摘要
目的:探讨256层CT支气管动脉造影的技术优化。方法:90例拟行常规胸部增强CT(Philips i CT)的患者顺序分成三组:第1~30例纳入A组,采用120k V,Average 100m As(standard);第31~60例纳入B组,采用100k V,100m As(standard);第61~90例纳入C组,采用100k V,100m As(high)。0.67mm层厚,0.67mm间隔,i Dose4第4级重建,比较3组图像的主动脉CT值、噪声值(SD)和对比噪声比(CNR)。对三组采集的图像进行MIP和VR重组,并对重组图像上的支气管动脉细节显示进行主观评价。结果:主动脉CT强化值,B、C两组相似且均明显高于A组(P〈0.05),横断面图像SD值则A,B两组相似且明显低于C组(P〈0.05),CNR值则A,B两组相似且明显高于C组(P〈0.05)。三维图像上支气管动脉细节显示以C组最佳,优于B组(P〈0.05),显著优于A组(P〈0.01),B组稍优于A组(P〈0.05)。结论:低k V、高分辨扫描方式可以更好显示支气管动脉细节,适合256层i CT上应用。
Purpose: To optimize the technique ofMSCT angiography of bronchial artery with a 256-slice CT scanner. Methods: Ninety patients undertaken thoracic contrasted MSCT (Philips iCT) examination were enrolled in our study and divided into three groups according to the exam order: group A (patients 1-30) with protocol A (120kV, Average 100mAs, standard resolution), group B (patients 31-60) with protocol B (100kV, Average 100mAs, standard resolution), and group C (patients 61-90) with protocol C (100kV, Average 100mAs, high resolution). The other parameters included 0.67mm slice-thickness, 0.67ram interval, and iDose4 4 algorithm. The maximum intensity projection (MIP) and volume rendering (VR) images were obtained. The CT value, noise (SD) and contrast-noise-ratio (CNR) of aorta were compared among these three groups. The bronchial artery on MIP and VR images were evaluated by two radiologists. Results: The attenuation of aorta in group B and C was significantly larger than that in group A (P〈0.05). The SD values in group A and B was significantly smaller than that in group C (P〈0.05). The CNR in group A and B was significantly larger than that in group C (P〈0.05). The three-dimensional details of bronchial artery revealed in group C was better than that in group B (P〈0.05) and group A (P〈0.01). Conclusion: The protocol including low kV and high resolution scan mode would best reveal the details of bronchial artery, which could be applied in Philips iCT scanner.
出处
《中国医学计算机成像杂志》
CSCD
北大核心
2014年第6期561-564,共4页
Chinese Computed Medical Imaging
基金
上海市卫生局课题资助(编号20114191)~~