Literature DB >> 16912374

MRI-based measurements of respiratory motion variability and assessment of imaging strategies for radiotherapy planning.

J M Blackall1, S Ahmad, M E Miquel, J R McClelland, D B Landau, D J Hawkes.   

Abstract

Respiratory organ motion has a significant impact on the planning and delivery of radiotherapy (RT) treatment for lung cancer. Currently widespread techniques, such as 4D-computed tomography (4DCT), cannot be used to measure variability of this motion from one cycle to the next. In this paper, we describe the use of fast magnetic resonance imaging (MRI) techniques to investigate the intra- and inter-cycle reproducibility of respiratory motion and also to estimate the level of errors that may be introduced into treatment delivery by using various breath-hold imaging strategies during lung RT planning. A reference model of respiratory motion is formed to enable comparison of different breathing cycles at any arbitrary position in the respiratory cycle. This is constructed by using free-breathing images from the inhale phase of a single breathing cycle, then co-registering the images, and thereby tracking landmarks. This reference model is then compared to alternative models constructed from images acquired during the exhale phase of the same cycle and the inhale phase of a subsequent cycle, to assess intra- and inter-cycle variability ('hysteresis' and 'reproducibility') of organ motion. The reference model is also compared to a series of models formed from breath-hold data at exhale and inhale. Evaluation of these models is carried out on data from ten healthy volunteers and five lung cancer patients. Free-breathing models show good levels of intra- and inter-cycle reproducibility across the tidal breathing range. Mean intra-cycle errors in the position of organ surface landmarks of 1.5(1.4)-3.5(3.3) mm for volunteers and 2.8(1.8)-5.2(5.2) mm for patients. Equivalent measures of inter-cycle variability across this range are 1.7(1.0)-3.9(3.3) mm for volunteers and 2.8(1.8)-3.3(2.2) mm for patients. As expected, models based on breath-hold sequences do not represent normal tidal motion as well as those based on free-breathing data, with mean errors of 4.4(2.2)-7.7(3.9) mm for volunteers and 10.1(6.1)-12.5(6.3) mm for patients. Errors are generally larger still when using a single breath-hold image at either exhale or inhale to represent the lung. This indicates that account should be taken of intra- and inter-cycle respiratory motion variability and that breath-hold-based methods of obtaining data for RT planning may potentially introduce large errors. This approach to analysis of motion and variability has potential to inform decisions about treatment margins and optimize RT planning.

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Year:  2006        PMID: 16912374     DOI: 10.1088/0031-9155/51/17/003

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


  40 in total

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2.  Ultrasound echoes as biometric navigators.

Authors:  Benjamin M Schwartz; Nathan J McDannold
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3.  Digital tomosynthesis for respiratory gated liver treatment: clinical feasibility for daily image guidance.

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Review 4.  Magnetic resonance imaging in lung: a review of its potential for radiotherapy.

Authors:  Shivani Kumar; Gary Liney; Robba Rai; Lois Holloway; Daniel Moses; Shalini K Vinod
Journal:  Br J Radiol       Date:  2016-02-03       Impact factor: 3.039

Review 5.  Imaging techniques for tumour delineation and heterogeneity quantification of lung cancer: overview of current possibilities.

Authors:  Wouter van Elmpt; Catharina M L Zegers; Marco Das; Dirk De Ruysscher
Journal:  J Thorac Dis       Date:  2014-04       Impact factor: 2.895

6.  Blind Compressed Sensing Enables 3-Dimensional Dynamic Free Breathing Magnetic Resonance Imaging of Lung Volumes and Diaphragm Motion.

Authors:  Sampada Bhave; Sajan Goud Lingala; John D Newell; Scott K Nagle; Mathews Jacob
Journal:  Invest Radiol       Date:  2016-06       Impact factor: 6.016

7.  Adaptive 4D MR imaging using navigator-based respiratory signal for MRI-guided therapy.

Authors:  Junichi Tokuda; Shigehiro Morikawa; Hasnine A Haque; Tetsuji Tsukamoto; Kiyoshi Matsumiya; Hongen Liao; Ken Masamune; Takeyoshi Dohi
Journal:  Magn Reson Med       Date:  2008-05       Impact factor: 4.668

8.  A post-processing method based on interphase motion correction and averaging to improve image quality of 4D magnetic resonance imaging: a clinical feasibility study.

Authors:  Zixin Deng; Jianing Pang; Yi Lao; Xiaoming Bi; Guan Wang; Yuhua Chen; Matthias Fenchel; Richard Tuli; Debiao Li; Wensha Yang; Zhaoyang Fan
Journal:  Br J Radiol       Date:  2019-01-03       Impact factor: 3.039

9.  Simulation of spatiotemporal CT data sets using a 4D MRI-based lung motion model.

Authors:  Mirko Marx; Jan Ehrhardt; René Werner; Heinz-Peter Schlemmer; Heinz Handels
Journal:  Int J Comput Assist Radiol Surg       Date:  2013-12-10       Impact factor: 2.924

10.  MRI Investigation of the Linkage Between Respiratory Motion of the Heart and Markers on Patient's Abdomen and Chest: Implications for Respiratory Amplitude Binning List-Mode PET and SPECT Studies.

Authors:  Paul Dasari; Karen Johnson; Joyoni Dey; Clifford Lindsay; Mohammed S Shazeeb; Joyeeta Mitra Mukherjee; Shaokuan Zheng; Michael A King
Journal:  IEEE Trans Nucl Sci       Date:  2014-02-06       Impact factor: 1.679

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