Clinical-CT environmental-radiomics for distinguishing peripheral lung cancer and inflammatory mass under background of chronic obstructive pulmonary disease
10.13929/j.issn.1003-3289.2024.07.015
- VernacularTitle:临床-CT环境影像组学鉴别慢性阻塞性肺疾病背景下周围型肺癌与肺炎性肿块
- Author:
Yingjian YE
1
,
2
;
Peng AN
Author Information
1. 湖北医药学院附属襄阳市第一人民医院影像科,湖北襄阳 441000
2. 湖北医药学院附属襄阳市第一人民医院内科,湖北襄阳 441000
- Keywords:
lung neoplasms;
pulmonary disease,chronic obstructive;
radiomics;
tomography,X-ray computed
- From:
Chinese Journal of Medical Imaging Technology
2024;40(7):1030-1035
- CountryChina
- Language:Chinese
-
Abstract:
Objective To observe the value of clinical-CT environmental-radiomics for distinguishing peripheral lung cancer(PLC)and inflammatory mass under the background of chronic obstructive pulmonary disease(COPD).Methods Data of 86 COPD patients with pathologically confirmed PLC(PLC group)and 155 COPD with inflammatory masses(inflammatory mass group)were retrospectively analyzed.The patients were divided into training set(n=170)and test set(n=71)at the ratio of 7∶3.Based on enhanced CT,the lesion ROI1(uneven enhancement area),ROI2(uniform enhancement area)and ROI3(tumor surrounding zone)were delineated,and the corresponding Radscore 1,2 and 3 were generated.Clinical,routine CT and environmental-radiomics data were compared between groups.Logistic regression analysis was performed,then clinical model,CT environmental-radiomics model and clinical-CT environmental-radiomics model were established,and their efficacy for distinguishing PLC and inflammatory mass were analyzed.Results Lesion morphology,enhancement mode,Radscore 2 and 3 were all impact factors for distinguishing PLC and pneumonia mass under background of COPD(all P＜0.05).The area under the curve(AUC)of the established clinical model,CT environmental-radiomics model and clinical-CT environmental-radiomics model for distinguishing PLC and pneumonia mass in COPD was 0.763,0.859 and 0.892 in training set,and was 0.729,0.843 and 0.882 in test set,respectively.AUC of clinical-CT environmental-radiomics model had the highest AUC(all P＜0.05),with the accuracy of 83.53％,sensitivity of 81.97％ and specificity of 84.40％.Conclusion Clinical-CT environmental-radiomics was helpful for distinguishing PLC and pneumonia mass under the background of COPD.
