Study on the pattern of pulmonary vascular remodeling in patients with chronic obstructive pulmonary disease based on artificial intelligence technology
10.3760/cma.j.cn112149-20231207-00456
- VernacularTitle:基于人工智能技术研究慢性阻塞性肺疾病患者肺血管重塑的规律
- Author:
Mengyi SONG
1
;
Rui LI
;
Ronghua WANG
;
Linning E
Author Information
1. 山西白求恩医院（山西医学科学院）放射科，太原 030032
- Keywords:
Pulmonary disease, chronic obstructive;
Pulmonary vascular;
Tomography, X-ray computed
- From:
Chinese Journal of Radiology
2024;58(8):813-821
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the pattern of pulmonary vascular remodeling in patients with chronic obstructive pulmonary disease (COPD) using artificial intelligence technology based on chest CT images.Methods:This was a cross-sectional study. The clinical and imaging data of 257 patients with stable COPD who underwent chest high resolution CT (HRCT) and pulmonary function tests (PFT) from January 2018 to October 2022 at Shanxi Bethune Hospital were retrospectively analyzed. In addition, 28 healthy individuals with normal HRCT and PFT were collected in the same period as a control group. According to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) grading criteria, COPD patients were classified into 31 cases of GOLD 1, 116 cases of GOLD 2, 82 cases of GOLD 3, and 28 cases of GOLD 4. FACT digital lung software was used to automatically segment the pulmonary arteries and pulmonary veins of all the cases, and to calculate the relevant pulmonary vascular parameters, including total lung volume (TLV), vessel volumes at all levels [cross-sectional area less than 5 mm 2 (CSA <5), between 5 and 10 mm 2 (CSA 5-10), and more than 10 mm 2 (CSA >10)], number of vascular branches, and vascular density (pulmonary vascular volume/TLV). Percentage of emphysema (%LAA) and pulmonary artery diameter/aortic diameter (PAD/AD) were calculated for all cases. ANOVA or Kruskal-Wallis H test was used for multiple intergroup comparisons, and LSD test or Bonferroni correction was used for within-group pairwise comparisons. Spearman correlation test was conducted to examine the relationship between CT pulmonary vascular parameters and pulmonary function parameters, as well as %LAA, in both the control group and the COPD group. Results:Differences in age, body mass index, pulmonary function parameters, %LAA and PAD/AD were statistically significant among the 5 groups ( P<0.001). Differences in overall pulmonary vascular density parameters were statistically significant among the 5 groups ( P<0.05). Differences in pulmonary arterial density parameters among the 5 groups with CSA <5, CSA 5-10, and CSA >10 were statistically significant ( P<0.05). The pulmonary arterial density values of GOLD 1 CSA <5, CSA 5-10 and CSA >10 were higher than those of the control group, and then showed a decreasing trend with the increase of COPD severity. The differences in pulmonary venous density parameters among the 5 groups with CSA< 5, CSA 5-10, and CSA >10 were statistically significant ( P<0.001), and the CSA 5-10 pulmonary venous density was higher in GOLD 1 patients than in the control group, and the remaining pulmonary venous densities showed a gradual decreasing trend with the increase in the severity of COPD. The number of arterial and venous vascular branches/TLV tended to decrease in the control group, GOLD 1, GOLD 2, GOLD 3, and GOLD 4 patients ( P<0.001). Pulmonary vascular density parameters were positively correlated with all PFT parameters ( r=0.138-0.510, P<0.05), and negatively correlated with %LAA ( r=-0.340--0.671, P<0.001); PAD/AD was negatively correlated with PFT parameters ( r=-0.208--0.286, P<0.001) and positively correlated with %LAA ( r=0.131, P<0.05). Conclusion:Various pulmonary vascular density parameters can be quantitatively analyzed by artificial intelligence technology based on chest CT images, which can reveal the changing pattern of pulmonary vascular remodeling in COPD patients.
