Application value of iterative reconstruction with CTA to intractable headache patients

Abstract

Application value of iterative reconstruction with computed tomographic angiography (CTA) in the patients with intractable headache was investigated. One hundred and eighty patients with headache, who were admitted and treated in Cangzhou Central Hospital, were selected to undergo CTA scan. The patients were divided into group A, B and C according to different scanning conditions and data reconstruction techniques. In group A, the scanning parameters were 120 kV and 300 mA, and filtered back projection (FBP) algorithm was used for data reconstruction. In group B, the scan parameters were 100 kV and automatic milliamperes. Further, adaptive iterative dose reduction via three-dimensional processing (AIDR-3D) was used for data reconstruction. In group C, the scan parameters were 80 kV with automatic milliamperes, and AIDR-3D technique was utilized for data reconstruction. The CT value, noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), subjective assessment score of image quality and radiation dose of the three groups of images were compared. There were significant differences in CT values, standard deviation (SD) values, SNRs and CNRs of different vessel segments and muscles among the three groups (P<0.05). The image assessment scores at the levels of the atlas and C7 vertebra as well as those of the brain parenchyma in the three groups had notable differences (P<0.05). However, they showed no differences at the level of the C4 vertebra (P>0.05). Further, significant differences were observed in volume computed tomography dose index (CTDIvol), dose-length product (DLP) and effective dose (ED) (P<0.05). In conclusion, for patients with intractable headache, the image quality of the CTA scan using AIDR-3D reconstruction method showed better results over FBP reconstruction method. Further, best results were observed when the scan parameters were 100 kV, automatic milliamperes and the data reconstruction was performed by AIDR-3D.