人工智能定量分析在CTD-ILD诊断和分级中的应用研究
Artificial intelligence quantitative evaluation in diagnosis and grading of CTD-ILD
储晨 1方宇 1孙艺 2王春 3隗英 4石峰 4辛小燕 1赵盛楠3
作者信息
- 1. 南京大学医学院附属鼓楼医院医学影像科 江苏 南京 210008
- 2. 南京中医药大学鼓楼临床医学院医学影像科 江苏 南京 210008
- 3. 南京大学医学院附属鼓楼医院风湿免疫科 江苏 南京 210008
- 4. 上海联影智能医疗科技有限公司研发部 上海 200232
- 折叠
摘要
目的 探讨人工智能定量分析在结缔组织病相关间质性肺疾病(CTD-ILD)诊断和分级中的应用.方法 选取CTD-ILD 128 例患者,所有患者均进行CT扫描和肺功能检查,分为轻度组和重度组.独立样本t检验和ROC分析鉴别轻度组和重度组.方差分析和LSD检验鉴别各组病变成分.Spearman 秩和检验比较各参数与肺功能等级的相关性.结果 重度组肺体积均显著小于轻度组;重度组肺病变体积和百分比均显著大于轻度组(P≤0.001).ROC曲线显示肺病变体积和百分比指标具有较高诊断价值(AUC值均>0.700).各组病变成分之间均具有显著性差异(P<0.001).各参数与肺功能等级均具有相关性.结论 人工智能在CTD-ILD患者的定量分析中具有一定的优势,对患者的诊断和分级能够提供价值.
Abstract
Objective To explore the value of artificial intelligence in quantitative of connective tissue disease-associated in-terstitial lung disease(CTD-ILD).Methods A total of 128 CTD-ILD patients were prospectively enrolled and divided into mild and severe groups.The independent sample t test and ROC analysis were used to distinguish the parameters of pneumonia analysis in mild and severe groups.The analysis of variance and LSD test were used to compare the lesion components.The spear-man rank analysis was used to compare the correlation between all parameters and pulmonary function grades.Results The lung volume of severe groups was significantly higher than mild groups(P value were≤0.001).The ROC curves showed that the volume and percentage indexes of the lung were of high diagnostic value(AUCs>0.700).There were significantly differences be-tween different lesion components.The parameters were correlated with the pulmonary function grades.Conclusion Artificial intelligence has advantages in the quantitative analysis of CTD-ILD patients and can provide value for the diagnosis and grading of patients.
关键词
间质性肺疾病/结缔组织病/人工智能/体层摄影术,X线计算机Key words
Interstitial lung disease/Connective tissue disease/Artificial intelligence/Tomography/X-ray computed引用本文复制引用
基金项目
国家自然科学基金(81871282)
江苏省"双创博士"人才引进计划(JSSCBS20211495)
出版年
2024
NETL
NSTL
万方数据