Literature DB >> 16532943

Improving retrospective sorting of 4D computed tomography data.

Eike Rietzel1, George T Y Chen.   

Abstract

Respiratory correlated CT is commercially available, and we have implemented its routine clinical use in planning lung tumor patients. Its value is determined by the fidelity of the spatiotemporal data set after processing the acquired reconstructed slices. Retrospective sorting of reconstructed slices is based on respiratory phase. However, the existing commercial software inadequately models respiratory phase for about 30% of the patients, mainly due to irregularities in the respiratory cycle. We have developed software that improves phase determination and consequently leads to an improvement of retrospective data sorting to make 4DCT data acquisition feasible for routine clinical use. Peak inhalation and exhalation respiratory states are selected manually; intermediate phases are interpolated. Residual motion artifacts in the resulting 4DCT volumes are reduced and allow use of the 4D imaging studies for treatment planning.

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Year:  2006        PMID: 16532943     DOI: 10.1118/1.2150780

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


  24 in total

1.  Reduction of irregular breathing artifacts in respiration-correlated CT images using a respiratory motion model.

Authors:  Agung Hertanto; Qinghui Zhang; Yu-Chi Hu; Oleksandr Dzyubak; Andreas Rimner; Gig S Mageras
Journal:  Med Phys       Date:  2012-06       Impact factor: 4.071

2.  Development of a novel post-processing treatment planning platform for 4D radiotherapy.

Authors:  Lan Lin; Chengyu Shi; Yaxi Liu; Gregory Swanson; Nikos Papanikolaou
Journal:  Technol Cancer Res Treat       Date:  2008-04

3.  4D CT lung ventilation images are affected by the 4D CT sorting method.

Authors:  Tokihiro Yamamoto; Sven Kabus; Cristian Lorenz; Eric Johnston; Peter G Maxim; Maximilian Diehn; Neville Eclov; Cristian Barquero; Billy W Loo; Paul J Keall
Journal:  Med Phys       Date:  2013-10       Impact factor: 4.071

4.  Automated identification and reduction of artifacts in cine four-dimensional computed tomography (4DCT) images using respiratory motion model.

Authors:  Min Li; Sarah Joy Castillo; Richard Castillo; Edward Castillo; Thomas Guerrero; Liang Xiao; Xiaolin Zheng
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-02-14       Impact factor: 2.924

5.  Characterization and identification of spatial artifacts during 4D-CT imaging.

Authors:  Dongfeng Han; John Bayouth; Sudershan Bhatia; Milan Sonka; Xiaodong Wu
Journal:  Med Phys       Date:  2011-04       Impact factor: 4.071

6.  Prediction error and required internal margin provided for irregular respiratory movements: a phantom study.

Authors:  Nobuyoshi Fukumitsu; Haruko Numajiri; Kayoko Ohnishi; Masashi Mizumoto; Teruhito Aihara; Hitoshi Ishikawa; Toshiyuki Okumura; Koji Tsuboi; Toshiyuki Terunuma; Takeji Sakae; Hideyuki Sakurai
Journal:  Jpn J Radiol       Date:  2015-04-16       Impact factor: 2.374

7.  Variations in tumor size and position due to irregular breathing in 4D-CT: a simulation study.

Authors:  Joyatee Sarker; Alan Chu; Kit Mui; John A Wolfgang; Ariel E Hirsch; George T Y Chen; Gregory C Sharp
Journal:  Med Phys       Date:  2010-03       Impact factor: 4.071

8.  Accuracy in the localization of thoracic and abdominal tumors using respiratory displacement, velocity, and phase.

Authors:  U W Langner; P J Keall
Journal:  Med Phys       Date:  2009-02       Impact factor: 4.071

9.  Retrospective analysis of artifacts in four-dimensional CT images of 50 abdominal and thoracic radiotherapy patients.

Authors:  Tokihiro Yamamoto; Ulrich Langner; Billy W Loo; John Shen; Paul J Keall
Journal:  Int J Radiat Oncol Biol Phys       Date:  2008-09-25       Impact factor: 7.038

10.  Development of a geometry-based respiratory motion-simulating patient model for radiation treatment dosimetry.

Authors:  Juying Zhang; George X Xu; Chengyu Shi; Martin Fuss
Journal:  J Appl Clin Med Phys       Date:  2008-01-21       Impact factor: 2.102

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