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SU‐E‐I‐13: Theoretical Modeling of the Variations of CT Number Distributions for Mobile Targets in Cone‐Beam Computed Tomographic Imaging
Author(s) -
Ali I,
Alsbou N,
Algan O,
Herman T,
Ahmad S
Publication year - 2013
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4814118
Subject(s) - imaging phantom , cone beam computed tomography , medical imaging , motion (physics) , phase (matter) , physics , computer science , optics , computed tomography , computer vision , artificial intelligence , radiology , medicine , quantum mechanics
Purpose: To investigate quantitatively variations in CT number distributions of mobile targets in cone‐beam CT (CBCT) imaging. A mathematical model was developed to predict variations in the CT number distributions and their dependence on motion parameters of mobile targets. Materials and Methods: CBCT images were acquired for three targets manufactured from homogenous water‐equivalent gel inserted into a commercial mobile thorax phantom. The phantom moved with controlled cyclic motion patterns in one‐dimension along the superior‐inferior direction to simulate patient respiratory motion. Profiles of the CT number distributions of the static and mobile targets were obtained using CBCT images. Mathematical modeling was developed to predict the variations in CT number distributions and their dependence on the motion parameters of targets moving in one‐dimension using CBCT imaging. Results: The mathematical model of CT number distributions of mobile targets in CBCT reproduced the measured CT number distributions and predicted their dependence on the target size and phantom motion parameters such as speed, amplitude, phase and frequency. The extension of the CT number distribution increased linearly with range of motion in the direction of motion. Motion frequency and phase play important role in spatial and level variations of the CT number distributions. The CT number levels of the mobile targets were smeared over a longer distribution and CT number level dropped in comparison with the distribution of stationary targets. Conclusion: The CT number distributions varied considerably with motion in CBCT. The mathematical model of CT number distribution for mobile targets developed in this work predicted well variations in the measured CT number profiles and their dependence on motion parameters. The CT number distributions spread‐out along the direction of motion and CT number level decreased. This quantitative characterization of motion artifacts on CT number distributions in CBCT may have potential application in diagnostic imaging and radiotherapy.