Study on the feasibility of low-dose chest CT combined with deep learning reconstruction algorithm in the diagnosis of pediatric mycoplasma pneumonia
10.3969/j.issn.1672-8270.2024.06.003
- VernacularTitle:胸部低剂量CT联合深度学习重建算法在小儿支原体肺炎诊断中的可行性研究
- Author:
Xiu CHENG
1
;
Guihua LIU
;
Sirun YU
;
Dehong WU
;
Wen CHEN
;
Guan WANG
;
Chao LIU
Author Information
1. 湖北医药学院附属太和医院医学影像中心 十堰 442000
- Keywords:
Radiation dose;
Deep learning reconstruction;
Pediatric mycoplasma pneumonia;
Image quality
- From:
China Medical Equipment
2024;21(6):12-17
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the feasibility of 60 kV low-dose scanning technique on chest combined with ClearInfinity deep learning reconstruction algorithm in the diagnosis of pediatric mycoplasma pneumonia.Methods:A total of 132 pediatric patients,who admitted to Taihe Hospital Affiliated to Hubei Medical College and were diagnosed as mycoplasma pneumonia,were selected,and all of them underwent computed tomography(CT)scans on chest.They were randomly divided into routine dose group(66 cases),low dose ClearView and ClearInfinity group(66 cases).In the routine dose group,the tube voltage of CT scan on chest was 100 kV,and 50%ClearView iterative algorithm was adopted in this group.The tube voltage of CT scan on chest was 60kV in low dose ClearView and ClearInfinity group,and 50%ClearView iterative algorithm and 50%ClearInfinity deep learning reconstruction algorithm were used respectively to conduct reconstruction.The difference of radiation dose among the three groups was compared.The CT values and standard deviation(SD)values,signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)of the region of interest(ROI)of the images of 3 groups were measured and calculated.The images were subjectively evaluated by two diagnostic attending physicians with 10 years of work experience,and the Kappa test was adopted to analyze the consistency of the score results.Results:Compared with the routine dose group,the volume CT dose index(CTDIvol)values,dose-length product(DLP)values and effective radiation dose(ED)values of the low dose ClearView group and ClearInfinity group reduced respectively by 87.58%,87.24%and 88.00%,and the differences were statistically significant(t=4 584.07,63.73,61.27,P<0.01).The noise values of left and right lung of the routine dose group were significantly lower than those of the low dose ClearView group,while were significantly higher than those of ClearInfinity group,and the differences were significant(Z=-9.912,-7.013,P<0.01),and the difference of them between low dose ClearView group and ClearInfinity group was significant(Z=-9.912,P<0.01).The SNR and CNR of left and right lung of low dose ClearView group were significantly lower than those of the routine dose group,with statistically significant(t=-34.810,5.522,P<0.01),while these of the low dose ClearInfinity group were significant higher than them of the routine dose group(t=3.544,-8.674,P<0.05),respectively.The two attending physicians had favorable consistency in the subjective evaluation for images(Kappa>0.75,P<0.01).The subjective score of the routine dose group was not significantly different with that of the low dose ClearInfinity group(P>0.05),but was significantly better than that of the low dose ClearView group(Z=-6.425,P<0.01).Conclusion:For pediatric patients with mycoplasma pneumonia,the 60 kV low dose CT on chest combined with ClearInfinity deep learning reconstruction algorithm can ensure image quality on the premise of reducing radiation,which can ensure the diagnostic effect.
