Literature DB >> 18695293

Combination of intensity-based image registration with 3D simulation in radiation therapy.

Pan Li1, Urban Malsch, Rolf Bendl.   

Abstract

Modern techniques of radiotherapy like intensity modulated radiation therapy (IMRT) make it possible to deliver high dose to tumors of different irregular shapes at the same time sparing surrounding healthy tissue. However, internal tumor motion makes precise calculation of the delivered dose distribution challenging. This makes analysis of tumor motion necessary. One way to describe target motion is using image registration. Many registration methods have already been developed previously. However, most of them belong either to geometric approaches or to intensity approaches. Methods which take account of anatomical information and results of intensity matching can greatly improve the results of image registration. Based on this idea, a combined method of image registration followed by 3D modeling and simulation was introduced in this project. Experiments were carried out for five patients 4DCT lung datasets. In the 3D simulation, models obtained from images of end-exhalation were deformed to the state of end-inhalation. Diaphragm motions were around -25 mm in the cranial-caudal (CC) direction. To verify the quality of our new method, displacements of landmarks were calculated and compared with measurements in the CT images. Improvement of accuracy after simulations has been shown compared to the results obtained only by intensity-based image registration. The average improvement was 0.97 mm. The average Euclidean error of the combined method was around 3.77 mm. Unrealistic motions such as curl-shaped deformations in the results of image registration were corrected. The combined method required less than 30 min. Our method provides information about the deformation of the target volume, which we need for dose optimization and target definition in our planning system.

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Year:  2008        PMID: 18695293     DOI: 10.1088/0031-9155/53/17/011

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  8 in total

1.  Mass preserving nonrigid registration of CT lung images using cubic B-spline.

Authors:  Youbing Yin; Eric A Hoffman; Ching-Long Lin
Journal:  Med Phys       Date:  2009-09       Impact factor: 4.071

2.  Deformable image registration of heterogeneous human lung incorporating the bronchial tree.

Authors:  Adil Al-Mayah; Joanne Moseley; Mike Velec; Shannon Hunter; Kristy Brock
Journal:  Med Phys       Date:  2010-09       Impact factor: 4.071

3.  Four-dimensional deformable image registration using trajectory modeling.

Authors:  Edward Castillo; Richard Castillo; Josue Martinez; Maithili Shenoy; Thomas Guerrero
Journal:  Phys Med Biol       Date:  2010-01-07       Impact factor: 3.609

4.  Evaluation of image registration spatial accuracy using a Bayesian hierarchical model.

Authors:  Suyu Liu; Ying Yuan; Richard Castillo; Thomas Guerrero; Valen E Johnson
Journal:  Biometrics       Date:  2014-02-27       Impact factor: 2.571

5.  Modeling lung deformation: a combined deformable image registration method with spatially varying Young's modulus estimates.

Authors:  Min Li; Edward Castillo; Xiao-Lin Zheng; Hong-Yan Luo; Richard Castillo; Yi Wu; Thomas Guerrero
Journal:  Med Phys       Date:  2013-08       Impact factor: 4.071

6.  A finite element head and neck model as a supportive tool for deformable image registration.

Authors:  Jihun Kim; Kazuhiro Saitou; Martha M Matuszak; James M Balter
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-12-24       Impact factor: 2.924

7.  A reference dataset for deformable image registration spatial accuracy evaluation using the COPDgene study archive.

Authors:  Richard Castillo; Edward Castillo; David Fuentes; Moiz Ahmad; Abbie M Wood; Michelle S Ludwig; Thomas Guerrero
Journal:  Phys Med Biol       Date:  2013-04-10       Impact factor: 3.609

8.  A hybrid, image-based and biomechanics-based registration approach to markerless intraoperative nodule localization during video-assisted thoracoscopic surgery.

Authors:  Pablo Alvarez; Simon Rouzé; Michael I Miga; Yohan Payan; Jean-Louis Dillenseger; Matthieu Chabanas
Journal:  Med Image Anal       Date:  2021-01-30       Impact factor: 13.828

  8 in total

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