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-tonoise 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 ± 8.4 (Toshiba), 85.9 ± 11.7 (GE), and 55.0 ± 14.8 (Siemens); and the most correct results of metal area were 157.1 ± 1.4 mm 2 (Toshiba), 155.0 ± 1.0 (GE), and 170.6 ± 5.3 (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 ¼ 0.002). 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.

BACKGROUND: Metal artifact reduction (MAR) techniques can improve metal artifacts of computed tomography (CT) images. OBJECTIVE: This work focused on conducting a quantitative analysis to compare the effectiveness of four commercial MAR techniques on three types of metal implants (hip implant, spinal implant, and dental filling) with a self-made acrylic phantom. METHODS: A cylindrical phantom was made from acrylic with a groove in the middle, and then three types of metal implants were placed in the groove. The phantom was scanned by four CT scanners and four commercialized MAR techniques were used to analyze the images. The techniques used were single-energy metal artifact reduction (SEMAR, Canon), smart metal artifact reduction software (Smart-MAR, GE), iterative metal artifact reduction (IMAR, Siemens), and metal artifact reduction for orthopedic implants (OMAR, Philips). Quantitative analysis methods included objective and subjective analysis. RESULTS: The expected value of SEMAR, Smart-MAR, IMAR, and OMAR were 36.6, 37.8, 5.0, and 2.3, respectively. SEMAR and Smart-MAR achieved optimal results. CONCLUSION: This study successfully evaluated the effects of four commercial MAR techniques on three types of metal implants in a phantom. All MAR techniques effectively reduced metal artifacts, but the effect was not significant with dental fillings due to high-density material.