.pone.0272639. eCollection 2022.

DOI:10.1371/journal.pone.0272639
PMID:36026490
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9417040/
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.

摘要

四维计算机断层扫描（4DCT）的不确定性，也称为残余运动伪影（RMA），可能会因不规则的呼吸模式而降低整体放射治疗的质量。本研究旨在量化和减少这些不确定性。对 RMA 的定量指标进行了比较研究，并在此基础上提出了一种新的 4DCT 分类方法，该方法可在不影响当前临床工作流程的情况下应用。除了默认的相位分类策略外，本研究还引入了外部替代物的附加幅度信息和 RMA 的定量指标。通过 10 例屏气（BH）CT 和 30 例 4DCT 对定量指标和所提出的分类方法的性能进行了比较。结果证实，归一化均方根偏差（N-RMSD）与我们研究所的制度、手动分类方法的视觉标准最匹配，并且可以准确地表示 RMA。与默认的相位分类方法相比，所提出的方法在 N-RMSD 的平均值上提高了约 18.8%，从而改善了降低 4DCT 不确定性的性能。据我们所知，这是第一项使用 BHCT 和 4DCT 结合基于视觉标准的手动分类来评估 RMA 指标并提出基于这些指标的改进 4DCT 分类策略的研究。

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