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Four-Dimensional Cone-Beam CT Algorithm by Extraction of Physical and Motion Parameter of Mobile Targets Retrospective to Image Reconstruction with Motion Modeling

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I Ali

I Ali1*, N Alsbou2 , S Ahmad1 , (1) University of Oklahoma Health Sciences, Oklahoma City, OK, (2) Ohio Northern University, Ada, OH, (3) University of Oklahoma Health Sciences Center, Oklahoma City, OK


SU-E-J-150 (Sunday, July 12, 2015) 3:00 PM - 6:00 PM Room: Exhibit Hall

Purpose: To develop 4D-cone-beam CT (CBCT) algorithm by motion modeling that extracts actual length, CT numbers level and motion amplitude of a mobile target retrospective to image reconstruction by motion modeling.
Methods: The algorithm used three measurable parameters: apparent length and blurred CT number distribution of a mobile target obtained from CBCT images to determine actual length, CT-number value of the stationary target, and motion amplitude. The predictions of this algorithm were tested with mobile targets that with different well-known sizes made from tissue-equivalent gel which was inserted into a thorax phantom. The phantom moved sinusoidally in one-direction to simulate respiratory motion using eight amplitudes ranging 0-20mm.
Results: Using this 4D-CBCT algorithm, three unknown parameters were extracted that include: length of the target, CT number level, speed or motion amplitude for the mobile targets retrospective to image reconstruction. The motion algorithms solved for the three unknown parameters using measurable apparent length, CT number level and gradient for a well-defined mobile target obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on the actual target length and motion amplitude. The gradient of the CT number distribution of the mobile target is dependent on the stationary CT number level, actual target length and motion amplitude. Motion frequency and phase did not affect the elongation and CT number distribution of the mobile target and could not be determined.
Conclusion: A 4D-CBCT motion algorithm was developed to extract three parameters that include actual length, CT number level and motion amplitude or speed of mobile targets directly from reconstructed CBCT images without prior knowledge of the stationary target parameters. This algorithm provides alternative to 4D-CBCT without requirement to motion tracking and sorting of the images into different breathing phases which has potential applications in diagnostic CT imaging and radiotherapy.

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