Keita Kuya1, Yuki Shinohara2, Ayumi Kato3, Makoto Sakamoto4, Masamichi Kurosaki4, Toshihide Ogawa1. 1. Division of Radiology, Department of Pathophysiological and Therapeutic Science, Faculty of Medicine, Tottori University, 36-1, Nishi-cho, Yonago, 683-8504, Japan. 2. Division of Radiology, Department of Pathophysiological and Therapeutic Science, Faculty of Medicine, Tottori University, 36-1, Nishi-cho, Yonago, 683-8504, Japan. shino-y@olive.plala.or.jp. 3. Department of Radiology, Tottori Municipal Hospital, Yonago, Japan. 4. Division of Neurosurgery, Department of Neurological Sciences, Faculty of Medicine, Tottori University, Yonago, Japan.
Abstract
PURPOSE: The aim of this study is to assess the value of adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) for reduction of metal artifacts due to dental hardware in carotid CT angiography (CTA). METHODS: Thirty-seven patients with dental hardware who underwent carotid CTA were included. CTA was performed with a GE Discovery CT750 HD scanner and reconstructed with filtered back projection (FBP), ASIR, and MBIR. We measured the standard deviation at the cervical segment of the internal carotid artery that was affected most by dental metal artifacts (SD1) and the standard deviation at the common carotid artery that was not affected by the artifact (SD2). We calculated the artifact index (AI) as follows: AI = [(SD1)2 - (SD2)2]1/2 and compared each AI for FBP, ASIR, and MBIR. Visual assessment of the internal carotid artery was also performed by two neuroradiologists using a five-point scale for each axial and reconstructed sagittal image. The inter-observer agreement was analyzed using weighted kappa analysis. RESULTS: MBIR significantly improved AI compared with FBP and ASIR (p < 0.001, each). We found no significant difference in AI between FBP and ASIR (p = 0.502). The visual score of MBIR was significantly better than those of FBP and ASIR (p < 0.001, each), whereas the scores of ASIR were the same as those of FBP. Kappa values indicated good inter-observer agreements in all reconstructed images (0.747-0.778). CONCLUSIONS: MBIR resulted in a significant reduction in artifact from dental hardware in carotid CTA.
PURPOSE: The aim of this study is to assess the value of adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) for reduction of metal artifacts due to dental hardware in carotid CT angiography (CTA). METHODS: Thirty-seven patients with dental hardware who underwent carotid CTA were included. CTA was performed with a GE Discovery CT750 HD scanner and reconstructed with filtered back projection (FBP), ASIR, and MBIR. We measured the standard deviation at the cervical segment of the internal carotid artery that was affected most by dental metal artifacts (SD1) and the standard deviation at the common carotid artery that was not affected by the artifact (SD2). We calculated the artifact index (AI) as follows: AI = [(SD1)2 - (SD2)2]1/2 and compared each AI for FBP, ASIR, and MBIR. Visual assessment of the internal carotid artery was also performed by two neuroradiologists using a five-point scale for each axial and reconstructed sagittal image. The inter-observer agreement was analyzed using weighted kappa analysis. RESULTS: MBIR significantly improved AI compared with FBP and ASIR (p < 0.001, each). We found no significant difference in AI between FBP and ASIR (p = 0.502). The visual score of MBIR was significantly better than those of FBP and ASIR (p < 0.001, each), whereas the scores of ASIR were the same as those of FBP. Kappa values indicated good inter-observer agreements in all reconstructed images (0.747-0.778). CONCLUSIONS: MBIR resulted in a significant reduction in artifact from dental hardware in carotid CTA.
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