Improving image quality with iterative reconstruction algorithm in chest CT for necrotizing pneumonia pediatrics
TIAN Hongwei
SUN Jihang
HAN Zhonglong
HUO Aihua
HONG Tianyu
WANG Wei
PENG Yun
Abstract：Objective To evaluate two kinds of iterative reconstruction algorithm compared to the traditional filtered back-projection (FBP) algorithm for the identification of low dose CT children's lung necrotic lesions.Methods 73 children (age ranging from 2 months to 12 years,median of 4 years) who underwent low dose CT scans were included.Images were retrospectively reconstructed into thin slice thickness of 0.625 mm using model-based iterative reconstruction (MBIR),adaptive statistical iterative reconstruction (ASIR) and FBP,respectively.The subjective quality of the images was independently evaluated by two radiologists using a 4-scale score including whole image quality and necrotic lesion quality.CT value and image noise in the lesion,consolidation and normal lung were measured,Contrast-to-noise ratios (SNR) were calculated.Results The subjective scores of whole image and necrotized lesions were 3.71 ± 0.45 and 4.00 ± 0.00 with MBIR,better than ASIR and FBP images.In terms of objective noise,the lesion noises were 14.71 ±3.85,25.68 ±6.33,35.78 ± 8.87 for MBIR,ASIR and FBP image,CNR contrast to consolidation were 4.03 ± 0.98,2.38 ± 0.75,1.57 ± 0.41,and CNR contrast to lung were 41.94 ± 10.03,29.32 ±8.14,20.47 ± 4.69.Conclusion Iterative reconstruction algorithm can improve the recognition ability of necrotic lesion in children low dose CT,in which the MBIR image is the best.
Keywords：TomographyX-ray computerIterative reconstructionChildrenlung
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 1462-1465 )