Improve image resolution in low-dose pediatric chest CT scans with combination of adaptive statistical iterative reconstruction and sharp recon kernel
10.13929/j.1003-3289.201610011
- VernacularTitle:自适应迭代重建技术结合高分辨算法提高儿童低剂量胸部CT肺脏病变显示的能力
- Author:
Jihang SUN
;
Fanning WANG
;
Xiaomin DUAN
;
Yong LIU
;
Zhimin LIU
;
Lei SONG
;
Yun PENG
- Keywords:
Tomography,X-ray computed;
Adaptive statistical iterative reconstruction;
Child;
Chest
- From:
Chinese Journal of Medical Imaging Technology
2017;33(5):773-777
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the value of adaptive statistical iterative reconstruction (ASIR) and a sharp recon kernel to obtain high resolution pulmonary images in low-dose pediatric chest CT scans.Methods Totally 42 children underwent low-dose chest CT scans with ASIR were included.Age dependent noise index (NI) was used for dose optimization:NI=12 for 0-12 months old,NI=15 for ＞1 2 years old,NI=17 for 3-6 years old and NI=20 for ≥7 years old.Images were reconstructed to 0.625 mm using different recon kernels:Soft,Standard,Lung,and Chest kernel.ASIR blending was varied from 0 100％ to provide balanced image noise and spatial resolution.Two radiologists independently evaluated images for normal lung structures,abnormal CT findings and image noise on a 5 point scale with 3 being clinically acceptable.The best kernel,as well as the match with the best ASIR weight were analyzed statistically.Results CT images with lung kernel and ASIR 60％ were rated substantially better than those kernel.Conclusion ASIR 60％ with a sharp lung kernel can significantly improve image quality in low dose pediatric chest CT scans.
