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| Analysis of CT Segmental Texture Characteristics and Relationship with Pulmonary Function Indices in COPD Patients |
| WANG Caicai, WANG Yuan, LI Jiangtao, et al |
| Hebei Chest Hospital, Hebei Shijiazhuang 050000, China |
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Abstract Objective: To analyze the CT segmented texture characteristics and the relationship with pulmonary function indicators in patients with chronic obstructive pulmonary disease (COPD).Methods: From March 2022 to March 2023, 80 patients with COPD were selected as the study subjects (study group), and 60 healthy people who received physical examination in the hospital were included in the control group. All patients underwent high-resolution CT scans and CT segmented texture characteristics and pulmonary function tests. The pulmonary function indicators [forced expiratory volume in the first second as a percentage of predicted value FEV1%), forced vital capacity (FVC), FEV1/FVC] and texture characteristics of the whole lung region and the outer lung region were compared between the two groups The correlation between CT texture characteristics and pulmonary function indicators was analyzed.Results: There were no statistical differences in age and gender between groups (P>0.05). The FEV1%, FVC, and FEV1/FVC in the study group were lower than those in the control group (P<0.05). The whole lung GLCM contrast, whole lung GLCM entropy, whole lung GLSZM area size non-uniformity, outer lung GLCM contrast, outer lung GLCM entropy, outer lung GLSZM area size non-uniformity, and outer lung LBP eigenvalue in the study group were higher than those in the control group (P<0.05). Pearson correlation analysis showed that whole lung GLCM contrast, whole lung GLCM entropy, whole lung GLSZM area size non-uniformity, outer lung GLCM contrast, outer lung GLCM entropy, outer lung GLSZM area size non-uniformity, and outer lung LBP eigenvalue were negatively correlated with FEV1%, FVC and FEV1/FVC (P<0.05). Multivariate regression analysis showed that whole lung GLCM contrast, whole lung GLCM entropy, whole lung GLSZM area size non-uniformity, outer lung GLCM contrast, outer lung GLCM entropy, outer lung GLSZM area size non-uniformity, and outer lung LBP eigenvalue had significant effects on FEV1%, FVC and FEV1/FVC in patients with COPD (P<0.05), and the R2 values were 0.682, 0.657 and 0.715 respectively, suggesting that the model had high goodness of fit.Conclusion: CT segmented texture characteristics are closely related to pulmonary function indicators of COPD patients. The GLCM contrast, GLCM entropy, GLSZM area size non-uniformity, and LBP eigenvalue of the whole lung and outer lung can be used as important reference indicators for imaging evaluation and early diagnosis of COPD.
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[1] 周璇,邹娟,谢莉,等.慢性阻塞性肺疾病急性加重期患者CT肺血管参数与肺功能及预后相关性分析[J].陕西医学杂志,2023,52(5):587-617.
[2] 纪蒙蒙,张晓辰,李永,等.不同时期慢性阻塞性肺疾病患者呼吸双相计算机断层扫描征象及相关定量参数与患者肺功能相关性研究[J].临床军医杂志,2024,52(2):166-168.
[3] 王雯婷,王晓华,贺蓓,等.基于吸呼双相CT定量参数的慢性阻塞性肺疾病影像学表型研究[J].中华医学杂志,2021,101(28):2242-2245.
[4] Makimoto K,Hogg JC,Bourbeau J,et al.CT Imaging with machine learning for predicting progression to COPD in individuals at risk[J].Chest,2023,164(5):1139-1149.
[5] 蔡柏蔷.慢性阻塞性肺疾病诊断,处理和预防全球策略(2017 GOLD报告)解读[J].国际呼吸杂志,2017,37(1):6-17.
[6] 兰长青,王洁,黄梅萍,等.CT肺气肿指数及空间分布对慢性阻塞性肺疾病肺损伤的评估价值[J].中国临床医学影像杂志,2021,32(5):320-325.
[7] 王益德,田宗祥,李争,等.基于倾向性评分匹配的结核相关阻塞性肺疾病患者肺功能及影像学特征分析[J].中国全科医学,2022,25(14):1718-1723.
[8] 阴玮灵,沈敏,牛媛,等.双气相定量CT的肺空气体积比值对吸烟者慢性阻塞性肺病的诊断价值[J].影像诊断与介入放射学,2023,32(1):43-48.
[9] 韩春杰.COPD合并慢性肺源性心脏病患者临床特点及MSCT影像诊断价值[J].中国CT和MRI杂志,2022,20(11):58-60.
[10] Sharma M,Wyszkiewicz PV,Matheson AM,McCormack DG,Parraga G.Chest MRI and CT predictors of 10-year all-cause mortality in COPD[J].COPD,2023,20(1):307-320.
[11] Kovacs G,Avian A,Bachmaier G,et al.Severe pulmonary hypertension in COPD: impact on survival and diagnostic approach[J].Chest,2022,162(1):202-212.
[12] Diaz AA,Orejas JL,Grumley S,et al.Airway-occluding mucus plugs and mortality in patients with chronic obstructive pulmonary disease[J].JAMA,2023,329(21):1832-1839. |
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2024, Vol. 30 
