Wang Sen, Yang Yirong, Pal Debashish, Yin Zhye, Maltz Jonathan S, Pelc Norbert J, Wang Adam S
Stanford University, Department of Radiology, Stanford, California, United States.
Stanford University, Department of Electrical Engineering, Stanford, California, United States.
J Med Imaging (Bellingham). 2024 Dec;11(Suppl 1):S12805. doi: 10.1117/1.JMI.11.S1.S12805. Epub 2024 Jul 25.
Photon counting CT (PCCT) provides spectral measurements for material decomposition. However, the image noise (at a fixed dose) depends on the source spectrum. Our study investigates the potential benefits from spectral optimization using fast kV switching and filtration to reduce noise in material decomposition.
The effect of the input spectra on noise performance in both two-basis material decomposition and three-basis material decomposition was compared using Cramer-Rao lower bound analysis in the projection domain and in a digital phantom study in the image domain. The fluences of different spectra were normalized using the CT dose index to maintain constant dose levels. Four detector response models based on Si or CdTe were included in the analysis.
For single kV scans, kV selection can be optimized based on the imaging task and object size. Furthermore, our results suggest that noise in material decomposition can be substantially reduced with fast kV switching. For two-material decomposition, fast kV switching reduces the standard deviation (SD) by . For three-material decomposition, greater noise reduction in material images was found with fast kV switching (26.2% for calcium and 25.8% for iodine, in terms of SD), which suggests that challenging tasks benefit more from the richer spectral information provided by fast kV switching.
The performance of PCCT in material decomposition can be improved by optimizing source spectrum settings. Task-specific tube voltages can be selected for single kV scans. Also, our results demonstrate that utilizing fast kV switching can substantially reduce the noise in material decomposition for both two- and three-material decompositions, and a fixed Gd filter can further enhance such improvements for two-material decomposition.
光子计数CT(PCCT)可提供用于物质分解的光谱测量。然而,(在固定剂量下)图像噪声取决于源光谱。我们的研究探讨了使用快速千伏切换和滤波进行光谱优化以降低物质分解中噪声的潜在益处。
使用投影域中的克拉美 - 罗下界分析以及图像域中的数字体模研究,比较了输入光谱对双基物质分解和三基物质分解中噪声性能的影响。使用CT剂量指数对不同光谱的注量进行归一化,以保持剂量水平恒定。分析中包括了基于硅或碲化镉的四种探测器响应模型。
对于单千伏扫描,可根据成像任务和物体大小优化千伏选择。此外,我们的结果表明,快速千伏切换可大幅降低物质分解中的噪声。对于双物质分解,快速千伏切换将标准差(SD)降低了 。对于三物质分解,快速千伏切换在物质图像中实现了更大的降噪效果(钙的标准差降低26.2%,碘的标准差降低25.8%),这表明具有挑战性的任务从快速千伏切换提供的更丰富光谱信息中受益更多。
通过优化源光谱设置可提高PCCT在物质分解方面的性能。对于单千伏扫描,可选择特定任务的管电压。此外,我们的结果表明,利用快速千伏切换可大幅降低双物质和三物质分解中物质分解的噪声,并且固定的钆滤波器可进一步增强双物质分解的这种改善效果。