Z. Gao, Wang Yigeng, Haijie Li, Jiangfen Wu, Z. Ye
{"title":"Phantom study in the quality control of low dose solid pulmonary nodule CT based on radiomics analysis","authors":"Z. Gao, Wang Yigeng, Haijie Li, Jiangfen Wu, Z. Ye","doi":"10.3760/CMA.J.ISSN.1005-1201.2020.01.012","DOIUrl":null,"url":null,"abstract":"Objective \nTo investigate the value of radiomics in image quality control with low-dose CT examination of solid pulmonary nodules. \n \n \nMethods \nImages were acquired on CT750 HD scanner, and chest pulmonary nodules phantom were scanned at different tube voltage and tube current. The radiation dose CTDIvol under different scanning conditions were recorded, as well as CNR and SNR of each scanning sequence. The variation of radiation dose, noise, tube voltage and tube current were analyzed. All data were analyzed by radiomics analysis software. R language statistics software was adopted to analyze the extracted features by principal component analysis (PCA), and the characteristic parameters with the largest contribution rate to image quality were selected for analysis. One-way ANOVA was used to analyze all the important characteristic parameters to reveal the difference of characteristic parameters under different tube voltages. Finally, the post-test method was used to find out the differences among different tube voltage groups. \n \n \nResults \nRadiation dose rised linearly with the increase of tube current and tube voltage. Although the overall change trend of SNR and CNR in pulmonary nodules was linearly related to the change of tube voltage and tube current, there was no clear change trend threshold at low dose, which could not accurately evaluate the image quality under low radiation. Both CNR and SNR cannot evaluate the image quality effectively, and have no practiced value for optimizing the low dose scanning parameters. There main components including Uniformity, Voxel Value Sum, and Haralick Correlation extracted by radiomics analysis software were proved to play a critical role in image quality control. The cumulative contribution rate of variance was 89.20% and the eigen values were greater than 1. Uniformity curve of characteristic parameter showed that the trend of change was correlated with the change of tube voltage and tube current, and the stability and consistency were good. Uniformity one-way ANOVA analysis showed that when the tube voltage reduced from 140 to 120 kVp, there was no difference (P=0.117) in the uniformity, while from 120 to 80 kVp, significant differences revealed (P<0.001). Considering tube current, no significant variation was observed in uniformity when current was greater than 90 mA, which indicated that tube current of 90 mA could lead to better image quality. \n \n \nConclusion \nRadiomics analysis can effectively evaluate and control the CT image quality of low dose solid pulmonary nodules. \n \n \nKey words: \nRadiation dosage; Pulmonary nodule; Phantoms","PeriodicalId":39377,"journal":{"name":"Zhonghua fang she xue za zhi Chinese journal of radiology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Zhonghua fang she xue za zhi Chinese journal of radiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3760/CMA.J.ISSN.1005-1201.2020.01.012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
Objective
To investigate the value of radiomics in image quality control with low-dose CT examination of solid pulmonary nodules.
Methods
Images were acquired on CT750 HD scanner, and chest pulmonary nodules phantom were scanned at different tube voltage and tube current. The radiation dose CTDIvol under different scanning conditions were recorded, as well as CNR and SNR of each scanning sequence. The variation of radiation dose, noise, tube voltage and tube current were analyzed. All data were analyzed by radiomics analysis software. R language statistics software was adopted to analyze the extracted features by principal component analysis (PCA), and the characteristic parameters with the largest contribution rate to image quality were selected for analysis. One-way ANOVA was used to analyze all the important characteristic parameters to reveal the difference of characteristic parameters under different tube voltages. Finally, the post-test method was used to find out the differences among different tube voltage groups.
Results
Radiation dose rised linearly with the increase of tube current and tube voltage. Although the overall change trend of SNR and CNR in pulmonary nodules was linearly related to the change of tube voltage and tube current, there was no clear change trend threshold at low dose, which could not accurately evaluate the image quality under low radiation. Both CNR and SNR cannot evaluate the image quality effectively, and have no practiced value for optimizing the low dose scanning parameters. There main components including Uniformity, Voxel Value Sum, and Haralick Correlation extracted by radiomics analysis software were proved to play a critical role in image quality control. The cumulative contribution rate of variance was 89.20% and the eigen values were greater than 1. Uniformity curve of characteristic parameter showed that the trend of change was correlated with the change of tube voltage and tube current, and the stability and consistency were good. Uniformity one-way ANOVA analysis showed that when the tube voltage reduced from 140 to 120 kVp, there was no difference (P=0.117) in the uniformity, while from 120 to 80 kVp, significant differences revealed (P<0.001). Considering tube current, no significant variation was observed in uniformity when current was greater than 90 mA, which indicated that tube current of 90 mA could lead to better image quality.
Conclusion
Radiomics analysis can effectively evaluate and control the CT image quality of low dose solid pulmonary nodules.
Key words:
Radiation dosage; Pulmonary nodule; Phantoms