Literature DB >> 22516384

On-line use of three-dimensional marker trajectory estimation from cone-beam computed tomography projections for precise setup in radiotherapy for targets with respiratory motion.

Esben S Worm1, Morten Høyer, Walther Fledelius, Jens E Nielsen, Lars P Larsen, Per R Poulsen.   

Abstract

PURPOSE: To develop and evaluate accurate and objective on-line patient setup based on a novel semiautomatic technique in which three-dimensional marker trajectories were estimated from two-dimensional cone-beam computed tomography (CBCT) projections. METHODS AND MATERIALS: Seven treatment courses of stereotactic body radiotherapy for liver tumors were delivered in 21 fractions in total to 6 patients by a linear accelerator. Each patient had two to three gold markers implanted close to the tumors. Before treatment, a CBCT scan with approximately 675 two-dimensional projections was acquired during a full gantry rotation. The marker positions were segmented in each projection. From this, the three-dimensional marker trajectories were estimated using a probability based method. The required couch shifts for patient setup were calculated from the mean marker positions along the trajectories. A motion phantom moving with known tumor trajectories was used to examine the accuracy of the method. Trajectory-based setup was retrospectively used off-line for the first five treatment courses (15 fractions) and on-line for the last two treatment courses (6 fractions). Automatic marker segmentation was compared with manual segmentation. The trajectory-based setup was compared with setup based on conventional CBCT guidance on the markers (first 15 fractions).
RESULTS: Phantom measurements showed that trajectory-based estimation of the mean marker position was accurate within 0.3 mm. The on-line trajectory-based patient setup was performed within approximately 5 minutes. The automatic marker segmentation agreed with manual segmentation within 0.36 ± 0.50 pixels (mean ± SD; pixel size, 0.26 mm in isocenter). The accuracy of conventional volumetric CBCT guidance was compromised by motion smearing (≤21 mm) that induced an absolute three-dimensional setup error of 1.6 ± 0.9 mm (maximum, 3.2) relative to trajectory-based setup.
CONCLUSIONS: The first on-line clinical use of trajectory estimation from CBCT projections for precise setup in stereotactic body radiotherapy was demonstrated. Uncertainty in the conventional CBCT-based setup procedure was eliminated with the new method.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22516384     DOI: 10.1016/j.ijrobp.2011.12.007

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  5 in total

1.  Real-time image guidance in laparoscopic liver surgery: first clinical experience with a guidance system based on intraoperative CT imaging.

Authors:  Hannes G Kenngott; Martin Wagner; Matthias Gondan; Felix Nickel; Marco Nolden; Andreas Fetzer; Jürgen Weitz; Lars Fischer; Stefanie Speidel; Hans-Peter Meinzer; Dittmar Böckler; Markus W Büchler; Beat P Müller-Stich
Journal:  Surg Endosc       Date:  2013-11-01       Impact factor: 4.584

2.  Kilovoltage Imaging of Implanted Fiducials to Monitor Intrafraction Motion With Abdominal Compression During Stereotactic Body Radiation Therapy for Gastrointestinal Tumors.

Authors:  Ellen Yorke; Ying Xiong; Qian Han; Pengpeng Zhang; Gikas Mageras; Michael Lovelock; Hai Pham; Jian-Ping Xiong; Karyn A Goodman
Journal:  Int J Radiat Oncol Biol Phys       Date:  2015-11-18       Impact factor: 7.038

3.  Tumor motion tracking based on a four-dimensional computed tomography respiratory motion model driven by an ultrasound tracking technique.

Authors:  Lai-Lei Ting; Ho-Chiao Chuang; Ai-Ho Liao; Chia-Chun Kuo; Hsiao-Wei Yu; Hsin-Chuan Tsai; Der-Chi Tien; Shiu-Chen Jeng; Jeng-Fong Chiou
Journal:  Quant Imaging Med Surg       Date:  2020-01

4.  Proof-of-concept for x-ray based real-time image guidance during cardiac radioablation.

Authors:  Nicholas Hindley; Suzanne Lydiard; Chun-Chien Shieh; Paul Keall
Journal:  Phys Med Biol       Date:  2021-08-24       Impact factor: 3.609

5.  Liver segmentation in CT imaging with enhanced mask region-based convolutional neural networks.

Authors:  Xiaowen Chen; Xiaoqin Wei; Mingyue Tang; Aimin Liu; Ce Lai; Yuanzhong Zhu; Wenjing He
Journal:  Ann Transl Med       Date:  2021-12
  5 in total

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