Nuclear and Radiological Engineering and Medical Physics Programs, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
Med Phys. 2010 Oct;37(10):5395-406. doi: 10.1118/1.3483260.
Applications of cone-beam CT (CBCT) to image-guided radiationtherapy (IGRT) are hampered by shading artifacts in the reconstructed images. These artifacts are mainly due to scatter contamination in the projections but also can result from uncorrected beam hardening effects as well as nonlinearities in responses of the amorphous silicon flat panel detectors. While currently, CBCT is mainly used to provide patient geometry information for treatment setup, more demanding applications requiring high-quality CBCT images are under investigation. To tackle these challenges, many CBCT correction algorithms have been proposed; yet, a standard approach still remains unclear. In this work, we propose a shading correction method for CBCT that addresses artifacts from low-frequency projection errors. The method is consistent with the current workflow of radiation therapy.
With much smaller inherent scatter signals and more accurate detectors, diagnostic multidetector CT (MDCT) provides high quality CT images that are routinely used for radiation treatment planning. Using the MDCT image as "free" prior information, we first estimate the primary projections in the CBCT scan via forward projection of the spatially registered MDCT data. Since most of the CBCT shading artifacts stem from low-frequency errors in the projections such as scatter, these errors can be accurately estimated by low-pass filtering the difference between the estimated and raw CBCT projections. The error estimates are then subtracted from the raw CBCT projections. Our method is distinct from other published correction methods that use the MDCT image as a prior because it is projection-based and uses limited patient anatomical information from the MDCT image. The merit of CBCT-based treatment monitoring is therefore retained.
The proposed method is evaluated using two phantom studies on tabletop systems. On the Catphan 600 phantom, our approach reduces the reconstruction error from 348 Hounsfield unit (HU) without correction to 4 HU around the object center after correction, and from 375 HU to 17 HU in the high-contrast regions. In the selected regions of interest (ROIs), the average image contrast is increased by a factor of 3.3. When noise suppression is implemented, the proposed correction substantially improves the contrast-to-noise ratio (CNR) and therefore the visibility of low-contrast objects, as seen in a more challenging pelvis phantom study. Besides a significant improvement in image uniformity, a low-contrast object of approximately 25 HU, which is otherwise buried in the shading artifacts, can be clearly identified after the proposed correction due to a CNR increase of 3.1. Compared to a kernel-based scatter correction method coupled with an analytical beam hardening correction, our approach also shows an overall improved performance with some residual artifacts.
By providing effective shading correction, our approach has the potential to improve the accuracy of more advanced CBCT-based clinical applications for IGRT, such as tumor delineation and dose calculation.
锥形束 CT（CBCT）在图像引导放射治疗（IGRT）中的应用受到重建图像中阴影伪影的阻碍。这些伪影主要是由于投影中的散射污染引起的，但也可能是由于未校正的束硬化效应以及非晶硅平板探测器的响应非线性引起的。虽然目前 CBCT 主要用于为治疗设置提供患者几何信息，但正在研究需要高质量 CBCT 图像的更具挑战性的应用。为了应对这些挑战，已经提出了许多 CBCT 校正算法；然而，仍然不清楚一种标准方法。在这项工作中，我们提出了一种用于 CBCT 的阴影校正方法，用于校正低频投影误差引起的伪影。该方法与放射治疗的当前工作流程一致。
与固有散射信号小得多且探测器更准确的诊断多排 CT（MDCT）提供了常规用于放射治疗计划的高质量 CT 图像。使用 MDCT 图像作为“免费”先验信息，我们首先通过对空间配准的 MDCT 数据进行正向投影来估计 CBCT 扫描中的原始投影。由于大多数 CBCT 阴影伪影主要源自投影中的低频误差，例如散射，因此可以通过对估计和原始 CBCT 投影之间的差值进行低通滤波来准确估计这些误差。然后从原始 CBCT 投影中减去误差估计值。我们的方法与使用 MDCT 图像作为先验的其他已发表的校正方法不同，因为它是基于投影的，并且仅使用来自 MDCT 图像的有限患者解剖信息。因此，保留了基于 CBCT 的治疗监测的优势。
该方法通过在台式系统上进行的两项体模研究进行了评估。在 Catphan 600 体模上，我们的方法将未校正时的重建误差从 348 个亨氏单位（HU）降低到校正后的物体中心周围的 4 HU，并且在高对比度区域从 375 HU 降低到 17 HU。在选定的感兴趣区域（ROI）中，图像对比度的平均值提高了 3.3 倍。实施噪声抑制后，由于对比度噪声比（CNR）的提高，因此低对比度物体的可见度大大提高，这在更具挑战性的骨盆体模研究中可见。除了图像均匀性的显著改善之外，由于 CNR 提高了 3.1，因此可以在提议的校正后清楚地识别大约 25 HU 的低对比度物体，否则这些物体将被阴影伪影所掩盖。与结合分析束硬化校正的基于核的散射校正方法相比，我们的方法还表现出整体性能的提高，并且存在一些残余伪影。
通过提供有效的阴影校正，我们的方法有可能提高更先进的基于 CBCT 的 IGRT 临床应用的准确性，例如肿瘤描绘和剂量计算。
