Improvement of metallic artifacts in computed tomography in the absence of artifact reduction algorithms for spinal treatment planning applications
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Date
2020-09
Journal Title
Journal ISSN
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Publisher
Wolters Kluwer India Pvt. Ltd.
Abstract
Aim of Study: The goal of this research was to investigate if application of optimized imaging parameters, recommended in literature, would be effective in producing the image quality required for treatment planning of spinal radiation fields with metallic implants. Materials and Methods: CT images from an anthropomorphic torso phantom with and without spinal implants were acquired using different imaging protocols: raising kVp and mAs, reducing the pitch and applying an extended CT scale (ECTS) technique. Profiles of CT number (CT#) were produced using DICOM data of each image. The effect of artifact on dose calculation accuracy was investigated using the image data in the absence of implant as a reference and the recommended electron density tolerance levels (Δρe). Results: Raising the kVp was the only method that produced improvement to some degree in CT# in artifact regions. Application of ECTS improved CT# values only for metal. Conclusions: Although raising the kVp was effective in reducing metallic artifact, the significance of this effect on Δρe values in corrected images depends on the required tolerance for treatment planning dose calculation accuracy. ECTS method was only successful in correcting the CT number range in the metal. Although, application of ECTS method did not have any effect on artifact regions, its use is necessary in order to improve delineation of metal and accuracy of attenuation calculations in metal, provided that the treatment planning system can use an extended CT# calibration curve. Also, for Monte Carlo calculations using patient's images, ECTS-post-processed-CT images improve dose calculation accuracy for impure metals
Description
Keywords
Computed tomography image artifact, extended computed tomography scale, spinal metallic implant, treatment planning
Citation
Alinejad Marjan, Pourmoghaddas Amir, Amouheidari Alireza, Shokrani Parvaneh. Improvement of metallic artifacts in computed tomography in the absence of artifact reduction algorithms for spinal treatment planning applications. Journal of Cancer Research and Therapeutics. 2020 Sep; 16(4): 878-883