Computer Assisted Surgery | 2019

Quantitative assessment of three vendor’s metal artifact reduction techniques for CT imaging using a customized phantom

 
 
 
 
 

Abstract


Abstract A metal implant was placed in an acrylic phantom to enable quantitative analysis of the metal artifact reduction techniques used in computed tomography (CT) scanners from three manufacturers. Two titanium rods were placed in a groove in a cylindrical phantom made by acrylic, after which the groove was filled with water. The phantom was scanned using three CT scanners (Toshiba, GE, Siemens) under the abdomen CT setting. CT number accuracy, contrast-to-noise ratio, area of the metal rods in the images, and fraction of affected pixel area of water were measured using ImageJ. Different iterative reconstruction, dual energy, and metal artifact reduction techniques were compared within three vendors. The highest contrast-to-noise ratio of three scanners were 85.7\u2009±\u20098.4 (Toshiba), 85.9\u2009±\u200911.7 (GE), and 55.0\u2009±\u200914.8 (Siemens); and the most correct results of metal area were 157.1\u2009±\u20091.4\u2009mm2 (Toshiba), 155.0\u2009±\u20091.0 (GE), and 170.6\u2009±\u20095.3 (Siemens). The fraction of affected pixel area obtained using single-energy metal artifact reduction of Toshiba scanner was 2.2% ± 0.7%, which is more favorable than 4.1% ± 0.7% obtained using metal artifact reduction software of GE scanner (p\u2009=\u20090.002). Among all quantitative results, the estimations with fraction of affected pixel areas matched the effect of metal artifact reduction in the actual images. Therefore, the single-energy metal artifact reduction technique of Toshiba scanner had a desirable effect. The metal artifact reduction software of GE scanner effectively reduced the effect of metal artifacts; however, it underestimated the size of the metal rods. The monoenergetic and dual energy composition techniques of Siemens scanner could not effectively reduce metal artifacts.

Volume 24
Pages 34 - 42
DOI 10.1080/24699322.2019.1649075
Language English
Journal Computer Assisted Surgery

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