能谱CT脑动脉造影单能量图像质量优化研究

目的：探讨能谱CT不同单能量水平对脑动脉造影图像质量的影响，以确定最优化的单能量图像。方法：采用能谱CT对53例患者行脑CT动脉造影（CTA）检查。应用能谱分析软件，以10 keV间隔重建40～140 keV单能量脑CTA图像。测量并计算基底动脉、颈内动脉颅内段、大脑前、中、后动脉图像对比噪声比（CNR）、信号噪声比（SNR）；采用5分法对脑CTA图像的主观质量进行盲法独立评分。分别采用单因素方差分析和非参数秩和检验对各单能量脑CTA图像的客观和主观质量进行比较评价。结果：图像客观质量比较，60、70 keV脑CTA图像CNR、SNR值较其他各单能量图像显著增加（P＜0.05），但60、70 keV间差异无统计学意义（P＞0.05）。单能量脑CTA图像噪声以70 keV为界，70～140 keV图像噪声显著低于40、50、60 keV单能量水平。而且70 keV图像主观质量评分结果较60 keV及其他各单能量图像评分结果显著增加。结论：能谱70 keV水平单能量脑CTA图像兼顾图像CNR、SNR及图像噪声，可作为最优化单能量水平。

Imaging quality optimization of CT cerebral angiography by using single source spectral CT

Objective: To determinate the optimal keV levels of single source spectral CT by evaluating imaging qualities of CT cerebral angiography. Methods: A total of 53 cases underwent spectral CT were enrolled in this study. All images of cerebral angiography were reconstructed by software of spectral CT from 40 to 140 keV in 10 keV increments. The mean vessel attenuation and the contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR) of the following arteries: basilar artery, internal carotid artery, anterior cerebral artery, middle cerebral artery and posterior cerebral artery were measured and calculated respectively. Subjective assessment on imaging quality was performed by using a 5-point scoring system. The results of objective image quality among different keV levels were compared using one-way analysis of variance. For subjective assessment, the Nonparametric Wilcoxon test was used to analyze the differences in subjective scores. Results: The image noise at 70-140 keV levels was statistically lower than that at 40, 50 and 60 keV levels. The image CNR and SNR between 60 keV and 70 keV levels showed on statistically differences, but markedly higher than other keV levels (P<0.05). The scores of subjective image quality at 70 keV level were all higher than other keV levels including 60 keV level (P<0.05). Conclusion: The 70 keV level can be commended as an optimal keV setting for spectral CT cerebral angiography by improving image CNR, SNR and reducing image noise.