Background:Computed tomography(CT)plays a great role in characterizing and quantifying changes in lung structure and function of chronic obstructive pulmonary disease(COPD).This study aimed to explore the performance ...Background:Computed tomography(CT)plays a great role in characterizing and quantifying changes in lung structure and function of chronic obstructive pulmonary disease(COPD).This study aimed to explore the performance of CT-based whole lung radiomic in discriminating COPD patients and non-COPD patients.Methods:This retrospective study was performed on 2785 patients who underwent pulmonary function examination in 5 hospitals and were divided into non-COPD group and COPD group.The radiomic features of the whole lung volume were extracted.Least absolute shrinkage and selection operator(LASSO)logistic regression was applied for feature selection and radiomic signature construction.A radiomic nomogram was established by combining the radiomic score and clinical factors.Receiver operating characteristic(ROC)curve analysis and decision curve analysis(DCA)were used to evaluate the predictive performance of the radiomic nomogram in the training,internal validation,and independent external validation cohorts.Results:Eighteen radiomic features were collected from the whole lung volume to construct a radiomic model.The area under the curve(AUC)of the radiomic model in the training,internal,and independent external validation cohorts were 0.888[95%confidence interval(CI)0.869–0.906],0.874(95%CI 0.844–0.904),and 0.846(95%CI 0.822–0.870),respectively.All were higher than the clinical model(AUC were 0.732,0.714,and 0.777,respectively,P<0.001).DCA demonstrated that the nomogram constructed by combining radiomic score,age,sex,height,and smoking status was superior to the clinical factor model.Conclusions:The intuitive nomogram constructed by CT-based whole-lung radiomic has shown good performance and high accuracy in identifying COPD in this multicenter study.展开更多
基金supported by the National Key Research and Development Program of China(2022YFC2010002,2022YFC2010000 and 2022YFC2010005)the National Natural Science Foundation of China(82171926,81930049 and 82202140)+3 种基金the Medical Imaging Database Construction Program of National Health Commission(YXFSC2022JJSJ002)the Clinical Innovative Project of Shanghai Changzheng Hospital(2020YLCYJ-Y24)the Program of Science and Technology Commission of Shanghai Municipality(21DZ2202600)the Shanghai Sailing Program(20YF1449000).
文摘Background:Computed tomography(CT)plays a great role in characterizing and quantifying changes in lung structure and function of chronic obstructive pulmonary disease(COPD).This study aimed to explore the performance of CT-based whole lung radiomic in discriminating COPD patients and non-COPD patients.Methods:This retrospective study was performed on 2785 patients who underwent pulmonary function examination in 5 hospitals and were divided into non-COPD group and COPD group.The radiomic features of the whole lung volume were extracted.Least absolute shrinkage and selection operator(LASSO)logistic regression was applied for feature selection and radiomic signature construction.A radiomic nomogram was established by combining the radiomic score and clinical factors.Receiver operating characteristic(ROC)curve analysis and decision curve analysis(DCA)were used to evaluate the predictive performance of the radiomic nomogram in the training,internal validation,and independent external validation cohorts.Results:Eighteen radiomic features were collected from the whole lung volume to construct a radiomic model.The area under the curve(AUC)of the radiomic model in the training,internal,and independent external validation cohorts were 0.888[95%confidence interval(CI)0.869–0.906],0.874(95%CI 0.844–0.904),and 0.846(95%CI 0.822–0.870),respectively.All were higher than the clinical model(AUC were 0.732,0.714,and 0.777,respectively,P<0.001).DCA demonstrated that the nomogram constructed by combining radiomic score,age,sex,height,and smoking status was superior to the clinical factor model.Conclusions:The intuitive nomogram constructed by CT-based whole-lung radiomic has shown good performance and high accuracy in identifying COPD in this multicenter study.
文摘目的 研究敦煌呼吸妙诀吐纳导引操对改善老年慢性阻塞性肺疾病(chronic obstructive pulmonary disease,COPD)稳定期患者肺康复的临床疗效。方法 将70例COPD患者按照随机数字表法分为试验组(n=35)和对照组(n=35)。对照组进行常规治疗及康复训练,试验组在对照组干预基础上进行2个月的敦煌呼吸妙诀吐纳导引操训练。比较两组患者干预前后的肺功能指标、6 min步行试验(6-minute walking test,6MWT)步行距离、改良版英国医学研究委员会呼吸困难量表(modified Medical Research Council dyspnea scale,mMRC)评分以及慢性阻塞性肺疾病评估测试(COPD assessment test,CAT)评分。结果 干预后,试验组患者第1秒用力呼气容积(forced expiratory volume in one second,FEV1)、用力肺活量(forced vital capacity,FVC)、FEV1/FVC较对照组明显升高(P均<0.05),6MWT步行距离较对照组明显增加,mMRC评分、CAT评分较对照组明显降低(P均<0.05)。结论 敦煌呼吸妙诀吐纳导引操对加速老年COPD患者肺康复、缓解呼吸困难及改善肺功能效果明显,具有较高的临床应用价值。
