Value of low-dose spiral CT visual subtypes and quantitative parameters in predicting chronic obstructive pulmonary disease
10.3760/cma.j.cn112149-20221201-00959
- VernacularTitle:低剂量CT视觉亚型联合定量参数预测慢性阻塞性肺疾病的价值
- Author:
Junhong LU
1
;
Zhicong WANG
Author Information
1. 厦门大学附属第一医院放射科，厦门 361003
- Keywords:
Pulmonary disease, chronic obstructive;
Tomography, X-ray computed;
Visual subtypes;
Low attenuation area;
Diagnostic efficacy
- From:
Chinese Journal of Radiology
2023;57(10):1068-1073
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the value of low dose CT visual subtypes and quantitative parameters in predicting chronic obstructive pulmonary disease (COPD).Methods:The clinical and imaging data of 172 patients with smoking or previous smoking who visited the First Affiliated Hospital of Xiamen University from January 2021 to March 2022 due to cough, expectoration or shortness of breath/difficulty were analyzed retrospectively. All patients underwent pulmonary function testing and CT examinations. According to the diagnostic criteria of the Global Initiative for COPD, 172 patients were divided into a non COPD group (79 cases) and a COPD group (93 cases). The visual subtypes grading of the patient′s images were analyzed and the percentage of low attenuation area (LAA)-950, bronchial wall thickness (WT), and lumen area percentage (WA%) on CT images were measured. Visual subtype grading and CT parameters were compared between the 2 groups using the Mann-Whitney U test, and statistically significant differences were included in a multifactorial logistic regression analysis to screen for independent risk factors predicting COPD. Finally, a logistic prediction model of clinical features combined with CT imaging features was constructed, and the area under the curve (AUC) of the receiver operating characteristic curves was used to analyze the model to predict the efficacy of COPD. Results:The age and proportion of cough and sputum in the COPD group were higher than those in the non COPD group, and the body mass index was lower than that in the non COPD group ( P<0.05). In terms of imaging features, there were statistically significant differences in visual subtypes grading, LAA-950, WT, and WA% between the COPD group and the non COPD group ( P<0.001). Logistic regression analysis showed age (OR=1.06, 95%CI 1.02—1.10, P=0.002), expectoration (OR=2.86, 95%CI 1.37—5.97, P=0.005), and visual subtype grading (OR=1.73, 95%CI 1.30—2.30, P<0.001) were independent risk factors for predicting COPD. The final logistic prediction model was jointly constructed with age, body mass index, cough/sputum, imaging visual subtype grading, LAA-950, and WA%, and its AUC for predicting COPD was 0.903 with a sensitivity of 82.8% and a specificity of 81.0%. Conclusion:The combined clinical features of LAA-950, visual subtype grading and WA% based on low-dose CT show good clinical value in diagnosing COPD.
