医学
图像质量
氡变换
放射科
血管造影
核医学
计算机断层血管造影
图像噪声
颈总动脉
辐射剂量
颈动脉
外科
数学
人工智能
图像(数学)
数学分析
计算机科学
作者
Shuang Yu,L. Zhang,Jiachen Zheng,Yanfeng Xu,Y. Chen,Zhenchun Song
标识
DOI:10.1016/j.crad.2016.08.004
摘要
To compare the effects of exposure parameters on image quality and radiation dose for craniocervical computed tomography angiography (CTA) using adaptive iterative dose reduction in three dimensions (AIDR 3D) and filtered back projection (FBP) algorithms.One hundred and eighty patients were divided into three groups; group A (120 kV, 300 mA, FBP), group B (100 kV, automatic mA, AIDR 3D) and group C (80kV, automatic mA, AIDR 3D). Image quality and radiation dose were evaluated for each group.For both cervical and intracranial vessels, CT attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were higher in the AIDR 3D groups. The difference in mean vascular noise was also statistically significant (p<0.001), with group B having the lowest value at 16.5±3.2 HU and group C having the highest at 19.1±2.9 HU. FBP reconstruction resulted in lower image-quality scores for the common carotid artery. Parenchymal image-quality scores also varied significantly different between groups with group C partially failing to meet the minimum standards for diagnostic use. For the middle cerebral artery, image-quality scores were significantly better in group A, although images from groups B and C also satisfied clinical diagnostic requirements. The image quality of the internal carotid artery was the best in group B. Image-quality scores between groups were not significantly different for the carotid sinus. Radiation doses in the groups using AIDR 3D were >70% lower than in the FBP group.AIDR 3D (100 kV, automatic modulation) provides optimal image quality of vascular and parenchymal tissues at significantly lower radiation doses (mSV) than FBP in craniocervical CTA. For cases in which highly accurate parenchymal assessment is not required, the tube voltage can be lowered to 80 kV to further decrease radiation dose.
科研通智能强力驱动
Strongly Powered by AbleSci AI