Med Phys
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A Fourier-based iterative reconstruction technique, termed Equally Sloped Tomography (EST), is developed in conjunction with advanced mathematical regularization to investigate radiation dose reduction in x-ray CT. The method is experimentally implemented on fan-beam CT and evaluated as a function of imaging dose on a series of image quality phantoms and anonymous pediatric patient data sets. Numerical simulation experiments are also performed to explore the extension of EST to helical cone-beam geometry. ⋯ A Fourier-based iterative method has been applied to the reconstruction of fan-bean CT data with reduced x-ray fluence. This method incorporates advantageous features in both real and Fourier space iterative schemes: using a fast and algebraically exact method to calculate forward projection, enforcing the measured data in Fourier space, and applying physical constraints and flexible regularization in real space. Our results suggest that EST can be utilized for radiation dose reduction in x-ray CT via the readily implementable technique of lowering mAs settings. Numerical experiments further indicate that EST requires less computation time than several other iterative algorithms and can, in principle, be extended to helical cone-beam geometry in combination with the ASSR method.
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Acquiring data for CT at low radiation doses has become a pressing goal. Unfortunately, the reduced data quality adversely affects the quality of the reconstructions, impeding their readability. In previous work, the authors showed how a prior regular-dose scan of the same patient can efficiently be used to mitigate low-dose artifacts. However, since a prior is not always available, the authors now extend the authors' method to use a database of images of other patients. ⋯ The authors image restoration algorithm successfully restores images to high quality when the registration is well performed and also when the priors match the target well. When the priors do not contain sufficient information, the affected image regions can only be restored to the quality achieved with conventional regularization. Hence, a sufficiently rich database is a key for successful artifact mitigation with this approach. Finally, the blockwise scheme demonstrates the potential of using small patches of images to form the database.
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3D rotational setup errors in radiotherapy are often ignored by most clinics due to inability to correct or simulate them accurately and efficiently. There are two types of rotation-related problems in a clinical setting. One is to assess the affected dose distribution in real-time if correction is not applied and the other one is to correct the rotational setup errors prior to the initiation of the treatment. Here, the authors present the analytical solutions to both problems. ⋯ They have derived the analytical solutions to a new set of table, gantry, and collimator angles for a given treatment beam configuration as a function of patient rotational errors. One solution was used to assess the dosimetric effects of an imperfect patient setup and the other one was used to correct for the setup errors without rotating the patient. Compared to the widely adopted method of rotation effect assessment by importing the rotational CT images into TPS, the equivalent beam approach is simple and accurate. The analytical solutions to correcting for rotational setup errors prior to treatment were also derived. Based on the initial clinical investigations, they firmly believe that clinically viable real-time treatment planning and adaptive radiation therapy are feasible with this novel method.