论文标题
质子停止功率图像来自蒙特卡洛模拟双能CT扫描
Proton stopping power images from Monte Carlo simulated dual-energy CT scans
论文作者
论文摘要
我们使用双能量CT-TO-SP程序测试了一组虚拟单色（VM）CT图像，测试一组虚拟单色（VM）CT图像的可行性，该虚拟单色（VM）CT图像使用蒙特卡洛生成的CT扫描创建的可行性。以70和150 kVp光谱的形式建模了蒙特卡洛CT模拟，以Somatom力双源DECT DECT DECT扫描仪和Gammex RMI 467 Tissue Calibration Phantom的X射线管参数进行建模。使用两个VM X射线图像创建了重建的SP图像，并选择单色能对，以使用根平方 - 元素（RMSE）最小化SP残差误差。除了平均重建的插入值的相对误差（使用已知的电子密度和每种材料的化学成分计算得出，制造商提供的平均重建插入值（计算得出），还研究了幻影插入物的对比度。还将结果与类似的基于双能量的SP转换程序进行了比较。在幻影的低密度和高密度构型中，几乎所有插入物中都可以看到误差和噪声的适度降低，并且可见的是横梁硬化的条纹伪像的可见降低。我们的蒙特卡洛模拟DECT扫描证实了先前提出的基于DECT的$ S（ρ_e，Z）$确定的方法的可行性。通过利用VM图像并仅优化RMSE在特定插入物上，当已知存在极低或高密度的组织时，最重要的身体组织中的残留误差可能会减少。
We test the feasibility of calculating proton stopping power (SP) from a set of virtual monochromatic (VM) CT images, created with Monte Carlo-generated CT scans, using a dual-energy CT-to-SP procedure. The Monte Carlo CT simulations, with 70 and 150 kVp spectra, were modeled on the x-ray tube parameters of the SOMATOM Force dual-source DECT scanner and the Gammex RMI 467 tissue calibration phantom. Reconstructed SP images were created with two VM x-ray images, and the monochromatic energy pairs were chosen to minimize the SP residual errors using the root-mean-squared-error (RMSE). The contrast of phantom inserts has also been examined, in addition to relative errors of the average reconstructed insert values (which are calculated using the known electron densities and chemical compositions of each material, provided by the manufacturer). Results were also compared to a similar dual-energy-based SP conversion procedure for comparison. Modest reductions in errors and noise were seen in almost all inserts in both low- and high-density configurations of the phantom, with a visible reduction in beam-hardening streaking artifacts. Our Monte Carlo simulated DECT scans confirm the feasibility of previously proposed methods of DECT-based $ S(ρ_e, Z) $-determination. By utilizing VM images and only optimizing the RMSE over specific inserts, the residual error across the most vital bodily tissues may be reduced when extremely low- or high-density tissues are known to be present.
