An Image-Domain Contrast Material Extraction Method for Dual-Energy Computed Tomography.
An Image-Domain Contrast Material Extraction Method for Dual-Energy Computed Tomography.
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DOI：
10.1097/rli.0000000000000335
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发表时间：
2017-04
影响因子：
6.7
通讯作者：
Yeh BM
中科院分区：
文献类型：
--
作者：
Lambert JW;Sun Y;Gould RG;Ohliger MA;Li Z;Yeh BM
用于双能量CT（DECT）的传统材料分解技术假定质量或体积守恒，其中每个体素的CT编号完全分配给预定义的材料。我们提出了一种图像域对比度材料提取过程（CMEP）的方法，优先提取对比度产生的材料，而其余的图像完好无损。图像处理免费软件（Fiji）用于在双能量比率图上执行连续的算术运算以生成掩模，然后将掩模应用于原始图像以生成材料特定的图像。首先，将低能量图像除以高能量图像以生成比率图。然后将比率贴图分割为特定于材质的遮罩。已知对应于特定材料（例如碘、钙）的比率区间被指定为乘数1，而这些区间之间的比率值被指定为从0到1的线性梯度。然后将掩模乘以原始CT图像以产生材料特异性图像。该方法进行了定量测试，在双源（DSCT）和快速kVp开关CT（RSCT）与phantomerase使用纯和混合配方的钨，钙和碘。通过比较已知的物质浓度与来自CMEP物质特定图像的物质浓度来评估误差。使用与体模相同的CMEP参数，在RSCT中使用家兔模型进行了进一步的体内定性评价。口服给予钨，血管内给予碘，和骨骼钙被用作三种对比材料。所有五种材料组合;钨、碘和钙以及钨-钙和碘-钙的混合物显示出明显的双能比，在DSCT和RSCT两者中基本上与材料浓度无关。CMEP在体模和体内均获得成功。对于体模中的纯造影剂，碘、钙和钨的已知和CMEP衍生材料浓度之间的最大误差分别为0.9 mg/mL、24.9 mg/mL和0.4 mg/mL。碘和钙的混合物显示出最高的差异，这反映了碘对提取最终材料特定图像所选图像类型的敏感性。家兔模型能够清楚地显示三种浸提材料相，即血管碘、口服钨和骨骼钙。一些骨骼钙被错误分配到提取的碘图像，但这并不妨碍血管系统的描绘。CMEP是一种直接的图像域方法，用于在双能量CT上提取材料信号。它对于将实验性高Z对比元素与常规碘对比剂或钙分离具有特别的价值，即使当所需对比材料的精确衰减系数分布可能未知时。CMEP很容易在免费软件中的图像域中实现，并且可以适用于来自多个供应商的图像。
Conventional material decomposition techniques for dual-energy CT (DECT) assume mass or volume conservation, where the CT number of each voxel is fully assigned to predefined materials. We present an image-domain contrast material extraction process (CMEP) method that preferentially extracts contrast-producing materials while leaving the remaining image intact. Image processing freeware (Fiji) is used to perform consecutive arithmetic operations on a dual-energy ratio map to generate masks, which are then applied to the original images to generate material-specific images. First, a low-energy image is divided by a high-energy image to generate a ratio map. The ratio map is then split into material-specific masks. Ratio intervals known to correspond to particular materials (e.g. iodine, calcium) are assigned a multiplier of 1, while ratio values in between these intervals are assigned linear gradients from 0 to 1. The masks are then multiplied by an original CT image to produce material-specific images. The method was tested quantitatively at Dual-Source (DSCT) and Rapid kVp-Switching CT (RSCT) with phantoms using pure and mixed formulations of tungsten, calcium and iodine. Errors were evaluated by comparing the known material concentrations with those derived from the CMEP material-specific images. Further qualitative evaluation was performed in vivo at RSCT with a rabbit model using identical CMEP parameters to the phantom. Orally administered tungsten, vascularly administered iodine, and skeletal calcium were used as the three contrast materials. All five material combinations; tungsten, iodine and calcium, and mixtures of tungsten-calcium and iodine-calcium, showed distinct dual-energy ratios, largely independent of material concentration at both DSCT and RSCT. The CMEP was successful in both phantoms and in vivo. For pure contrast materials in the phantom, the maximum error between the known and CMEP-derived material concentrations was 0.9 mg/mL, 24.9 mg/mL and 0.4 mg/mL for iodine, calcium and tungsten respectively. Mixtures of iodine and calcium showed the highest discrepancies, which reflected the sensitivity of iodine to the image-type chosen for the extraction of the final material-specific image. The rabbit model was able to clearly show the three extracted material phases, vascular iodine, oral tungsten and skeletal calcium. Some skeletal calcium was misassigned to the extracted iodine image, however this did not impede the depiction of the vasculature. The CMEP is a straightforward, image domain approach to extract material signal at dual-energy CT. It has particular value for separation of experimental high-Z contrast elements from conventional iodine contrast or calcium, even when the exact attenuation coefficient profiles of desired contrast materials may be unknown. The CMEP is readily implemented in the image-domain within freeware, and can be adapted for use with images from multiple vendors.