McCollough Cynthia H, Boedeker Kirsten, Cody Dianna, Duan Xinhui, Flohr Thomas, Halliburton Sandra S, Hsieh Jiang, Layman Rick R, Pelc Norbert J
Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Canon (formerly Toshiba) Medical Systems Corporation, 1440 Warnall Ave, Los Angeles, CA, 90024, USA.
Med Phys. 2020 Jul;47(7):e881-e912. doi: 10.1002/mp.14157. Epub 2020 May 28.
In x-ray computed tomography (CT), materials with different elemental compositions can have identical CT number values, depending on the mass density of each material and the energy of the detected x-ray beam. Differentiating and classifying different tissue types and contrast agents can thus be extremely challenging. In multienergy CT, one or more additional attenuation measurements are obtained at a second, third or more energy. This allows the differentiation of at least two materials. Commercial dual-energy CT systems (only two energy measurements) are now available either using sequential acquisitions of low- and high-tube potential scans, fast tube-potential switching, beam filtration combined with spiral scanning, dual-source, or dual-layer detector approaches. The use of energy-resolving, photon-counting detectors is now being evaluated on research systems. Irrespective of the technological approach to data acquisition, all commercial multienergy CT systems circa 2020 provide dual-energy data. Material decomposition algorithms are then used to identify specific materials according to their effective atomic number and/or to quantitate mass density. These algorithms are applied to either projection or image data. Since 2006, a number of clinical applications have been developed for commercial release, including those that automatically (a) remove the calcium signal from bony anatomy and/or calcified plaque; (b) create iodine concentration maps from contrast-enhanced CT data and/or quantify absolute iodine concentration; (c) create virtual non-contrast-enhanced images from contrast-enhanced scans; (d) identify perfused blood volume in lung parenchyma or the myocardium; and (e) characterize materials according to their elemental compositions, which can allow in vivo differentiation between uric acid and non-uric acid urinary stones or uric acid (gout) or non-uric acid (calcium pyrophosphate) deposits in articulating joints and surrounding tissues. In this report, the underlying physical principles of multienergy CT are reviewed and each of the current technical approaches are described. In addition, current and evolving clinical applications are introduced. Finally, the impact of multienergy CT technology on patient radiation dose is summarized.
在X射线计算机断层扫描（CT）中，具有不同元素组成的材料可能具有相同的CT数值，这取决于每种材料的质量密度和检测到的X射线束的能量。因此，区分和分类不同的组织类型及造影剂极具挑战性。在多能量CT中，可在第二种、第三种或更多能量下获得一个或多个额外的衰减测量值。这使得至少两种材料得以区分。目前，商业双能量CT系统（仅进行两次能量测量）已可使用，其采用的方法包括顺序采集低管电压和高管电压扫描、快速管电压切换、结合螺旋扫描的束流过滤、双源或双层探测器方法。目前正在研究系统上评估能量分辨光子计数探测器的使用。无论采用何种数据采集技术方法，2020年前后所有商业多能量CT系统均提供双能量数据。然后使用材料分解算法根据有效原子序数识别特定材料和/或定量质量密度。这些算法应用于投影数据或图像数据。自2006年以来，已开发出多种临床应用以供商业发布，包括那些能自动（a）从骨骼解剖结构和/或钙化斑块中去除钙信号；（b）从增强CT数据创建碘浓度图和/或量化绝对碘浓度；（c）从增强扫描创建虚拟非增强图像；（d）识别肺实质或心肌中的灌注血容量；以及（e）根据元素组成表征材料，这可以在体内区分尿酸和非尿酸尿路结石，或关节及周围组织中的尿酸（痛风）或非尿酸（焦磷酸钙）沉积物。在本报告中，将对多能量CT的基本物理原理进行综述，并描述每种当前的技术方法。此外，还将介绍当前和不断发展的临床应用。最后，总结多能量CT技术对患者辐射剂量的影响。
