Literature DB >> 19028282

A method to estimate mean position, motion magnitude, motion correlation, and trajectory of a tumor from cone-beam CT projections for image-guided radiotherapy.

Per Rugaard Poulsen1, Byungchul Cho, Paul J Keall.   

Abstract

PURPOSE: To develop a probability-based method for estimating the mean position, motion magnitude, and trajectory of a tumor using cone-beam CT (CBCT) projections. METHOD AND MATERIALS: CBCT acquisition was simulated for more than 80 hours of patient-measured trajectories for thoracic/abdominal tumors and prostate. The trajectories were divided into 60-second segments for which CBCT was simulated by projecting the tumor position onto a rotating imager. Tumor (surrogate) visibility on all projections was assumed. The mean and standard deviation of the tumor position and motion correlation along the three axes were determined with maximum likelihood estimation based on the projection data, assuming a Gaussian spatial distribution. The unknown position component along the imager axis was approximated by its expectation value, determined by the Gaussian distribution. Transformation of the resulting three-dimensional position to patient coordinates provided the estimated trajectory. Two trajectories were experimentally investigated by CBCT acquisition of a phantom.
RESULTS: The root-mean-square error of the estimated mean position was 0.05 mm. The root-mean-square error of the trajectories was <1 mm in 99.1% of the thorax/abdomen cases and in 99.7% of the prostate cases. The experimental trajectory estimation agreed with the actual phantom trajectory within 0.44 mm in any direction. Clinical applicability was demonstrated by estimating the tumor trajectory for a pancreas cancer case.
CONCLUSIONS: A method for estimation of mean position, motion magnitude, and trajectory of a tumor from CBCT projections has been developed. The accuracy was typically much better than 1 mm. The method is applicable to motion-inclusive, respiratory-gated, and tumor-tracking radiotherapy.

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Year:  2008        PMID: 19028282     DOI: 10.1016/j.ijrobp.2008.07.037

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


  22 in total

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3.  Efficient and accurate stereotactic radiotherapy using flattening filter free beams and HexaPOD robotic tables.

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Authors:  Bernard L Jones; Tracey Schefter; Moyed Miften
Journal:  Radiother Oncol       Date:  2015-04-15       Impact factor: 6.280

5.  Marker-free lung tumor trajectory estimation from a cone beam CT sinogram.

Authors:  Geoffrey D Hugo; Jian Liang; Di Yan
Journal:  Phys Med Biol       Date:  2010-04-14       Impact factor: 3.609

6.  A method for robust segmentation of arbitrarily shaped radiopaque structures in cone-beam CT projections.

Authors:  Per Rugaard Poulsen; Walther Fledelius; Paul J Keall; Elisabeth Weiss; Jun Lu; Emily Brackbill; Geoffrey D Hugo
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Authors:  Paul J Keall; Doan Trang Nguyen; Ricky O'Brien; Pengpeng Zhang; Laura Happersett; Jenny Bertholet; Per R Poulsen
Journal:  Int J Radiat Oncol Biol Phys       Date:  2018-04-14       Impact factor: 7.038

Review 8.  Recent progress in pancreatic cancer.

Authors:  Christopher L Wolfgang; Joseph M Herman; Daniel A Laheru; Alison P Klein; Michael A Erdek; Elliot K Fishman; Ralph H Hruban
Journal:  CA Cancer J Clin       Date:  2013-07-15       Impact factor: 508.702

9.  A Bayesian approach for three-dimensional markerless tumor tracking using kV imaging during lung radiotherapy.

Authors:  Chun-Chien Shieh; Vincent Caillet; Michelle Dunbar; Paul J Keall; Jeremy T Booth; Nicholas Hardcastle; Carol Haddad; Thomas Eade; Ilana Feain
Journal:  Phys Med Biol       Date:  2017-03-21       Impact factor: 3.609

10.  A Novel Method of Cone Beam CT Projection Binning Based on Image Registration.

Authors:  Seonyeong Park; Siyong Kim; Byongyong Yi; Geoffrey Hugo; H Michael Gach; Yuichi Motai
Journal:  IEEE Trans Med Imaging       Date:  2017-03-31       Impact factor: 10.048

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