{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T14:17:21Z","timestamp":1790605041184,"version":"4.1.0"},"reference-count":46,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,10,6]],"date-time":"2023-10-06T00:00:00Z","timestamp":1696550400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec><jats:title>Rationale and introduction<\/jats:title><jats:p>It is of significance to assess the severity and predict the mortality of patients with connective tissue disease-associated interstitial lung disease (CTD-ILD). In this double-center retrospective study, we developed and validated a radiomics nomogram for clinical management by using the ILD-GAP (gender, age, and pulmonary physiology) index system.<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and methods<\/jats:title><jats:p>Patients with CTD-ILD were staged using the ILD-GAP index system. A clinical factor model was built by demographics and CT features, and a radiomics signature was developed using radiomics features extracted from CT images. Combined with the radiomics signature and independent clinical factors, a radiomics nomogram was constructed and evaluated by the area under the curve (AUC) from receiver operating characteristic (ROC) analyses. The models were externally validated in dataset 2 to evaluate the model generalization ability using ROC analysis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A total of 245 patients from two clinical centers (dataset 1, n = 202; dataset 2, n = 43) were screened. Pack-years of smoking, traction bronchiectasis, and nine radiomics features were used to build the radiomics nomogram, which showed favorable calibration and discrimination in the training cohort {AUC, 0.887 [95% confidence interval (CI): 0.827\u20130.940]}, the internal validation cohort [AUC, 0.885 (95% CI: 0.816\u20130.922)], and the external validation cohort [AUC, 0.85 (95% CI: 0.720\u20130.919)]. Decision curve analysis demonstrated that the nomogram outperformed the clinical factor model and radiomics signature in terms of clinical usefulness.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The CT-based radiomics nomogram showed favorable efficacy in predicting individual ILD-GAP stages.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fimmu.2023.1213008","type":"journal-article","created":{"date-parts":[[2023,10,6]],"date-time":"2023-10-06T07:58:29Z","timestamp":1696579109000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Non-contrast computed tomography-based radiomics for staging of connective tissue disease-associated interstitial lung disease"],"prefix":"10.3389","volume":"14","author":[{"given":"Songnan","family":"Qin","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bingxuan","family":"Jiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bing","family":"Kang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haiou","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongwu","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Congshan","family":"Ji","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shifeng","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongtao","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ximing","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,10,6]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(12)61079-4","article-title":"Interstitial lung disease in connective tissue disorders","volume":"380","author":"Fischer","year":"2012","journal-title":"Lancet"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1002\/art.40769","article-title":"Proceedings of the american college of rheumatology\/association of physicians of great britain and Ireland connective tissue disease-associated interstitial lung disease summit: A multidisciplinary approach to address challenges and opportunities","volume":"71","author":"Fischer","year":"2019","journal-title":"Arthritis Rheumatol"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1007\/s40265-019-01178-x","article-title":"Current and emerging drug therapies for connective tissue disease-interstitial lung disease (CTD-ILD)","volume":"79","author":"Jee","year":"2019","journal-title":"Drugs"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.3390\/jcm9020407","article-title":"Therapeutic options for the treatment of interstitial lung disease related to connective tissue diseases. 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