title: Estimation of Radiation Dose in CT Based on Projection Data.
abstract: Managing and optimizing radiation dose has become a core problem for the CT community. As a fundamental step for dose optimization, accurate and computationally efficient dose estimates are crucial. The purpose of this study was to devise a computationally efficient projection-based dose metric. The absorbed energy and object mass were individually modeled using the projection data. The absorbed energy was estimated using the difference between intensity of the primary photon and the exit photon. The mass was estimated using the volume under the attenuation profile. The feasibility of the approach was evaluated across phantoms with a broad size range, various kVp settings, and two bowtie filters, using a simulation tool, the Computer Assisted Tomography SIMulator (CATSIM) software. The accuracy of projection-based dose estimation was validated against Monte Carlo (MC) simulations. The relationship between projection-based dose metric and MC dose estimate was evaluated using regression models. The projection-based dose metric showed a strong correlation with Monte Carlo dose estimates (R (2) > 0.94). The prediction errors for the projection-based dose metric were all below 15 %. This study demonstrated the feasibility of computationally efficient dose estimation requiring only the projection data.
authors.affiliation: Department of Biomedical Engineering, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, 2424 Erwin Road, Suite 302, Durham, NC, 27705, USA.
authors.forename: Xiaoyu
authors.initials: X
authors.lastname: Tian
authors.affiliation: CT Systems and Applications Laboratory, GE Global Research, Niskayuna, NY, 12309, USA.
authors.forename: Zhye
authors.initials: Z
authors.lastname: Yin
authors.affiliation: CT Systems and Applications Laboratory, GE Global Research, Niskayuna, NY, 12309, USA.
authors.forename: Bruno
authors.initials: B
authors.lastname: De Man
authors.affiliation: Department of Biomedical Engineering, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, 2424 Erwin Road, Suite 302, Durham, NC, 27705, USA. samei@duke.edu.|Medical Physics Graduate Program, Departments of Radiology, Electrical and Computer Engineering, and Physics, Duke University Medical Center, Durham, NC, 27705, USA. samei@duke.edu.
authors.forename: Ehsan
authors.initials: E
authors.lastname: Samei
mesh_terms: D003198:Computer Simulation; D006801:Humans; D009010:Monte Carlo Method; D019047:Phantoms, Imaging; D011829:Radiation Dosage; D011874:Radiometry / Q000379:methods; D012984:Software; D014057:Tomography, X-Ray Computed
keywords: CT; Computed tomography; Patient-specific dosimetry