Baiyu Chen1, Olav Christianson2, Joshua M Wilson2, Ehsan Samei3. 1. Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705 and Carl E. Ravin Advanced Imaging Laboratories, Duke University, Durham, North Carolina 27705. 2. Carl E. Ravin Advanced Imaging Laboratories, Duke University, Durham, North Carolina 27705 and Department of Radiology, Duke University, Durham, North Carolina 27705. 3. Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705; Carl E. Ravin Advanced Imaging Laboratories, Duke University, Durham, North Carolina 27705; Department of Radiology, Duke University, Durham, North Carolina 27705; and Departments of Physics, Biomedical Engineering, and Electronic and Computer Engineering, Duke University, Durham, North Carolina 27705.
Abstract
PURPOSE: For nonlinear iterative image reconstructions (IR), the computed tomography (CT) noise and resolution properties can depend on the specific imaging conditions, such as lesion contrast and image noise level. Therefore, it is imperative to develop a reliable method to measure the noise and resolution properties under clinically relevant conditions. This study aimed to develop a robust methodology to measure the three-dimensional CT noise and resolution properties under such conditions and to provide guidelines to achieve desirable levels of accuracy and precision. METHODS: The methodology was developed based on a previously reported CT image quality phantom. In this methodology, CT noise properties are measured in the uniform region of the phantom in terms of a task-based 3D noise-power spectrum (NPStask). The in-plane resolution properties are measured in terms of the task transfer function (TTF) by applying a radial edge technique to the rod inserts in the phantom. The z-direction resolution properties are measured from a supplemental phantom, also in terms of the TTF. To account for the possible nonlinearity of IR, the NPStask is measured with respect to the noise magnitude, and the TTF with respect to noise magnitude and edge contrast. To determine the accuracy and precision of the methodology, images of known noise and resolution properties were simulated. The NPStask and TTF were measured on the simulated images and compared to the truth, with criteria established to achieve NPStask and TTF measurements with <10% error. To demonstrate the utility of this methodology, measurements were performed on a commercial CT system using five dose levels, two slice thicknesses, and three reconstruction algorithms (filtered backprojection, FBP; iterative reconstruction in imaging space, IRIS; and sinogram affirmed iterative reconstruction with strengths of 5, SAFIRE5). RESULTS: To achieve NPStask measurements with <10% error, the number of regions of interest needed to be greater than 65. To achieve TTF measurements with <10% error, the contrast-to-noise ratio of the edge needed to be ≥15, achievable by averaging multiple slices across the same edge. The NPStask measured on a commercial CT system showed IR's reduced noise (IRIS, 30% and SAFIRE5, 55%) and "waxier" texture (peak frequencies: FBP, 0.25 mm(-1); IRIS, 0.23 mm(-1); and SAFIRE5, 0.16 mm(-1)). The TTF measured within the axial plane showed improved in-plane resolution with SAFIRE5 at the TTF 50% frequency, f50 (FBP, 0.36-0.41 mm(-1); SAFIRE5, 0.37-0.46 mm(-1)). The TTF measured along the axial direction showed improved z-direction resolution with thinner slice thickness (f50: 0.6 mm, 0.35-0.79 mm(-1); 1.5 mm, 0.22-0.3 mm(-1)) and with SAFIRE5 (f50: FBP, 0.35-0.52 mm(-1); SAFIRE5, 0.42-0.79 mm(-1)). Both in-plane and z-direction resolution of SAFIRE5 showed strong dependency on contrast, reflecting SAFIRE5's nonlinearity. CONCLUSIONS: A methodology was developed to measure three-dimensional CT noise and resolution properties for iterative reconstruction, especially at challenging measurement conditions with low contrast and high image noise. The methodology also demonstrated its utility for evaluating commercial CT systems.
PURPOSE: For nonlinear iterative image reconstructions (IR), the computed tomography (CT) noise and resolution properties can depend on the specific imaging conditions, such as lesion contrast and image noise level. Therefore, it is imperative to develop a reliable method to measure the noise and resolution properties under clinically relevant conditions. This study aimed to develop a robust methodology to measure the three-dimensional CT noise and resolution properties under such conditions and to provide guidelines to achieve desirable levels of accuracy and precision. METHODS: The methodology was developed based on a previously reported CT image quality phantom. In this methodology, CT noise properties are measured in the uniform region of the phantom in terms of a task-based 3D noise-power spectrum (NPStask). The in-plane resolution properties are measured in terms of the task transfer function (TTF) by applying a radial edge technique to the rod inserts in the phantom. The z-direction resolution properties are measured from a supplemental phantom, also in terms of the TTF. To account for the possible nonlinearity of IR, the NPStask is measured with respect to the noise magnitude, and the TTF with respect to noise magnitude and edge contrast. To determine the accuracy and precision of the methodology, images of known noise and resolution properties were simulated. The NPStask and TTF were measured on the simulated images and compared to the truth, with criteria established to achieve NPStask and TTF measurements with <10% error. To demonstrate the utility of this methodology, measurements were performed on a commercial CT system using five dose levels, two slice thicknesses, and three reconstruction algorithms (filtered backprojection, FBP; iterative reconstruction in imaging space, IRIS; and sinogram affirmed iterative reconstruction with strengths of 5, SAFIRE5). RESULTS: To achieve NPStask measurements with <10% error, the number of regions of interest needed to be greater than 65. To achieve TTF measurements with <10% error, the contrast-to-noise ratio of the edge needed to be ≥15, achievable by averaging multiple slices across the same edge. The NPStask measured on a commercial CT system showed IR's reduced noise (IRIS, 30% and SAFIRE5, 55%) and "waxier" texture (peak frequencies: FBP, 0.25 mm(-1); IRIS, 0.23 mm(-1); and SAFIRE5, 0.16 mm(-1)). The TTF measured within the axial plane showed improved in-plane resolution with SAFIRE5 at the TTF 50% frequency, f50 (FBP, 0.36-0.41 mm(-1); SAFIRE5, 0.37-0.46 mm(-1)). The TTF measured along the axial direction showed improved z-direction resolution with thinner slice thickness (f50: 0.6 mm, 0.35-0.79 mm(-1); 1.5 mm, 0.22-0.3 mm(-1)) and with SAFIRE5 (f50: FBP, 0.35-0.52 mm(-1); SAFIRE5, 0.42-0.79 mm(-1)). Both in-plane and z-direction resolution of SAFIRE5 showed strong dependency on contrast, reflecting SAFIRE5's nonlinearity. CONCLUSIONS: A methodology was developed to measure three-dimensional CT noise and resolution properties for iterative reconstruction, especially at challenging measurement conditions with low contrast and high image noise. The methodology also demonstrated its utility for evaluating commercial CT systems.
Authors: Daniel Gomez-Cardona; Juan Pablo Cruz-Bastida; Ke Li; Adam Budde; Jiang Hsieh; Guang-Hong Chen Journal: Med Phys Date: 2016-08 Impact factor: 4.071
Authors: Baiyu Chen; Lifeng Yu; Shuai Leng; James Kofler; Christopher Favazza; Thomas Vrieze; Cynthia McCollough Journal: Proc SPIE Int Soc Opt Eng Date: 2016-03-30
Authors: Ke Li; Daniel Gomez-Cardona; Jiang Hsieh; Meghan G Lubner; Perry J Pickhardt; Guang-Hong Chen Journal: Med Phys Date: 2015-09 Impact factor: 4.071