Observational studyRheumatology international2025
The association of symptoms, pulmonary function test and computed tomography in interstitial lung disease at the onset of connective tissue disease: an observational study with artificial intelligence analysis of high-resolution computed tomography.
Observational study in Rheumatology international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- High-resolution computed tomography assessment of connective tissue disease-associated interstitial lung disease: Advances in diagnosis and prognostic evaluation.World journal of radiology · 2026Review
- Liver stiffness in fibrotic ILD: a CTD-ILD biomarker or a phenotype-dependent signal of systemic fibrosis?Rheumatology international · 2026Article
- Use of Artificial Intelligence in Rheumatoid Arthritis: Advancements and Novel Perspectives.Journal of clinical medicine · 2026Review
- Assessment of CDASI scoring by a multimodal large language model: a comparative study with expert assessors.Rheumatology international · 2026Article
- Evolving landscape of imaging-based evaluation in systemic autoimmune rheumatic disease-associated interstitial lung disease: from visual assessment to quantitative artificial intelligence-assisted evaluation.Journal of rheumatic diseases · 2026Review
- Systemic Sclerosis-Associated ILD: Insights and Limitations of ScleroID.Diagnostics (Basel, Switzerland) · 2026Article
- Ethical Use of Artificial Intelligence for Processing Medical Images.Journal of Korean medical science · 2025Article
- Comparative evaluation of large language models on multiple-choice and image-based rheumatology questions.Rheumatology international · 2025Article
- AI-based HRCT quantification reveals DLCO and TLC as key determinants of ILD severity in connective tissue diseases.RMD open · 2025Article
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12 authors.
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Abstract
Interstitial lung disease (ILD) is a common and serious organ manifestation in patients with connective tissue disease (CTD), but it is uncertain whether there is a difference in ILD between symptomatic and asymptomatic patients. Therefore, we conducted a study to evaluate differences in the extent of ILD based on radiological findings between symptomatic/asymptomatic patients, using an artificial intelligence (AI)-based quantification of pulmonary high-resolution computed tomography (AIpqHRCT). Within the study, 67 cross-sectional HRCT datasets and clinical data (including pulmonary function test) of consecutively patients (mean age: 57.1 ± 14.7 years, woman n = 45; 67.2%) with both, initial diagnosis of CTD, with systemic sclerosis being the most frequent (n = 21, 31.3%), and ILD (all without immunosuppressive therapy), were analysed using AIqpHRCT. 25.4% (n = 17) of the patients with ILD at initial diagnosis of CTD had no pulmonary symptoms. Regarding the baseline characteristics (age, gender, disease), there were no significant difference between the symptomatic and asymptomatic group. The pulmonary function test (PFT) revealed the following mean values (%predicted) in the symptomatic and asymptomatic group, respectively: Forced vital capacity (FVC) 69.4 ± 17.4% versus 86.1 ± 15.8% (p = 0.001), and diffusing capacity of the lung for carbon monoxide (DLCO) 49.7 ± 17.9% versus 60.0 ± 15.8% (p = 0.043). AIqpHRCT data showed a significant higher amount of high attenuated volume (HAV) (14.8 ± 11.0% versus 8.9 ± 3.9%; p = 0.021) and reticulations (5.4 ± 8.7% versus 1.4 ± 1.5%; p = 0.035) in symptomatic patients. A quarter of patients with ILD at the time of initial CTD diagnosis had no pulmonary symptoms, showing DLCO were reduced in both groups. Also, AIqpHRCT demonstrated clinically relevant ILD in asymptomatic patients. These results underline the importance of an early risk adapted screening for ILD also in asymptomatic CTD patients, as ILD is associated with increased mortality.
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