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The presence of metal implants within CT imaging causes severe attenuation ofthe X-ray beam. Due to the incomplete information recorded by CT detectors,artifacts in the form of streaks and dark bands would appear in the resultingCT images. The metal-induced artifacts would firstly affect the quantitativeaccuracy of CT imaging, and consequently, the radiation treatment planning anddose estimation in radiation therapy. To address this issue, CT scanner vendorshave implemented metal artifact reduction (MAR) algorithms to avoid suchartifacts and enhance the overall quality of CT images. The orthopedic-MAR(OMAR) and normalized MAR (NMAR) algorithms are the most well-known metalartifact reduction (MAR) algorithms, used worldwide. These algorithms have beenimplemented on Philips and Siemens scanners, respectively. In this study, weset out to quantitatively and qualitatively evaluate the effectiveness of thesetwo MAR algorithms and their impact on accurate radiation treatment planningand CT-based dosimetry. The quantitative metrics measured on the simulatedmetal artifact dataset demonstrated superior performance of the OMAR techniqueover the NMAR one in metal artifact reduction. The analysis of radiationtreatment planning using the OMAR and NMAR techniques in the corrected CTimages showed that the OMAR technique reduced the toxicity of healthy tissuesby 10% compared to the uncorrected CT images.

Quantitative and Qualitative Performance Evaluation of Commercial Metal Artifact Reduction Methods: Dosimetric Effects on the Treatment Planning