From the Diagnostic and Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany.
Invest Radiol. 2019 Nov;54(11):689-696. doi: 10.1097/RLI.0000000000000591.
Using dual-energy computed tomography (DECT) for quantifying iodine content after injection of contrast agent could provide a quantitative basis for dynamic computed tomography (CT) perfusion measurements by means of established mathematical models of contrast agent kinetics, thus improving results by combining the strength of both techniques, which was investigated in this study.
A dynamic DECT acquisition over 51 seconds performed at 80/Sn140 kVp in 17 patients with pancreatic carcinoma was used to calculate iodine-enhancement images for each time point by means of 3-material decomposition. After motion correction, perfusion maps of blood flow were calculated using the maximum-slope model from both 80 kVp image data and iodine-enhancement images. Blood flow was measured in regions of interest placed in healthy pancreatic tissue and carcinoma for both of the derived perfusion maps. To assess image quality of input data, an adjusted contrast-to-noise ratio was calculated for 80 kVp images and iodine-enhancement images. Susceptibility of perfusion results to residual patient breathing motion during acquisition was investigated by measuring blood flow in fatty tissue surrounding the pancreas, where blood flow should be negligible compared with the pancreas.
For both 80 kVp and iodine-enhancement images, blood flow was significantly higher in healthy tissue (114.2 ± 37.4 mL/100 mL/min or 115.1 ± 36.2 mL/100 mL/min, respectively) than in carcinoma (46.5 ± 26.6 mL/100 mL/min or 49.7 ± 24.7 mL/100 mL/min, respectively). Differences in blood flow between 80 kVp image data and iodine-enhancement images were statistically significant in healthy tissue, but not in carcinoma. For 80 kVp images, adjusted contrast-to-noise ratio was significantly higher (1.3 ± 1.1) than for iodine-enhancement images (1.1 ± 0.9). When evaluating fatty tissue surrounding the pancreas for estimating influence of patient motion, measured blood flow was significantly lower for iodine-enhancement images (30.7 ± 12.0 mL/100 mL/min) than for 80 kVp images (39.0 ± 19.1 mL/100 mL/min). Average patient radiation exposure was 8.01 mSv for dynamic DECT acquisition, compared with 4.60 mSv for dynamic 80 kVp acquisition.
Iodine enhancement images can be used to calculate CT perfusion maps of blood flow, and compared with 80 kVp images, results showed only a small difference of 1 mL/100 mL/min in blood flow in healthy tissue, whereas patient radiation exposure was increased for dynamic DECT. Perfusion maps calculated based on iodine-enhancement images showed lower blood flow in fatty tissues surrounding the pancreas, indicating reduced susceptibility to residual patient breathing motion during the acquisition.
使用双能量计算机断层扫描（DECT）对造影剂注射后的碘含量进行定量，可以为通过造影剂动力学的既定数学模型进行动态计算机断层扫描（CT）灌注测量提供定量基础，从而通过结合两种技术的优势来提高结果，本研究对此进行了探讨。
在 17 例胰腺癌患者中进行了 51 秒的动态 DECT 采集，在 80/Sn140 kVp 下进行，使用 3 种材料分解法为每个时间点计算碘增强图像。在运动校正后，使用最大斜率模型从 80 kVp 图像数据和碘增强图像计算血流灌注图。在这两种衍生的灌注图中，在健康胰腺组织和癌组织中放置感兴趣区域来测量血流。为了评估输入数据的图像质量，计算了 80 kVp 图像和碘增强图像的调整后对比噪声比。通过测量胰腺周围脂肪组织中的血流来研究灌注结果对采集过程中残留患者呼吸运动的敏感性，在这种情况下，与胰腺相比，血流应该可以忽略不计。
对于 80 kVp 和碘增强图像，健康组织中的血流均明显高于癌组织（分别为 114.2±37.4 mL/100 mL/min 和 115.1±36.2 mL/100 mL/min）。健康组织中 80 kVp 图像数据和碘增强图像之间的血流差异具有统计学意义，但在癌组织中则没有。对于 80 kVp 图像，调整后的对比噪声比（1.3±1.1）明显高于碘增强图像（1.1±0.9）。当评估胰腺周围的脂肪组织以估计患者运动的影响时，碘增强图像测量的血流（30.7±12.0 mL/100 mL/min）明显低于 80 kVp 图像（39.0±19.1 mL/100 mL/min）。与动态 80 kVp 采集相比，动态 DECT 采集的平均患者辐射暴露量为 8.01 mSv。
碘增强图像可用于计算血流的 CT 灌注图，与 80 kVp 图像相比，仅在健康组织中血流的差异为 1 mL/100 mL/min，而动态 DECT 的患者辐射暴露量增加。基于碘增强图像计算的灌注图显示胰腺周围脂肪组织中的血流较低，表明在采集过程中对残留患者呼吸运动的敏感性降低。
