Literature DB >> 21452727

The effects of compensator and imaging geometry on the distribution of x-ray scatter in CBCT.

G J Bootsma1, F Verhaegen, D A Jaffray.   

Abstract

PURPOSE: X-ray scatter contributes significantly to image degradation in cone-beam CT (CBCT) reconstructed images in the form of CT number inaccuracy image artifacts and loss of contrast. The need for an understanding of the relationship between the scatter distribution and common imaging parameters (cone angle, air gap, filtration, object size) is an essential element to developing methods for efficiently correcting for the effects of scatter in CBCT. The first objective of this study is to validate the scatter distributions calculated using a CBCT Monte Carlo (MC) model against measured scatter estimates. The second objective is to use the CBCT MC model to investigate the effects of common imaging parameters and bowtie compensators on the resulting scatter distribution.
METHODS: This investigation employs the use of a CBCT MC model, developed using the EGSnrc code, to simulate the primary and scatter fluence arriving at the detector. The simulation is validated against projection images, scatter-to-open field ratio (SOR), and scatter-to-primary ratio (SPR) measurements taken using a bench-top CBCT system. The CBCT MC model is used to simulate the scatter distribution arriving at the detector for different cone angles {1.4 degrees, 2.8 degrees, 5.7 degrees, and 11.3 degrees}, source-to-axis distances (SADs) {50, 75 and 100 cm}, and axis-to-detector distances (ADDs) {9, 18, 30, 44, 56 cm} for both a 16.4 and 30.6 cm diameter water cylinder. The effects of different bowtie filters are also simulated using the CBCT MC model for the aforementioned cylinder sizes.
RESULTS: Profiles of the simulated and measured projection images agree within 6%. The measurements of the SOR and SPR, taken using beam stop techniques, show good agreement with the simulated results. Limitations of current beam stop techniques in estimating scatter profiles of objects with varying thickness are also demonstrated. A functional relationship between scatter (SOR, SPR) and air gap, cone angle is reported. The bowtie filter was found to have the beneficial effect of decreasing the magnitude of scatter in the projection images (SPR decreased by 56%) as well as altering the spatial distribution of the scatter.
CONCLUSIONS: The CBCT MC model accurately simulates scatter and primary fluences in the CBCT imaging components and geometry. The CBCT MC model provides a useful tool in investigating the effects of varying CBCT imaging parameters on the scatter distribution. Increasing the air gap, decreasing the cone angle, and the use of bowtie filtration were all found to be effective ways to minimize scatter in CBCT. The bowtie filter was particularly effective in both minimizing the magnitude and modifying the spatial distribution of the scattered photons. This observation directs further research in optimizing bowtie filter design in an effort to minimize scatter induced artifacts.

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Year:  2011        PMID: 21452727     DOI: 10.1118/1.3539575

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


  6 in total

1.  Bowtie filtration for dedicated cone beam CT of the head and neck: a simulation study.

Authors:  G Zhang; N Marshall; R Jacobs; Q Liu; H Bosmans
Journal:  Br J Radiol       Date:  2013-05-31       Impact factor: 3.039

2.  Characterization of scatter magnitude and distribution in dedicated breast computed tomography with bowtie filters.

Authors:  Kimberly Kontson; Robert J Jennings
Journal:  J Med Imaging (Bellingham)       Date:  2014-12-18

3.  Relationship between x-ray illumination field size and flat field intensity and its impacts on x-ray imaging.

Authors:  Xue Dong; Tianye Niu; Xun Jia; Lei Zhu
Journal:  Med Phys       Date:  2012-10       Impact factor: 4.071

4.  Transmission characteristics of a two dimensional antiscatter grid prototype for CBCT.

Authors:  Cem Altunbas; Brian Kavanagh; Timur Alexeev; Moyed Miften
Journal:  Med Phys       Date:  2017-06-16       Impact factor: 4.071

5.  Shading artifact correction in breast CT using an interleaved deep learning segmentation and maximum-likelihood polynomial fitting approach.

Authors:  Peymon Ghazi; Andrew M Hernandez; Craig Abbey; Kai Yang; John M Boone
Journal:  Med Phys       Date:  2019-06-23       Impact factor: 4.071

6.  Implementation of an efficient Monte Carlo calculation for CBCT scatter correction: phantom study.

Authors:  Peter G F Watson; Ernesto Mainegra-Hing; Nada Tomic; Jan Seuntjens
Journal:  J Appl Clin Med Phys       Date:  2015-07-08       Impact factor: 2.102

  6 in total

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