INTRODUCTION: Metal artifacts may negatively affect radiologic assessment in the oral cavity. The aim of this study was to evaluate different metal artifact reduction techniques for metal artifacts induced by dental hardware in CT scans of the oral cavity. METHODS: Clinical image quality was assessed using a Thiel-embalmed cadaver. A Catphan phantom and a polymethylmethacrylate (PMMA) phantom were used to evaluate physical-technical image quality parameters such as artifact area, artifact index (AI), and contrast detail (IQFinv). Metal cylinders were inserted in each phantom to create metal artifacts. CT images of both phantoms and the Thiel-embalmed cadaver were acquired on a multislice CT scanner using 80, 100, 120, and 140 kVp; model-based iterative reconstruction (Veo); and synthesized monochromatic keV images with and without metal artifact reduction software (MARs). Four radiologists assessed the clinical image quality, using an image criteria score (ICS). RESULTS: Significant influence of increasing kVp and the use of Veo was found on clinical image quality (p = 0.007 and p = 0.014, respectively). Application of MARs resulted in a smaller artifact area (p < 0.05). However, MARs reconstructed images resulted in lower ICS. CONCLUSION: Of all investigated techniques, Veo shows to be most promising, with a significant improvement of both the clinical and physical-technical image quality without adversely affecting contrast detail. MARs reconstruction in CT images of the oral cavity to reduce dental hardware metallic artifacts is not sufficient and may even adversely influence the image quality.
INTRODUCTION:Metal artifacts may negatively affect radiologic assessment in the oral cavity. The aim of this study was to evaluate different metal artifact reduction techniques for metal artifacts induced by dental hardware in CT scans of the oral cavity. METHODS: Clinical image quality was assessed using a Thiel-embalmed cadaver. A Catphan phantom and a polymethylmethacrylate (PMMA) phantom were used to evaluate physical-technical image quality parameters such as artifact area, artifact index (AI), and contrast detail (IQFinv). Metal cylinders were inserted in each phantom to create metal artifacts. CT images of both phantoms and the Thiel-embalmed cadaver were acquired on a multislice CT scanner using 80, 100, 120, and 140 kVp; model-based iterative reconstruction (Veo); and synthesized monochromatic keV images with and without metal artifact reduction software (MARs). Four radiologists assessed the clinical image quality, using an image criteria score (ICS). RESULTS: Significant influence of increasing kVp and the use of Veo was found on clinical image quality (p = 0.007 and p = 0.014, respectively). Application of MARs resulted in a smaller artifact area (p < 0.05). However, MARs reconstructed images resulted in lower ICS. CONCLUSION: Of all investigated techniques, Veo shows to be most promising, with a significant improvement of both the clinical and physical-technical image quality without adversely affecting contrast detail. MARs reconstruction in CT images of the oral cavity to reduce dental hardware metallic artifacts is not sufficient and may even adversely influence the image quality.
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