  The presence of metal implants within CT imaging causes severe attenuation of
the 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 resulting
CT images. The metal-induced artifacts would firstly affect the quantitative
accuracy of CT imaging, and consequently, the radiation treatment planning and
dose estimation in radiation therapy. To address this issue, CT scanner vendors
have implemented metal artifact reduction (MAR) algorithms to avoid such
artifacts and enhance the overall quality of CT images. The orthopedic-MAR
(OMAR) and normalized MAR (NMAR) algorithms are the most well-known metal
artifact reduction (MAR) algorithms, used worldwide. These algorithms have been
implemented on Philips and Siemens scanners, respectively. In this study, we
set out to quantitatively and qualitatively evaluate the effectiveness of these
two MAR algorithms and their impact on accurate radiation treatment planning
and CT-based dosimetry. The quantitative metrics measured on the simulated
metal artifact dataset demonstrated superior performance of the OMAR technique
over the NMAR one in metal artifact reduction. The analysis of radiation
treatment planning using the OMAR and NMAR techniques in the corrected CT
images showed that the OMAR technique reduced the toxicity of healthy tissues
by 10% compared to the uncorrected CT images.
