清晨好,您是今天最早来到科研通的研友!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您科研之路漫漫前行!

Machine Learning and CT Texture Features in Ex-smokers with no CT Evidence of Emphysema and Mildly Abnormal Diffusing Capacity

DLCO公司 医学 肺活量测定 扩散能力 慢性阻塞性肺病 肺容积 曲线下面积 放射科 核医学 心脏病学 内科学 肺功能 哮喘
作者
Maksym Sharma,Miranda Kirby,David G. McCormack,Grace Párraga
出处
期刊:Academic Radiology [Elsevier]
卷期号:31 (6): 2567-2578 被引量:3
标识
DOI:10.1016/j.acra.2023.11.022
摘要

Ex-smokers without spirometry or CT evidence of chronic obstructive pulmonary disease (COPD) but with mildly abnormal diffusing capacity of the lungs for carbon monoxide (DLCO) are at higher risk of developing COPD. It remains difficult to make clinical management decisions for such ex-smokers without other objective assessments consistent with COPD. Hence, our objective was to develop a machine-learning and CT texture-analysis pipeline to dichotomize ex-smokers with normal and abnormal DLCO (DLCO≥75%pred and DLCO<75%pred).In this retrospective study, 71 ex-smokers (50-85yrs) without COPD underwent spirometry, plethysmography, thoracic CT, and 3He MRI to generate ventilation defect percent (VDP) and apparent diffusion coefficients (ADC). PyRadiomics was utilized to extract 496 CT texture-features; Boruta and principal component analysis were used for feature selection and various models were investigated for classification. Machine-learning classifiers were evaluated using area under the receiver operator characteristic curve (AUC), sensitivity, specificity, and F1-measure.Of 71 ex-smokers without COPD, 29 with mildly abnormal DLCO had significantly different MRI ADC (p < .001), residual-volume to total-lung-capacity ratio (p = .003), St. George's Respiratory Questionnaire (p = .029), and six-minute-walk distance (6MWD) (p < .001), but similar relative area of the lung < -950 Hounsfield-units (RA950) (p = .9) compared to 42 ex-smokers with normal DLCO. Logistic-regression machine-learning mixed-model trained on selected texture-features achieved the best classification accuracy of 87%. All clinical and imaging measurements were outperformed by high-high-pass filter high-gray-level-run-emphasis texture-feature (AUC=0.81), which correlated with DLCO (ρ = -0.29, p = .02), MRI ADC (ρ = 0.23, p = .048), and 6MWD (ρ = -0.25, p = .02).In ex-smokers with no CT evidence of emphysema, machine-learning models exclusively trained on CT texture-features accurately classified ex-smokers with abnormal diffusing capacity, outperforming conventional quantitative CT measurements.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
共享精神应助小夏采纳,获得10
7秒前
绿眼虫发布了新的文献求助10
15秒前
绿眼虫完成签到,获得积分10
26秒前
山乞凡完成签到 ,获得积分10
38秒前
吴雪完成签到 ,获得积分10
38秒前
zz完成签到 ,获得积分10
46秒前
111完成签到 ,获得积分10
48秒前
咯咯咯完成签到 ,获得积分10
59秒前
yuehan完成签到 ,获得积分10
1分钟前
1分钟前
1分钟前
姜忆霜完成签到 ,获得积分10
1分钟前
完美世界应助小夏采纳,获得10
1分钟前
wangye完成签到 ,获得积分10
1分钟前
zhangzhangzhang完成签到 ,获得积分10
1分钟前
正直的夏真完成签到 ,获得积分10
1分钟前
玛琳卡迪马完成签到,获得积分10
1分钟前
幽默的太阳完成签到 ,获得积分10
1分钟前
1分钟前
小夏发布了新的文献求助10
1分钟前
平常山河完成签到 ,获得积分10
1分钟前
yqcsysu完成签到 ,获得积分10
1分钟前
luying发布了新的文献求助10
2分钟前
HXL完成签到 ,获得积分10
2分钟前
2分钟前
研友_LMo6rZ发布了新的文献求助10
2分钟前
孟寐以求完成签到 ,获得积分10
2分钟前
2分钟前
小夏发布了新的文献求助10
2分钟前
wenbinvan完成签到,获得积分0
2分钟前
香蕉子骞完成签到 ,获得积分10
2分钟前
小夏完成签到,获得积分10
3分钟前
3分钟前
慕青应助缓慢的饼干采纳,获得10
3分钟前
研友_LMo6rZ完成签到,获得积分10
3分钟前
嘟噜完成签到 ,获得积分10
3分钟前
3分钟前
4分钟前
付创发布了新的文献求助10
4分钟前
小哈完成签到 ,获得积分10
4分钟前
高分求助中
Solution Manual for Strategic Compensation A Human Resource Management Approach 1200
Natural History of Mantodea 螳螂的自然史 1000
Glucuronolactone Market Outlook Report: Industry Size, Competition, Trends and Growth Opportunities by Region, YoY Forecasts from 2024 to 2031 800
A Photographic Guide to Mantis of China 常见螳螂野外识别手册 800
Autoregulatory progressive resistance exercise: linear versus a velocity-based flexible model 500
The analysis and solution of partial differential equations 400
Sociocultural theory and the teaching of second languages 300
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3339039
求助须知:如何正确求助?哪些是违规求助? 2967054
关于积分的说明 8627952
捐赠科研通 2646510
什么是DOI,文献DOI怎么找? 1449258
科研通“疑难数据库(出版商)”最低求助积分说明 671343
邀请新用户注册赠送积分活动 660176