OBJECTIVE: The purpose of this study was to examine the effects of computed tomographic (CT) parameters on metal artifact reduction in multidetector CT (MDCT) using a quantitative 3-dimensional (3D) measurement of the metal artifact volume. METHODS: A steel-based plate and screw were implanted in the femora of 3 porcine thigh specimens. The specimens were examined using 16-slice MDCT with 7 different combinations of acquisition parameters that consisted of kilovolt (peak) (kV[p]) and effective milliampere-seconds (mAs): 120 and 100; 120 and 300; 120 and 500; 120 and 1000; 140 and 100; 140 and 300; and 140 and 500 under a detector collimation of 0.75 mm and a beam pitch of 0.45. The axial image reconstructions were performed with 4 different settings: 0.75-, 1-, 2-, and 2-mm slice thickness reconstruction under an extended CT scale. At the levels of all 14 screws in the 3 femora, the metal artifact volumes in various combinations of acquisition and reconstruction settings were measured using personal computer-based 3D imaging software and were compared with each other. RESULTS: The presence of a metal artifact was significantly reduced by increasing the kilovoltage and by decreasing the reconstruction thickness (P < 0.05; 2-way analysis of variance test). Neither increasing the effective mAs nor applying extended CT scale reduced the presence of the metal artifact significantly (P = 0.599 and P = 0.474, respectively). Compared with the metal artifact volume at 120 kV(p) and 100 mAs and a 2-mm slice thickness as a reference setting, the metal artifact reduction rate was 22% by increasing kilovoltage to 140, whereas only 11% by increasing mAs to 1000. CONCLUSIONS: We could quantitatively measure the metal artifact volume in MDCT by using 3D imaging software. In practice, the results of our study indicate that increasing kilovoltage is more effective for metal artifact reduction than increasing the effective mAs.
OBJECTIVE: The purpose of this study was to examine the effects of computed tomographic (CT) parameters on metal artifact reduction in multidetector CT (MDCT) using a quantitative 3-dimensional (3D) measurement of the metal artifact volume. METHODS: A steel-based plate and screw were implanted in the femora of 3 porcine thigh specimens. The specimens were examined using 16-slice MDCT with 7 different combinations of acquisition parameters that consisted of kilovolt (peak) (kV[p]) and effective milliampere-seconds (mAs): 120 and 100; 120 and 300; 120 and 500; 120 and 1000; 140 and 100; 140 and 300; and 140 and 500 under a detector collimation of 0.75 mm and a beam pitch of 0.45. The axial image reconstructions were performed with 4 different settings: 0.75-, 1-, 2-, and 2-mm slice thickness reconstruction under an extended CT scale. At the levels of all 14 screws in the 3 femora, the metal artifact volumes in various combinations of acquisition and reconstruction settings were measured using personal computer-based 3D imaging software and were compared with each other. RESULTS: The presence of a metal artifact was significantly reduced by increasing the kilovoltage and by decreasing the reconstruction thickness (P < 0.05; 2-way analysis of variance test). Neither increasing the effective mAs nor applying extended CT scale reduced the presence of the metal artifact significantly (P = 0.599 and P = 0.474, respectively). Compared with the metal artifact volume at 120 kV(p) and 100 mAs and a 2-mm slice thickness as a reference setting, the metal artifact reduction rate was 22% by increasing kilovoltage to 140, whereas only 11% by increasing mAs to 1000. CONCLUSIONS: We could quantitatively measure the metal artifact volume in MDCT by using 3D imaging software. In practice, the results of our study indicate that increasing kilovoltage is more effective for metal artifact reduction than increasing the effective mAs.
Authors: An De Crop; Jan Casselman; Tom Van Hoof; Melissa Dierens; Elke Vereecke; Nicolas Bossu; Jaime Pamplona; Katharina D'Herde; Hubert Thierens; Klaus Bacher Journal: Neuroradiology Date: 2015-05-01 Impact factor: 2.804
Authors: Shairah Radzi; Gary Cowin; Mark Robinson; Jit Pratap; Andrew Volp; Michael A Schuetz; Beat Schmutz Journal: Quant Imaging Med Surg Date: 2014-06