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Prediction of target position from multiple fiducial markers by partial least squares regression in real-time tumor-tracking radiation therapy

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Title: Prediction of target position from multiple fiducial markers by partial least squares regression in real-time tumor-tracking radiation therapy
Authors: Ukon, Kanako Browse this author
Arai, Yohei Browse this author
Takao, Seishin Browse this author →KAKEN DB
Matsuura, Taeko Browse this author →KAKEN DB
Ishikawa, Masayori Browse this author →KAKEN DB
Shirato, Hiroki Browse this author →KAKEN DB
Shimizu, Shinichi Browse this author →KAKEN DB
Umegaki, Kikuo Browse this author →KAKEN DB
Miyamoto, Naoki Browse this author →KAKEN DB
Keywords: real-time tumor-tracking radiation therapy
fiducial marker
partial least squares regression (PLSR)
tracking irradiation
gating irradiation
Issue Date: Sep-2021
Publisher: Oxford University Press
Journal Title: Journal of Radiation Research
Volume: 62
Issue: 5
Start Page: 926
End Page: 933
Publisher DOI: 10.1093/jrr/rrab054
Abstract: The purpose of this work is to show the usefulness of a prediction method of tumor location based on partial least squares regression (PLSR) using multiple fiducial markers. The trajectory data of respiratory motion of four internal fiducial markers inserted in lungs were used for the analysis. The position of one of the four markers was assumed to be the tumor position and was predicted by other three fiducial markers. Regression coefficients for prediction of the position of the tumor-assumed marker from the fiducial markers' positions is derived by PLSR. The tracking error and the gating error were evaluated assuming two possible variations. First, the variation of the position definition of the tumor and the markers on treatment planning computed tomograhy (CT) images. Second, the intra-fractional anatomical variation which leads the distance change between the tumor and markers during the course of treatment. For comparison, rigid predictions and ordinally multiple linear regression (MLR) predictions were also evaluated. The tracking and gating errors of PLSR prediction were smaller than those of other prediction methods. Ninety-fifth percentile of tracking/gating error in all trials were 3.7/4.1 mm, respectively in PLSR prediction for superior-inferior direction. The results suggested that PLSR prediction was robust to variations, and clinically applicable accuracy could be achievable for targeting tumors.
Type: article
Appears in Collections:工学院・工学研究院 (Graduate School of Engineering / Faculty of Engineering) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

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