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Radiography (Lond) ; 29(4): 752-759, 2023 07.
Article in English | MEDLINE | ID: mdl-37229844

ABSTRACT

INTRODUCTION: This study investigated the impact of high matrix image reconstruction in combination with different reconstruction kernels and levels of iterative reconstructions on image quality in chest CT. METHODS: An anthropomorphic chest phantom (Kyoto Kagaku Co., Ltd., Kyoto, Japan), and a Catphan® 600 (The Phantom Laboratory, Greenwich, NY, USA) phantom were scanned using a dual source scanner. Standard institutional protocol with 512 × 512 matrix was used as a reference. Reconstructions were performed for 768 × 768 and 1024 × 1024 matrices and all possible combinations of three different kernels and five levels of iterative reconstructions were included. Signal difference to noise ratio (SdNR) and line pairs per cm (lp/cm) were manually measured. A Linear regression model was applied for objective image analysis (SdNR) and inter-and intra-reader agreement was given as Cohen's kappa for the visual image assessment. RESULTS: Matrix size did not have a significant impact on SdNR (p = 0.595). Kernel (p = 0.014) and ADMIRE level (p = 0.001) had a statistically significant impact on SdNR. The spatial resolution ranged from 7 lp/cm to 9 lp/cm. The highest spatial resolution was achieved using kernel Br64 and ADMIRE 1, 2 and 3 in both 768- and 1024-matrices, and with Br59 with ADMIRE 2 and 4 and 768-matrix, all visualizing 9 lp/cm. Both readers scored kernel Br59 highest, and the scoring increased with increasing levels of Iterative Reconstruction. CONCLUSION: Matrix size did not influence image quality, however, the choice of kernel and degree of IR had an impact on objective and visual image quality in 768 - and 1024-matrices, suggesting that increased degree of IR may improve diagnostic image quality in chest CT. IMPLICATIONS FOR PRACTICE: Image quality in CT of the lung may be improved by increasing the level of IR.


Subject(s)
Algorithms , Tomography, X-Ray Computed , Humans , Tomography, X-Ray Computed/methods , Phantoms, Imaging , Thorax , Image Processing, Computer-Assisted/methods
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