ArticleFrontiers in oncology2022
Quantifying 6D tumor motion and calculating PTV margins during liver stereotactic radiotherapy with fiducial tracking.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Comparison of Six- and Three-Dimensional Error Corrections for the Planning Target Volume in Patients With Nasopharyngeal Cancer.Journal of medical radiation sciences · 2026Article
- Assessment of rotational dose perturbations in SBRT: A radiomic-dosiomic predictive model based on the structural similarity index measure.Journal of applied clinical medical physics · 2026Article
- Harnessing Next-Generation 3D Cancer Models to Elucidate Tumor-Microbiome Crosstalk.Advanced healthcare materials · 2026Review
- PhysMorph: A biomechanical and image-guided deep learning framework for real-time multi-modal liver image registration.Physics and imaging in radiation oncology · 2026Article
- Margin for compensating displacement of adrenal gland metastasis and fiducial marker along with respiratory phase in real-time motion-tracking radiation therapy.Radiological physics and technology · 2025Article
- Analysis of intra- and inter-observer variability in 4D liver ultrasound landmark labeling.Journal of medical imaging (Bellingham, Wash.) · 2025Article
- Optimized fiducial marker placement using B-spline surface modeling and graph theory for Cyberknife stereotactic body radiotherapy for superficial tumors.Precision radiation oncology · 2025Article
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Authors and funding
6 authors.
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Abstract
Objective: Our study aims to estimate intra-fraction six-dimensional (6D) tumor motion with rotational correction and the related correlations between motions of different degrees of freedom (DoF), as well as quantify sufficient anisotropic clinical target volume (CTV) to planning target volume (PTV) margins during stereotactic body radiotherapy (SBRT) of liver cancer with fiducial tracking technique. Methods: A cohort of 12 patients who were implanted with 3 or 4 golden markers were included in this study, and 495 orthogonal kilovoltage (kV) pairs of images acquired during the first fraction were used to extract the spacial position of each golden marker. Translational and rotational motions of tumor were calculated based on the marker coordinates by using an iterative closest point (ICP) algorithm. Moreover, the Pearson product-moment correlation coefficients ( Results: The mean translational variability of tumors were 0.56, 1.24 and 3.38 mm in the left-right (LR, Conclusions: The maximum translational motion was in SI direction, and the largest correlation coefficient of
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