1.Evaluation of air trapping in lung using biphasic quantitative CT in young asymptomatic females
Zhiran LIANG ; Meijuan SHI ; Haifeng DUAN ; Bingqiang XU ; Hongmei WANG ; Jiayin TONG ; Chenwang JIN ; Youmin GUO
Journal of Practical Radiology 2017;33(12):1831-1835
Objective To evaluate the extent and anatomic distribution of air trapping in lung in young asymptomatic female subjects to achieve early diagnosis of small airway diseases.Methods Fifty young females with normal pulmonary function were included retrospectively in this study.All subjects underwent both inspiratory and expiratory CT scans,the percentage of the area of air trapping(AT)and the percentage of the area of emphysema(Emph)were quantitatively analyzed.Comparison between bilateral lungs was analyzed using independent-samples t test;Comparisons among lobes were done using one-way ANOVA or Kruskal-Wallis rank sum test;Pairwise comparisons between lobes were conducted using LSD test or paired comparison;The effects of each lobe on AT were analyzed using Spearman's rank correlation coefficient,simple linear regression and multiple stepwise regression.Results There was a certain degree of air trapping in lung and a small amount of emphysema in young asymptomatic females.Air trapping was mainly located in the right middle lobe (RML)and bilateral upper lobes.The ratio of air trapping to volume was the highest in RML and the change of air trapping in the bilateral upper lobes had the greatest influence on the air trapping degree of the whole lung.Conclusion There is a certain degree of air trapping in lung in young asymptomatic females.The occurrence and development of air trapping in RML may be a sensitive biomarker for the early detection of pathophysiological changes in small airway diseases using imaging procedures.
2.Establishment and preliminary application of a voxel-based method for the quantitative analysis of air trapping
Chenwang JIN ; Zhiran LIANG ; Haifeng DUAN ; Meijuan SHI ; Xia WEI ; Xianxian CAO ; Xiaoyan GAO ; Jiantao PU ; Youmin GUO
Chinese Journal of Radiology 2019;53(1):21-25
Objective To establish and validate a voxel-based method for the quantitative detection of air trapping (AT),and to explore its diagnostic value by preliminarily apply this method in chronic obstructive pulmonary disease (COPD) patients.Methods From March 2015 to February 2016,fifty healthy young volunteers and eighteen COPD patients who underwent both end-inspiratory and end-expiratory CT were included from the Digital Lung Multi-center Study.The quantitative parameters of AT and emphysema were measured by both the voxel-based quantitative method and the conventional threshold method,respectively.All subjects underwent pulmonary function examination within 3 days after CT examination.For healthy volunteers,paired sample rank-sum test was used to compare the difference of quantitative parameters between voxel-based method and threshold method,Spearman rank correlation analysis was used to investigate the correlation between quantitative parameters of the two methods and pulmonary function.For COPD patients,the distribution and extent of AT and emphysema in patients with similar degree of pulmonary function (PFT) injury were observed.Results There were varying degrees of AT in the asymptomatic youth,with a median value of 5.70% for the voxel-based method and with a median value of 7.96% for the conventional threshold method,there was significant difference(Z=-4.015,P<0.001).The correlation between AT and emphysema parameters of the voxel-based method and PFT parameters (r=-0.399 and-0.494,-0.335 and-0.439 separately,P<0.05) were higher than that of the conventional threshold method,respectively (r=-0.357 and-0.453,-0.284 and-0.391,respectively;all P<0.05).Furthermore,the voxel-based method can classify COPD patients with similar degree of pulmonary function injury into three subtypes:AT-dominant,emphysema-dominant,and mixed.Conclusions The voxel-based AT quantitative measurement method not only has high sensitivity and accuracy,but also provides imaging phenotype for the diagnosis of COPD and provides assistant decision-making for clinical management.
3.Development and validation on death risk model of Stanford type A aortic dissection based on Cox regression
Zhiran GUO ; Sufang HUANG ; Qiansheng WU ; Yaru XIAO ; Miqi LI ; Quan ZHOU ; Xiaorong LANG ; Danni FENG
Chinese Critical Care Medicine 2021;33(11):1315-1321
Objective:To construct the prediction model of death risk of Stanford type A aortic dissection (AAD) based on Cox proportional risk regression model.Methods:AAD patients who were diagnosed and received surgical treatment admitted to the department of cardiothoracic surgery of Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology from January 1st, 2019 to April 30th, 2020 were enrolled. The general situation, clinical manifestations, pre-hospital data, laboratory examination and imaging examination results of the patients were collected. The observation period was up to the death of the patients or ended on April 30th, 2021. They were divided into the model group and the verification group according to the ratio of 7∶3. Lasso method was used to screen prognostic variables from the data of the modeling group, and multivariate Cox regression analysis was included to construct the AAD death risk prediction model, which was displayed by nomogram. The receiver operator characteristic curve (ROC curve) was used to evaluate the discrimination of the model, the calibration curve to evaluate the accuracy of the model, and the clinical decision curve (DCA) to evaluate the effectiveness of the model.Results:A totel of 454 patients with AAD were finally included, and the mortality was 19.4% (88/454). Lasso regression analysis was used to screen out 10 variables from the data of 317 patients in the model group, and the prediction model of death risk was constructed: 0.511×abdominal pain+1.061×syncope+0.428×lower limb pain/numbness-0.365×emergency admission-1.933×direct admission-1.493×diagnosis before referral+0.662×preoperative systolic blood pressure (SBP) < 100 mmHg (1 mmHg = 0.133 kPa)+0.632×hypersensitivity cardiac troponin I (hs-cTnI) > 34.2 ng/L+1.402×De Bakey type+0.641× pulmonary infection+1.472×postoperative delirium. The area under the ROC curve (AUC) and 95% confidence interval (95% CI) of the AAD death risk prediction model were 0.873 (0.817-0.928), and that of the verification group was 0.828 (0.740-0.916). DCA showed that the net benefit value of the model was higher. The calibration curve showed that there was a good correlation between the actual observation results and the model prediction results. Conclusion:The AAD death risk prediction model based on abdominal pain, syncope, lower limb pain/numbness, mode of admission, diagnosis before referral, preoperative SBP < 100 mmHg, hs-cTnI > 34.2 ng/L, De Bakey type , pulmonary infection, and postoperative delirium can effectively help clinicians identify patients at high risk for AAD, evaluate their postoperative survival and timely adjust treatment strategies.
4.Correlation between airway remodeling and lung function in adult-onset eosinophilic asthma
Tingting HAN ; Zhiran LIANG ; Meijuan SHI ; Liyu HE ; Chenwang JIN ; Youming GUO
Journal of Xi'an Jiaotong University(Medical Sciences) 2021;42(5):730-734
【Objective】 To investigate the airway parameters of adult-onset eosinophilic asthma (EA) and analyze the correlation between airway remodeling and lung function by quantitative CT. 【Methods】 From March 2015 to November 2016, totally 94 subjects from the “FACT-Digital Lung” Multi-research Center were divided into three groups: 30 normal subjects, 33 EA patients and 31 non-eosinophilic asthma (NEA) patients. We measured and recorded the bronchial parameters of RB1, LB1+2, RB10, and LB10, and small airway disease parameters. The indicators for quantitative evaluation of bronchial parameters include lumen area (LA), wall thickness (WT), wall area (WA), and wall area percentage (WA%). The parameters for the quantitative assessment of small airway disease included the percentage of inspiratory voxels below -950HU (IN