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Author O.’Connell, D. P. ♦ Thomas, D. H. ♦ Dou, T. H. ♦ Lamb, J. M. ♦ Yang, L. ♦ Low, D. A.
Source United States Department of Energy Office of Scientific and Technical Information
Content type Text
Language English
Subject Keyword APPLIED LIFE SCIENCES ♦ ACCURACY ♦ ANIMAL TISSUES ♦ COMPUTERIZED TOMOGRAPHY ♦ DEFORMATION ♦ ERRORS ♦ IMAGE PROCESSING ♦ IMAGES ♦ LUNGS ♦ NEOPLASMS ♦ NMR IMAGING ♦ PATIENTS ♦ PLANNING ♦ RADIOTHERAPY ♦ RESPIRATION ♦ SIMULATION
Abstract Purpose: A respiratory motion model previously used to generate breathing-gated CT images was used with cine MR images. Accuracy and predictive ability of the in-plane models were evaluated. Methods: Sagittalplane cine MR images of a patient undergoing treatment on a ViewRay MRI/radiotherapy system were acquired before and during treatment. Images were acquired at 4 frames/second with 3.5 × 3.5 mm resolution and a slice thickness of 5 mm. The first cine frame was deformably registered to following frames. Superior/inferior component of the tumor centroid position was used as a breathing surrogate. Deformation vectors and surrogate measurements were used to determine motion model parameters. Model error was evaluated and subsequent treatment cines were predicted from breathing surrogate data. A simulated CT cine was created by generating breathing-gated volumetric images at 0.25 second intervals along the measured breathing trace, selecting a sagittal slice and downsampling to the resolution of the MR cines. A motion model was built using the first half of the simulated cine data. Model accuracy and error in predicting the remaining frames of the cine were evaluated. Results: Mean difference between model predicted and deformably registered lung tissue positions for the 28 second preview MR cine acquired before treatment was 0.81 +/− 0.30 mm. The model was used to predict two minutes of the subsequent treatment cine with a mean accuracy of 1.59 +/− 0.63 mm. Conclusion: Inplane motion models were built using MR cine images and evaluated for accuracy and ability to predict future respiratory motion from breathing surrogate measurements. Examination of long term predictive ability is ongoing. The technique was applied to simulated CT cines for further validation, and the authors are currently investigating use of in-plane models to update pre-existing volumetric motion models used for generation of breathing-gated CT planning images.
ISSN 00942405
Educational Use Research
Learning Resource Type Article
Publisher Date 2015-06-15
Publisher Place United States
Journal Medical Physics
Volume Number 42
Issue Number 6


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