Assessment of Material Identification Errors, Image Quality, and Radiation Doses Using Small Animal Spectral Photon-Counting CT

IEEE Transactions on Radiation and Plasma Medical Sciences(2021)

引用 11|浏览18
暂无评分
摘要
Photon-counting CT offers the potential to provide new diagnostic information. In this study, we sought to determine the interplay between material identification errors, image quality indicators, and radiation doses using photon-counting spectral CT, and to determine whether this relationship is replicated in spectral CT scans of mice. Custom-built Perspex phantoms were used to measure signal-to-noise ratio (SNR) and spatial resolution, and to measure radiation dose using thermoluminescent dosimeters. A multicontrast calibration phantom containing inserts with different concentrations of gadolinium (1, 2, 4, and 8 mg/mL), hydroxyapatite rods (0, 54.3, 104.3, 211.7, 402.3, and 808.5 mg/mL) along with water and lipid was used to assess material identification errors. Image acquisition was performed using the MARS photon-counting scanner with four energy channels (30–45, 45–60, 60–78, and 78–118 keV) at four different tube currents (24, 34, 44, and $55~\mu \text{A}$ ). As increased tube current showed no significant effect on material characterization, small animal dosimetry was performed with 24- $\mu \text{A}$ tube current using two noncontrast mice and one mouse injected with gadolinium. Results demonstrated that a tube current increase from 24 to $54~\mu \text{A}$ improved the SNR and spatial resolution by <10%, gadolinium identification by <20% (for 1 mg/mL) but radiation dose increased by >160%. Imaging results of the mice showed no obvious artefacts, and the mean absorbed dose measured for the three mice was 27.3±2.4 mGy. The results suggest that the energy resolving capability of photon-counting CT maintains diagnostically relevant image quality with high levels of material discrimination at reduced radiation dose.
更多
查看译文
关键词
Absorbed dose,image quality,material decomposition,Medipix,molecular imaging,photon-counting CT,spectral CT
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要