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.

中文翻译：

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商业金属伪影减少方法的定量和定性性能评估：剂量学对治疗计划的影响


CT 成像中金属植入物的存在会导致 X 射线束严重衰减。由于 CT 探测器记录的信息不完整，因此生成的 CT 图像中会出现条纹和暗带形式的伪影。金属伪影首先会影响CT成像的定量准确性，进而影响放射治疗中的放射治疗计划和剂量估计。为了解决这个问题，CT 扫描仪供应商实施了金属伪影减少 (MAR) 算法，以避免此类伪影并提高 CT 图像的整体质量。整形外科 MAR (OMAR) 和归一化 MAR (NMAR) 算法是全球范围内使用的最著名的金属伪影减少 (MAR) 算法。这些算法已分别在飞利浦和西门子扫描仪上实现。在本研究中，我们着手定量和定性评估这两种 MAR 算法的有效性及其对准确放射治疗计划和基于 CT 的剂量测定的影响。在模拟金属伪影数据集上测量的定量指标表明，OMAR 技术在金属伪影减少方面优于 NMAR 技术。在校正的CT图像中使用OMAR和NMAR技术对放射治疗计划的分析表明，与未校正的CT图像相比，OMAR技术将健康组织的毒性降低了10%。