Model-based iterative reconstruction for improvement of low-contrast detectability in liver CT at reduced radiation dose: ex-vivo experience.

AIM To compare low-contrast detectability, and qualitative and quantitative image parameters on standard and reduced radiation dose abdominal CT reconstructed with filtered back projection (FBP) and model-based iterative reconstruction (MBIR). MATERIALS AND METHODS A custom built liver phantom containing 43 lesions was imaged at 120 kVp and four radiation dose levels (100% = 188 mAs, 50%, 25%, and 10%). Image noise and contrast-to-noise ratios (CNR) were assessed. Lesion detection and qualitative image analysis (five-point Likert scale with 1 = worst, 5 = best for confidence) was performed by three independent radiologists. RESULTS CNR on MBIR images was significantly higher (mean 246%, range 151-383%) and image noise was significantly lower (69%, 59-78%) than on FBP images at the same radiation dose (both p < 0.05). On MBIR 10% images, CNR (3.3 ± 0.3) was significantly higher and noise (15 ± 1HU) significantly lower than on FBP 100% images (2.5 ± 0.1; 21 ± 1 HU). On 100% images, lesion attenuation was significantly lower with MBIR than with FBP (mean difference -2 HU). Low-contrast detectability and qualitative results were similar with MBIR 50% and FBP 100%. CONCLUSION Low-contrast detectability with MBIR 50% and FBP 100% were equal. Quantitative parameters on even lower dose MBIR images are superior to 100%-dose FBP images. Some attenuation values differ significantly with MBIR compared with FBP.

[1]  Patrik Rogalla,et al.  Iterative reconstruction algorithm for CT: can radiation dose be decreased while low-contrast detectability is preserved? , 2013, Radiology.

[2]  Joon Koo Han,et al.  Assessment of a Model-Based, Iterative Reconstruction Algorithm (MBIR) Regarding Image Quality and Dose Reduction in Liver Computed Tomography , 2013, Investigative radiology.

[3]  Sana Boudabbous,et al.  Computed tomography of the chest with model-based iterative reconstruction using a radiation exposure similar to chest X-ray examination: preliminary observations , 2013, European Radiology.

[4]  Haruhiko Machida,et al.  Measurement of vascular wall attenuation: comparison of CT angiography using model-based iterative reconstruction with standard filtered back-projection algorithm CT in vitro. , 2012, European journal of radiology.

[5]  Laureline Berteloot,et al.  Model-based iterative reconstruction in pediatric chest CT: assessment of image quality in a prospective study of children with cystic fibrosis , 2013, Pediatric Radiology.

[6]  H. Alkadhi,et al.  Combining automated attenuation-based tube voltage selection and iterative reconstruction: a liver phantom study , 2014, European Radiology.

[7]  Zhou Yu,et al.  Fast Model-Based X-Ray CT Reconstruction Using Spatially Nonhomogeneous ICD Optimization , 2011, IEEE Transactions on Image Processing.

[8]  Varut Vardhanabhuti,et al.  Image Comparative Assessment Using Iterative Reconstructions: Clinical Comparison of Low-Dose Abdominal/Pelvic Computed Tomography Between Adaptive Statistical, Model-Based Iterative Reconstructions and Traditional Filtered Back Projection in 65 Patients , 2014, Investigative radiology.

[9]  Rainer Raupach,et al.  Automated Attenuation-Based Tube Potential Selection for Thoracoabdominal Computed Tomography Angiography: Improved Dose Effectiveness , 2011, Investigative radiology.

[10]  U. Schoepf,et al.  CT coronary angiography: image quality with sinogram-affirmed iterative reconstruction compared with filtered back-projection. , 2013, Clinical radiology.

[11]  Ehsan Samei,et al.  Towards task-based assessment of CT performance: System and object MTF across different reconstruction algorithms. , 2012, Medical physics.

[12]  Y. Yamashita,et al.  Low-dose abdominal CT: comparison of low tube voltage with moderate-level iterative reconstruction and standard tube voltage, low tube current with high-level iterative reconstruction. , 2013, Clinical radiology.

[13]  Jean-Baptiste Thibault,et al.  Model-based iterative reconstruction versus adaptive statistical iterative reconstruction and filtered back projection in liver 64-MDCT: focal lesion detection, lesion conspicuity, and image noise. , 2013, AJR. American journal of roentgenology.

[14]  Thomas L Toth,et al.  Low-dose CT of the abdomen: evaluation of image improvement with use of noise reduction filters pilot study. , 2003, Radiology.

[15]  D. Brenner,et al.  Computed tomography--an increasing source of radiation exposure. , 2007, The New England journal of medicine.

[16]  Masaki Katsura,et al.  Model-Based Iterative Reconstruction Technique for Ultralow-Dose Chest CT: Comparison of Pulmonary Nodule Detectability With the Adaptive Statistical Iterative Reconstruction Technique , 2013, Investigative radiology.

[17]  David H. Kim,et al.  Abdominal CT with model-based iterative reconstruction (MBIR): initial results of a prospective trial comparing ultralow-dose with standard-dose imaging. , 2012, AJR. American journal of roentgenology.

[18]  D. Newby,et al.  Iterative reconstruction and individualized automatic tube current selection reduce radiation dose while maintaining image quality in 320-multidetector computed tomography coronary angiography☆ , 2013, Clinical Radiology.

[19]  Francis R Verdun,et al.  Iterative reconstruction methods in two different MDCT scanners: physical metrics and 4-alternative forced-choice detectability experiments--a phantom approach. , 2013, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

[20]  Mannudeep K. Kalra,et al.  Comparison of Hybrid and Pure Iterative Reconstruction Techniques With Conventional Filtered Back Projection: Dose Reduction Potential in the Abdomen , 2012, Journal of computer assisted tomography.

[21]  Jan Menke,et al.  Comparison of different body size parameters for individual dose adaptation in body CT of adults. , 2005, Radiology.

[22]  Masaki Katsura,et al.  Model-based iterative reconstruction for reduction of radiation dose in abdominopelvic CT: comparison to adaptive statistical iterative reconstruction , 2013, SpringerPlus.

[23]  Varut Vardhanabhuti,et al.  Assessment of Image Quality on Effects of Varying Tube Voltage and Automatic Tube Current Modulation With Hybrid and Pure Iterative Reconstruction Techniques in Abdominal/Pelvic CT: A Phantom Study , 2013, Investigative radiology.

[24]  M. Körner,et al.  Filtered back projection, adaptive statistical iterative reconstruction, and a model-based iterative reconstruction in abdominal CT: an experimental clinical study. , 2013, Radiology.

[25]  C. McCollough,et al.  CT dose reduction and dose management tools: overview of available options. , 2006, Radiographics : a review publication of the Radiological Society of North America, Inc.

[26]  D. Volders,et al.  Model-based iterative reconstruction and adaptive statistical iterative reconstruction techniques in abdominal CT: comparison of image quality in the detection of colorectal liver metastases. , 2013, Radiology.

[27]  E. Samei,et al.  Precision of iodine quantification in hepatic CT: effects of iterative reconstruction with various imaging parameters. , 2013, AJR. American journal of roentgenology.

[28]  H Alkadhi,et al.  Effect of automatic tube voltage selection on image quality and radiation dose in abdominal CT angiography of various body sizes: a phantom study. , 2013, Clinical radiology.