Won Jong Jeong, Bo Da Nam, Jung Hwa Hwang, Chang Hyun Lee, Hee-Young Yoon, Eun Ji Lee, Eunsun Oh, Jewon Jeong, Sung Hwan Bae
{"title":"健康筛查中低剂量胸部CT间质性肺异常的长期随访:利用基于人工智能的定量CT分析探索临床显著间质性肺疾病的预测因素","authors":"Won Jong Jeong, Bo Da Nam, Jung Hwa Hwang, Chang Hyun Lee, Hee-Young Yoon, Eun Ji Lee, Eunsun Oh, Jewon Jeong, Sung Hwan Bae","doi":"10.3348/jksr.2024.0032","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>This study examined longitudinal changes in interstitial lung abnormalities (ILAs) and predictors of clinically significant interstitial lung diseases (ILDs) in a screening population with ILAs.</p><p><strong>Materials and methods: </strong>We retrieved 36891 low-dose chest CT records from screenings between January 2003 and May 2021. After identifying 101 patients with ILAs, the clinical findings, spirometry results, and initial and follow-up CT findings, including visual and artificial intelligence-based quantitative analyses, were compared between patients diagnosed with ILD (<i>n</i> = 23, 23%) and those who were not (<i>n</i> = 78, 77%). Logistic regression analysis was used to identify significant parameters for the clinical diagnosis of ILD.</p><p><strong>Results: </strong>Twenty-three patients (<i>n</i> = 23, 23%) were subsequently diagnosed with clinically significant ILDs at follow-up (mean, 8.7 years). Subpleural fibrotic ILAs on initial CT and signs of progression on follow-up CT were common in the ILD group (both <i>p</i> < 0.05). Logistic regression analysis revealed that emerging respiratory symptoms (odds ratio [OR], 5.56; 95% confidence interval [CI], 1.28-24.21; <i>p</i> = 0.022) and progression of ILAs at follow-up chest CT (OR, 4.07; 95% CI, 1.00-16.54; <i>p</i> = 0.050) were significant parameters for clinical diagnosis of ILD.</p><p><strong>Conclusion: </strong>Clinically significant ILD was subsequently diagnosed in approximately one-quarter of the screened population with ILAs. Emerging respiratory symptoms and progression of ILAs at follow-up chest CT can be predictors of clinically significant ILDs.</p>","PeriodicalId":101329,"journal":{"name":"Journal of the Korean Society of Radiology","volume":"85 6","pages":"1141-1156"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11625842/pdf/","citationCount":"0","resultStr":"{\"title\":\"Long-Term Follow-Up of Interstitial Lung Abnormalities in Low-Dose Chest CT in Health Screening: Exploring the Predictors of Clinically Significant Interstitial Lung Diseases Using Artificial Intelligence-Based Quantitative CT Analysis.\",\"authors\":\"Won Jong Jeong, Bo Da Nam, Jung Hwa Hwang, Chang Hyun Lee, Hee-Young Yoon, Eun Ji Lee, Eunsun Oh, Jewon Jeong, Sung Hwan Bae\",\"doi\":\"10.3348/jksr.2024.0032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>This study examined longitudinal changes in interstitial lung abnormalities (ILAs) and predictors of clinically significant interstitial lung diseases (ILDs) in a screening population with ILAs.</p><p><strong>Materials and methods: </strong>We retrieved 36891 low-dose chest CT records from screenings between January 2003 and May 2021. After identifying 101 patients with ILAs, the clinical findings, spirometry results, and initial and follow-up CT findings, including visual and artificial intelligence-based quantitative analyses, were compared between patients diagnosed with ILD (<i>n</i> = 23, 23%) and those who were not (<i>n</i> = 78, 77%). Logistic regression analysis was used to identify significant parameters for the clinical diagnosis of ILD.</p><p><strong>Results: </strong>Twenty-three patients (<i>n</i> = 23, 23%) were subsequently diagnosed with clinically significant ILDs at follow-up (mean, 8.7 years). Subpleural fibrotic ILAs on initial CT and signs of progression on follow-up CT were common in the ILD group (both <i>p</i> < 0.05). Logistic regression analysis revealed that emerging respiratory symptoms (odds ratio [OR], 5.56; 95% confidence interval [CI], 1.28-24.21; <i>p</i> = 0.022) and progression of ILAs at follow-up chest CT (OR, 4.07; 95% CI, 1.00-16.54; <i>p</i> = 0.050) were significant parameters for clinical diagnosis of ILD.</p><p><strong>Conclusion: </strong>Clinically significant ILD was subsequently diagnosed in approximately one-quarter of the screened population with ILAs. Emerging respiratory symptoms and progression of ILAs at follow-up chest CT can be predictors of clinically significant ILDs.</p>\",\"PeriodicalId\":101329,\"journal\":{\"name\":\"Journal of the Korean Society of Radiology\",\"volume\":\"85 6\",\"pages\":\"1141-1156\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11625842/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Korean Society of Radiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3348/jksr.2024.0032\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/11/21 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Korean Society of Radiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3348/jksr.2024.0032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/11/21 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Long-Term Follow-Up of Interstitial Lung Abnormalities in Low-Dose Chest CT in Health Screening: Exploring the Predictors of Clinically Significant Interstitial Lung Diseases Using Artificial Intelligence-Based Quantitative CT Analysis.
Purpose: This study examined longitudinal changes in interstitial lung abnormalities (ILAs) and predictors of clinically significant interstitial lung diseases (ILDs) in a screening population with ILAs.
Materials and methods: We retrieved 36891 low-dose chest CT records from screenings between January 2003 and May 2021. After identifying 101 patients with ILAs, the clinical findings, spirometry results, and initial and follow-up CT findings, including visual and artificial intelligence-based quantitative analyses, were compared between patients diagnosed with ILD (n = 23, 23%) and those who were not (n = 78, 77%). Logistic regression analysis was used to identify significant parameters for the clinical diagnosis of ILD.
Results: Twenty-three patients (n = 23, 23%) were subsequently diagnosed with clinically significant ILDs at follow-up (mean, 8.7 years). Subpleural fibrotic ILAs on initial CT and signs of progression on follow-up CT were common in the ILD group (both p < 0.05). Logistic regression analysis revealed that emerging respiratory symptoms (odds ratio [OR], 5.56; 95% confidence interval [CI], 1.28-24.21; p = 0.022) and progression of ILAs at follow-up chest CT (OR, 4.07; 95% CI, 1.00-16.54; p = 0.050) were significant parameters for clinical diagnosis of ILD.
Conclusion: Clinically significant ILD was subsequently diagnosed in approximately one-quarter of the screened population with ILAs. Emerging respiratory symptoms and progression of ILAs at follow-up chest CT can be predictors of clinically significant ILDs.