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Measurement of vascular wall attenuation: Comparison of CT angiography using model-based iterative reconstruction with standard filtered back-projection algorithm CT in vitro
- Source :
- European Journal of Radiology. 81:3348-3353
- Publication Year :
- 2012
- Publisher :
- Elsevier BV, 2012.
-
Abstract
- Objectives To compare the performance of model-based iterative reconstruction (MBIR) with that of standard filtered back projection (FBP) for measuring vascular wall attenuation. Study design After subjecting 9 vascular models (actual attenuation value of wall, 89 HU) with wall thickness of 0.5, 1.0, or 1.5 mm that we filled with contrast material of 275, 396, or 542 HU to scanning using 64-detector computed tomography (CT), we reconstructed images using MBIR and FBP (Bone, Detail kernels) and measured wall attenuation at the center of the wall for each model. We performed attenuation measurements for each model and additional supportive measurements by a differentiation curve. We analyzed statistics using analyzes of variance with repeated measures. Results Using the Bone kernel, standard deviation of the measurement exceeded 30 HU in most conditions. In measurements at the wall center, the attenuation values obtained using MBIR were comparable to or significantly closer to the actual wall attenuation than those acquired using Detail kernel. Using differentiation curves, we could measure attenuation for models with walls of 1.0- or 1.5-mm thickness using MBIR but only those of 1.5-mm thickness using Detail kernel. We detected no significant differences among the attenuation values of the vascular walls of either thickness (MBIR, P = 0.1606) or among the 3 densities of intravascular contrast material (MBIR, P = 0.8185; Detail kernel, P = 0.0802). Conclusions Compared with FBP, MBIR reduces both reconstruction blur and image noise simultaneously, facilitates recognition of vascular wall boundaries, and can improve accuracy in measuring wall attenuation.
- Subjects :
- media_common.quotation_subject
Iterative reconstruction
Sensitivity and Specificity
Standard deviation
Image noise
Humans
Contrast (vision)
Medicine
Radiology, Nuclear Medicine and imaging
media_common
Radon transform
Phantoms, Imaging
business.industry
Attenuation
Angiography
Reproducibility of Results
General Medicine
Radiographic Image Enhancement
Kernel (statistics)
Radiographic Image Interpretation, Computer-Assisted
Tomography, X-Ray Computed
Nuclear medicine
business
Algorithms
Biomedical engineering
Subjects
Details
- ISSN :
- 0720048X
- Volume :
- 81
- Database :
- OpenAIRE
- Journal :
- European Journal of Radiology
- Accession number :
- edsair.doi.dedup.....23e1f15200a67a6b5510eff36f71351f
- Full Text :
- https://doi.org/10.1016/j.ejrad.2012.02.009