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Phantom study of the impact of adaptive statistical iterative reconstruction (ASiRTM) on image quality for paediatric computed tomography  [PDF]
Angjelina Protik, Karen Thomas, Paul Babyn, Nancy L. Ford
Journal of Biomedical Science and Engineering (JBiSE) , 2012, DOI: 10.4236/jbise.2012.512A100

Quantitative analysis of image quality will be helpful for designing ASiRTM-enhanced paediatric CT protocols, balancing image quality and radiation dose. Catphan600 phantom studies were performed on a GE Discovery HD750 64-slice CT scanner. Images were reconstructed with 0% - 100% ASiRTM (tube current 150 mA, variable kVp 80 - 140) in order to determine the optimal ASiRTM-Filtered Back Projection (FBP) blend. Images reconstructed with a 50% ASiRTM-50% FBP blend were compared to FBP images (0% ASiRTM) over a wide range of kVp (80 - 140) and mA (10 - 400) values. Measurements of image noise, CT number accuracy and uniformity, spatial and contrast resolution, and low contrast detectability were performed on axial and reformatted coronal images. Improvements in CNR, low contrast detectability and radial uniformity were observed in ASiRTM images compared to FBP images. 50% ASiRTM was associated with a 26% - 30% reduction in image noise. Changes in noise texture were observed at higher %

Optimizing Radiation Dose Levels in Prospectively Electrocardiogram-Triggered Coronary Computed Tomography Angiography Using Iterative Reconstruction Techniques: A Phantom and Patient Study  [PDF]
Yang Hou, Jiahe Zheng, Yuke Wang, Mei Yu, Mani Vembar, Qiyong Guo
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0056295
Abstract: Aim To investigate the potential of reducing the radiation dose in prospectively electrocardiogram-triggered coronary computed tomography angiography (CCTA) while maintaining diagnostic image quality using an iterative reconstruction technique (IRT). Methods and Materials Prospectively-gated CCTA were first performed on a phantom using 256-slice multi-detector CT scanner at 120 kVp, with the tube output gradually reduced from 210 mAs (Group A) to 125, 105, 84, and 63 mAs (Group B–E). All scans were reconstructed using filtered back projection (FBP) algorithm and five IRT levels (L2-6), image quality (IQ) assessment was performed. Based on the IQ assessment, Group D(120 kVp, 84 mAs) reconstructed with L5 was found to provide IQ comparable to that of Group A with FBP. In the patient study, 21 patients underwent CCTA using 120 kV, 210 mAs with FBP reconstruction (Group 1) followed by 36 patients scanned with 120 kV, 84 mAs with IRT L5 (Group 2). Subjective and objective IQ and effective radiation dose were compared between two groups. Results In the phantom scans, there were no significant differences in image noise, contrast-to-noise ratio (CNR) and modulation transfer function (MTF) curves between Group A and the 84 mAs, 63 mAs groups (Groups D and E). Group D (120 kV, 84 mAs and L5) provided an optimum balance, producing equivalent image quality to Group A, at the lowest possible radiation dose. In the patient study, there were no significant difference in image noise, signal-to-noise ratio (SNR) and CNR between Group 1 and Group 2 (p = 0.71, 0.31, 0.5, respectively). The effective radiation dose in Group 2 was 1.21±0.14 mSv compared to 3.20±0.58 mSv (Group 1), reflecting dose savings of 62.5% (p<0.05). Conclusion iterative reconstruction technique used in prospectively ECG-triggered 256-slice coronary CTA can provide radiation dose reductions of up to 62.5% with acceptable image quality.
X-Ray Dose Reduction in Abdominal Computed Tomography Using Advanced Iterative Reconstruction Algorithms  [PDF]
Peigang Ning, Shaocheng Zhu, Dapeng Shi, Ying Guo, Minghua Sun
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0092568
Abstract: Objective This work aims to explore the effects of adaptive statistical iterative reconstruction (ASiR) and model-based iterative reconstruction (MBIR) algorithms in reducing computed tomography (CT) radiation dosages in abdominal imaging. Methods CT scans on a standard male phantom were performed at different tube currents. Images at the different tube currents were reconstructed with the filtered back-projection (FBP), 50% ASiR and MBIR algorithms and compared. The CT value, image noise and contrast-to-noise ratios (CNRs) of the reconstructed abdominal images were measured. Volumetric CT dose indexes (CTDIvol) were recorded. Results At different tube currents, 50% ASiR and MBIR significantly reduced image noise and increased the CNR when compared with FBP. The minimal tube current values required by FBP, 50% ASiR, and MBIR to achieve acceptable image quality using this phantom were 200, 140, and 80 mA, respectively. At the identical image quality, 50% ASiR and MBIR reduced the radiation dose by 35.9% and 59.9% respectively when compared with FBP. Conclusions Advanced iterative reconstruction techniques are able to reduce image noise and increase image CNRs. Compared with FBP, 50% ASiR and MBIR reduced radiation doses by 35.9% and 59.9%, respectively.
Radiation dose in paediatric computed tomography: risks and benefits
GI Ogbole
Annals of Ibadan Postgraduate Medicine , 2010,
Abstract: Computed tomography (CT) is a powerful tool for the accurate and effective diagnosis and treatment of a variety of conditions because it allows high-resolution three-dimensional images to be acquired very quickly. However as the number of CT procedures performed globally have continued to increase; with growing concerns about patient protection. Currently, no system is in place to track patient doses and the lifetime cumulative dose from medical sources. The widespread use of CT even in developing countries has raised questions regarding the possible threat to public health especially in children. The best available risk estimates suggest that paediatric CT will result in significantly increased lifetime radiation risk over adult CT. Studies have shown that lower milliampere-second (mAs) settings can be used for children without significant loss of information. Although the risk–benefit balance is still strongly tilted toward benefit, there is still need for caution. Furthermore since the frequency of paediatric CT examinations is rapidly increasing, and estimates suggest that quantitative lifetime radiation risks for children are not negligible, efforts should be made toward more active reduction of CT exposure settings in paediatric patients. This article hopes to address this concerns and draw attention to the fact that children are not ‘small adults ’ and should therefore be treated differently.
A Low-Cost Fiducial Reference Phantom for Computed Tomography
Levine, Zachary H.,Grantham, Steven,Sawyer, Daniel S.,Reeves, Anthony P.
Journal of Research of the National Institute of Standards and Technology , 2008,
Abstract: To detect the growth in lesions, it is necessary to ensure that the apparent changes in size are above the noise floor of the system. By introducing a fiducial reference, it may be possible to detect smaller changes in lesion size more reliably. We suspend three precision spheres with a precision structure built from pieces from a popular children's building toy. We measure the distances between the centroids of the structures three ways; namely, with a high-precision mechanical method, micro computerized tomography, and medical computerized tomography. The three methods are in agreement, and also agree with the design values for the structure. It is also possible to pick a threshold so that the three spheres have their nominal volumes in the medical computerized tomography images. The use of volumetric measures allows the determination of lengths to much less than the voxel size using materials which have x-ray properties within the range of the human body. A suitable structure may be built with a very small parts cost.
The Effects of Computed Tomography with Iterative Reconstruction on Solid Pulmonary Nodule Volume Quantification  [PDF]
Martin J. Willemink, Jaap Borstlap, Richard A. P. Takx, Arnold M. R. Schilham, Tim Leiner, Ricardo P. J. Budde, Pim A. de Jong
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0058053
Abstract: Background The objectives of this study were to evaluate the influence of iterative reconstruction (IR) on pulmonary nodule volumetry with chest computed tomography (CT). Methods Twenty patients (12 women and 8 men, mean age 61.9, range 32–87) underwent evaluation of pulmonary nodules with a 64-slice CT-scanner. Data were reconstructed using filtered back projection (FBP) and IR (Philips Healthcare, iDose4-levels 2, 4 and 6) at similar radiation dose. Volumetric nodule measurements were performed with semi-automatic software on thin slice reconstructions. Only solid pulmonary nodules were measured, no additional selection criteria were used for the nature of nodules. For intra-observer and inter-observer variability, measurements were performed once by one observer and twice by another observer. Algorithms were compared using the concordance correlation-coefficient (pc) and Friedman-test, and post-hoc analysis with the Wilcoxon-signed ranks-test with Bonferroni-correction (significance-level p<0.017). Results Seventy-eight nodules were present including 56 small nodules (volume<200 mm3, diameter<8 mm) and 22 large nodules (volume≥200 mm3, diameter≥8 mm). No significant differences in measured pulmonary nodule volumes between FBP, iDose4-levels 2, 4 and 6 were found in both small nodules and large nodules. FBP and iDose4-levels 2, 4 and 6 were correlated with pc-values of 0.98 or higher for both small and large nodules. Pc-values of intra-observer and inter-observer variability were 0.98 or higher. Conclusions Measurements of solid pulmonary nodule volume measured with standard-FBP were comparable with IR, regardless of the IR-level and no significant differences between measured volumes of both small and large solid nodules were found.
AIR: fused Analytical and Iterative Reconstruction method for computed tomography  [PDF]
Liu Yang,Yu Gao,Sharon X. Qi,Hao Gao
Physics , 2013,
Abstract: Purpose: CT image reconstruction techniques have two major categories: analytical reconstruction (AR) method and iterative reconstruction (IR) method. AR reconstructs images through analytical formulas, such as filtered backprojection (FBP) in 2D and Feldkamp-Davis-Kress (FDK) method in 3D, which can be either mathematically exact or approximate. On the other hand, IR is often based on the discrete forward model of X-ray transform and formulated as a minimization problem with some appropriate image regularization method, so that the reconstructed image corresponds to the minimizer of the optimization problem. This work is to investigate the fused analytical and iterative reconstruction (AIR) method. Methods: Based on IR with L1-type image regularization, AIR is formulated with a AR-specific preconditioner in the data fidelity term, which results in the minimal change of the solution algorithm that replaces the adjoint X-ray transform by the filtered X-ray transform. As a proof-of-concept 2D example of AIR, FBP is incorporated into tensor framelet (TF) regularization based IR, and the formulated AIR minimization problem is then solved through split Bregman method with GPU-accelerated X-ray transform and filtered adjoint X-ray transform. Conclusion: AIR, the fused Analytical and Iterative Reconstruction method, is proposed with a proof-of-concept 2D example to synergize FBP and TF-regularized IR, with improved image resolution and contrast for experimental data. The potential impact of AIR is that it offers a general framework to develop various AR enhanced IR methods, when neither AR nor IR alone is sufficient.
An iterative algorithm for computed tomography image reconstruction from limited-angle projections  [PDF]
Yuli Sun,Jinxu Tao,Conggui Liu
Computer Science , 2013,
Abstract: In application of tomography imaging, limited-angle problem is a quite practical and important issue. In this paper, an iterative reprojection-reconstruction (IRR) algorithm using a modified Papoulis-Gerchberg (PG) iterative scheme is developed for reconstruction from limited-angle projections which contain noise. The proposed algorithm has two iterative update processes, one is the extrapolation of unknown data, and the other is the modification of the known noisy observation data. And the algorithm introduces scaling factors to control the two processes, respectively. The convergence of the algorithm is guaranteed, and the method of choosing the scaling factors is given with energy constraints. The simulation result demonstrates our conclusions and indicates that the algorithm proposed in this paper can obviously improve the reconstruction quality.
Evaluation of Algebraic Iterative Image Reconstruction Methods for Tetrahedron Beam Computed Tomography Systems  [PDF]
Joshua Kim,Huaiqun Guan,David Gersten,Tiezhi Zhang
International Journal of Biomedical Imaging , 2013, DOI: 10.1155/2013/609704
Abstract: Tetrahedron beam computed tomography (TBCT) performs volumetric imaging using a stack of fan beams generated by a multiple pixel X-ray source. While the TBCT system was designed to overcome the scatter and detector issues faced by cone beam computed tomography (CBCT), it still suffers the same large cone angle artifacts as CBCT due to the use of approximate reconstruction algorithms. It has been shown that iterative reconstruction algorithms are better able to model irregular system geometries and that algebraic iterative algorithms in particular have been able to reduce cone artifacts appearing at large cone angles. In this paper, the SART algorithm is modified for the use with the different TBCT geometries and is tested using both simulated projection data and data acquired using the TBCT benchtop system. The modified SART reconstruction algorithms were able to mitigate the effects of using data generated at large cone angles and were also able to reconstruct CT images without the introduction of artifacts due to either the longitudinal or transverse truncation in the data sets. Algebraic iterative reconstruction can be especially useful for dual-source dual-detector TBCT, wherein the cone angle is the largest in the center of the field of view. 1. Introduction Image-guided radiation therapy (IGRT) is essential to ensure proper dose delivery to the target while sparing the surrounding tissue [1, 2]. Cone beam CT (CBCT) is a popular online imaging modality used for LINAC-based IGRT [3, 4]. Although CBCT is convenient to use, the performance of CBCT systems is less than ideal. The image quality for the CBCT is significantly degraded due to excessive scattered photons [5–8] as well as suboptimal performance of the flat panel detector [9]. These issues limit the use of CBCT for certain advanced radiation therapy techniques such as online adaptive radiotherapy [8, 10]. It is also well known that at large cone angles, there are artifacts caused by using approximate reconstruction methods that appear in CBCT reconstructions [11], but this issue has largely been ignored in IGRT because the scatter and detector issues are the dominant factors in the degradation of CBCT image quality. Tetrahedron beam computed tomography (TBCT) is a novel volumetric CT modality that overcomes the scatter and detector problems of CBCT [12, 13]. A TBCT system is composed of a minimum of one linear source array with one linear detector array positioned opposite and orthogonal to it. In TBCT, scattered photons are largely rejected due to the fan-beam geometry of the system. A TBCT
Adapted sampling for 3D X-ray computed tomography  [PDF]
Anthony Cazasnoves,Fanny Buyens,Sylvie Sevestre
Computer Science , 2015,
Abstract: In this paper, we introduce a method to build an adapted mesh representation of a 3D object for X-Ray tomography reconstruction. Using this representation, we provide means to reduce the computational cost of reconstruction by way of iterative algorithms. The adapted sampling of the reconstruction space is directly obtained from the projection dataset and prior to any reconstruction. It is built following two stages : firstly, 2D structural information is extracted from the projection images and is secondly merged in 3D to obtain a 3D pointcloud sampling the interfaces of the object. A relevant mesh is then built from this cloud by way of tetrahedralization. Critical parameters selections have been automatized through a statistical framework, thus avoiding dependence on users expertise. Applying this approach on geometrical shapes and on a 3D Shepp-Logan phantom, we show the relevance of such a sampling - obtained in a few seconds - and the drastic decrease in cells number to be estimated during reconstruction when compared to the usual regular voxel lattice. A first iterative reconstruction of the Shepp-Logan using this kind of sampling shows the relevant advantages in terms of low dose or sparse acquisition sampling contexts. The method can also prove useful for other applications such as finite element method computations.
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