Department of Biomedical Engineering, Marquette University, Milwaukee, WI 53201, USA.
Med Phys. 2011 Oct;38(10):5657-66. doi: 10.1118/1.3641749.
Energy-resolved CT using photon-counting detectors has the potential to provide improved material decomposition compared to dual-kVp approaches. However, available photon-counting detectors are susceptible to pulse-pileup artifacts, especially at the periphery of the field of view (FOV) where the object attenuation is low compared to the center of the FOV. Pulse pileup may be avoided by imaging a region-of-interest (ROI) where the dynamic range is expected to be limited. This work investigated performing material decomposition and reconstructing ROI basis images from truncated energy-resolved data.
A method is proposed to reconstruct images of basis functions primarily contained within the ROI, such as targeted or localized K-edge contrast agents. Material decomposition is performed independently for each ray in the sinogram, followed by filtered backprojection from the truncated data encompassing the ROI. A second method is proposed that uses a prior conventional energy-integrating image to estimate energy-resolved data outside the ROI. The measured and estimated energy-resolved data are decomposed into basis projections and merged into basis sinograms of the full FOV. Basis images of the ROI are then reconstructed through filtered backprojection. This method is most easily applied to objects that do not contain K-edge contrast agents outside the ROI. Simulations of a voxelized thorax phantom with iodine in the blood pool and a detector with five energy bins were performed. Full FOV, truncated, and truncated data merged with data estimated from the prior energy-integrating image were decomposed into Compton, photoelectric, and iodine basis functions. An empirical weighting factor was determined to blend the merged sinogram at the boundary of the truncated data. The effects of noise and misalignment in the prior image were also quantified. Basis images of the central 15 cm × 15 cm ROI containing the heart were reconstructed via filtered backprojection. Basis image accuracy was quantified relative to gold-standard basis images reconstructed from full FOV energy-resolved data.
The error in the iodine basis image reconstructed from truncated energy-resolved data without prior information was less than 1% for the central 7 cm of the 7.5-cm-radius ROI and 3% at the edge of the ROI. When the truncated and estimated basis sinograms were blended, the error was below 1% throughout the ROI for photoelectric basis images and ranged from 1% at the center of the ROI to 4% at the edge for the Compton basis image.
The density of localized K-edge contrast agents can be estimated to within 1% error using filtered back projection without prior information. For noncontrast and localized-contrast scans, ROI images of general basis functions can be reconstructed to within a few percent error using a prior energy-integrating image. The ability to perform material decomposition for a limited ROI may facilitate energy-resolved CT with available photon-counting detectors.
与双能 kVp 方法相比，使用基于光子计数探测器的能谱 CT 具有提供更好的材料分解的潜力。然而，现有的基于光子计数的探测器容易受到脉冲堆积伪影的影响，特别是在视场（FOV）的边缘，物体衰减与 FOV 的中心相比较低。通过对预期动态范围有限的感兴趣区域（ROI）进行成像，可以避免脉冲堆积。本研究探讨了从截断能谱数据中重建 ROI 基图像和进行材料分解的方法。
提出了一种从 ROI 中的基函数重建图像的方法，例如靶向或局部 K 边缘对比度剂。在每根射线的正弦图中独立进行材料分解，然后对包含 ROI 的截断数据进行滤波反投影。还提出了一种使用先验常规能量积分图像来估计 ROI 外的能谱数据的方法。测量和估计的能谱数据被分解为基投影，并合并到整个 FOV 的基正弦图中。然后通过滤波反投影重建 ROI 的基图像。该方法最适用于 ROI 外不含 K 边缘对比度剂的物体。对一个具有碘在血池中和一个具有五个能量-bin 的探测器的体素化胸腔模型进行了模拟。对整个 FOV、截断和截断后与先验能量积分图像估计值合并的数据进行了分解，得到康普顿、光电和碘基函数。确定了一个经验权重因子来混合截断数据边界处的合并正弦图。还量化了先验图像中的噪声和错位的影响。通过滤波反投影重建了包含心脏的中心 15cm×15cm ROI 的基图像。与从全 FOV 能谱数据重建的金标准基图像相比，定量评估了中心 15cm×15cm ROI 内的基图像的准确性。
在没有先验信息的情况下，从截断能谱数据重建碘基图像的误差小于 7.5cm 半径 ROI 中心 7cm 处的 1%，边缘处的 3%。当混合截断和估计的基正弦图时，光电基图像在整个 ROI 内的误差低于 1%，而康普顿基图像的误差从 ROI 中心的 1%到边缘的 4%不等。
无需先验信息，使用滤波反投影可以将局部 K 边缘对比度剂的密度估计到 1%以内的误差。对于非对比和局部对比度扫描，可以使用先验能量积分图像重建几个百分点误差内的通用基函数 ROI 图像。对于有限 ROI 进行材料分解的能力可能会促进使用现有的基于光子计数的探测器进行能谱 CT。
