Literature DB >> 8815382

Automatic three-dimensional inspection of patient setup in radiation therapy using portal images, simulator images, and computed tomography data.

K G Gilhuijs1, P J van de Ven, M van Herk.   

Abstract

In external beam radiotherapy, conventional analysis of portal images in two dimensions (2D) is limited to verification of in-plane rotations and translations of the patient. We developed and clinically tested a new method for automatic quantification of the patient setup in three dimensions (3D) using one set of computed tomography (CT) data and two transmission images. These transmission images can be either a pair of simulator images or a pair of portal images. Our procedure adjusts the position and orientation of the CT data in order to maximize the distance through bone in the CT data along lines between the focus of the irradiation unit and bony structures in the transmission images. For this purpose, bony features are either automatically detected or manually delineated in the transmission images. The performance of the method was quantified by aligning randomly displaced CT data with transmission images simulated from digitally reconstructed radiographs. In addition, the clinical performance were assessed in a limited number of images of prostate cancer and parotid gland tumor treatments. The complete procedure takes less than 2 min on a 90-MHz Pentium PC. The alignment time is 50 s for portal images and 80 s for simulator images. The accuracy is about 1 mm and 1 degrees. Application to clinical cases demonstrated that the procedure provides essential information for the correction of setup errors in case of large rotations (typically larger than 2 degrees) in the setup. The 3D procedure was found to be robust for imperfections in the delineation of bony structures in the transmission images. Visual verification of the results remains, however, necessary. It can be concluded that our strategy for automatic analysis of patient setup in 3D is accurate and robust. The procedure is relatively fast and reduces the human workload compared with existing techniques for the quantification of patient setup in 3D. In addition, the procedure improves the accuracy of treatment verification in 2D in some cases where rotational deviations in the setup occur.

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Year:  1996        PMID: 8815382     DOI: 10.1118/1.597801

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  12 in total

1.  Automated 2D-3D registration of a radiograph and a cone beam CT using line-segment enhancement.

Authors:  Reshma Munbodh; David A Jaffray; Douglas J Moseley; Zhe Chen; Jonathan P S Knisely; Pascal Cathier; James S Duncan
Journal:  Med Phys       Date:  2006-05       Impact factor: 4.071

2.  A frequency-based approach to locate common structure for 2D-3D intensity-based registration of setup images in prostate radiotherapy.

Authors:  Reshma Munbodh; Zhe Chen; David A Jaffray; Douglas J Moseley; Jonathan P S Knisely; James S Duncan
Journal:  Med Phys       Date:  2007-07       Impact factor: 4.071

3.  Quality assurance for kilo- and megavoltage in-room imaging and localization for off- and online setup error correction.

Authors:  James M Balter; Larry E Antonuk
Journal:  Int J Radiat Oncol Biol Phys       Date:  2008       Impact factor: 7.038

4.  Automated 2D-3D registration of portal images and CT data using line-segment enhancement.

Authors:  Reshma Munbodh; Zhe Chen; David A Jaffray; Douglas J Moseley; Jonathan P S Knisely; James S Duncan
Journal:  Med Phys       Date:  2008-10       Impact factor: 4.071

5.  Vesselness-based 2D-3D registration of the coronary arteries.

Authors:  Daniel Ruijters; Bart M ter Haar Romeny; Paul Suetens
Journal:  Int J Comput Assist Radiol Surg       Date:  2009-05-07       Impact factor: 2.924

6.  Fast reconstructed radiographs from octree-compressed volumetric data.

Authors:  Mark Fisher; Osama Dorgham; Stephen D Laycock
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-07-22       Impact factor: 2.924

7.  Positioning of port films for radiation: variability is present.

Authors:  Alexander Lukez; Lauren O'Loughlin; Mashhood Bodla; Jennifer Baima; Janaki Moni
Journal:  Med Oncol       Date:  2018-04-21       Impact factor: 3.064

8.  A gradient feature weighted Minimax algorithm for registration of multiple portal images to 3DCT volumes in prostate radiotherapy.

Authors:  Sudhakar Chelikani; Kailasnath Purushothaman; Jonathan Knisely; Zhe Chen; Ravinder Nath; Ravi Bansal; James Duncan
Journal:  Int J Radiat Oncol Biol Phys       Date:  2006-06-01       Impact factor: 7.038

9.  Evaluation of Image Enhancement Method on Target Registration Using Cone Beam CT in Radiation Therapy.

Authors:  Hui Yan; Ren Lei; Jackie Wu; Fu Di; Fang-Fang Yin
Journal:  Clin Med Oncol       Date:  2008-03-28

10.  Guide to clinical use of electronic portal imaging.

Authors:  M G Herman; J J Kruse; C R Hagness
Journal:  J Appl Clin Med Phys       Date:  2000       Impact factor: 2.102

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