Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran.
Br J Radiol. 2013 Sep;86(1029):20130308. doi: 10.1259/bjr.20130308. Epub 2013 Aug 9.
Recently introduced energy-sensitive X-ray CT makes it feasible to discriminate different nanoparticulate contrast materials. The purpose of this work is to present a K-edge ratio method for differentiating multiple simultaneous contrast agents using spectral CT.
The ratio of two images relevant to energy bins straddling the K-edge of the materials is calculated using an analytic CT simulator. In the resulting parametric map, the selected contrast agent regions can be identified using a thresholding algorithm. The K-edge ratio algorithm is applied to spectral images of simulated phantoms to identify and differentiate up to four simultaneous and targeted CT contrast agents.
We show that different combinations of simultaneous CT contrast agents can be identified by the proposed K-edge ratio method when energy-sensitive CT is used. In the K-edge parametric maps, the pixel values for biological tissues and contrast agents reach a maximum of 0.95, whereas for the selected contrast agents, the pixel values are larger than 1.10. The number of contrast agents that can be discriminated is limited owing to photon starvation. For reliable material discrimination, minimum photon counts corresponding to 140 kVp, 100 mAs and 5-mm slice thickness must be used.
The proposed K-edge ratio method is a straightforward and fast method for identification and discrimination of multiple simultaneous CT contrast agents.
A new spectral CT-based algorithm is proposed which provides a new concept of molecular CT imaging by non-iteratively identifying multiple contrast agents when they are simultaneously targeting different organs.
最近引入的能谱 X 射线 CT 使得区分不同纳米颗粒对比剂成为可能。本研究旨在提出一种基于能谱 CT 的 K 边比值法来区分多种同时使用的对比剂。
使用解析 CT 模拟器计算跨越材料 K 边的两个能区图像的比值。在得到的参数图中，使用阈值算法可以识别选定的对比剂区域。将 K 边比值算法应用于模拟体模的能谱图像，以识别和区分多达四种同时和靶向 CT 对比剂。
当使用能谱 CT 时，我们表明，所提出的 K 边比值法可以识别不同组合的同时 CT 对比剂。在 K 边参数图中，生物组织和对比剂的像素值达到最大值 0.95，而对于选定的对比剂，像素值大于 1.10。由于光子饥饿，可区分的对比剂数量有限。为了进行可靠的材料鉴别，必须使用对应于 140 kVp、100 mAs 和 5 mm 层厚的最小光子计数。
所提出的 K 边比值法是一种简单、快速的方法，可用于识别和区分多种同时使用的 CT 对比剂。
提出了一种新的基于能谱 CT 的算法，通过非迭代地识别同时靶向不同器官的多种对比剂，为分子 CT 成像提供了新概念。
