ArticleDiagnostics (Basel, Switzerland)2022
Radiomics for the Prediction of Response to Antifibrotic Treatment in Patients with Idiopathic Pulmonary Fibrosis: A Pilot Study.
Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 18 citations in OpenAlex.
- Prediction of intravenous cyclophosphamide treatment efficacy in idiopathic inflammatory myopathies-associated interstitial lung disease patients: a nomogram based on radiomics and clinical factors.BMC pulmonary medicine · 2026Article
- Decoding disease and therapy through multiomics integration and systems analysis.Briefings in bioinformatics · 2026Review
- Altered Metabolism in Idiopathic Pulmonary Fibrosis.Journal of cellular physiology · 2025Review
- Radiomics and Artificial Intelligence in Pulmonary Fibrosis.Journal of imaging informatics in medicine · 2025Review
- Application of HRCT-based radiomics to predict interstitial lung disease for juvenile dermatomyositis.BMC pediatrics · 2025Article
- What role does artificial intelligence-driven quantitative analysis of chest computed tomography play in providing pulmonary function for idiopathic pulmonary fibrosis patients undergoing pirfenidone treatment?Quantitative imaging in medicine and surgery · 2025Article
- Multimodal MRI radiomics based on habitat subregions of the tumor microenvironment for predicting risk stratification in glioblastoma.PloS one · 2025Article
- Fusing Diverse Decision Rules in 3D-Radiomics for Assisting Diagnosis of Lung Adenocarcinoma.Journal of imaging informatics in medicine · 2024Article
- Succinate promotes pulmonary fibrosis through GPR91 and predicts death in idiopathic pulmonary fibrosis.Scientific reports · 2024Article
- Multidisciplinary Approach to the Diagnosis of Idiopathic Interstitial Pneumonias: Focus on the Pathologist's Key Role.International journal of molecular sciences · 2024Review
- A Bi-LSTM and multihead attention-based model incorporating radiomics signatures and radiological features for differentiating the main subtypes of lung adenocarcinoma.Quantitative imaging in medicine and surgery · 2023Article
- Development of a radiomics nomogram to predict the treatment resistance of Chinese MPO-AAV patients with lung involvement: a two-center study.Frontiers in immunology · 2023Article
- Baseline whole-lung CT features deriving from deep learning and radiomics: prediction of benign and malignant pulmonary ground-glass nodules.Frontiers in oncology · 2023Article
- Artificial-intelligence-based computed tomography histogram analysis predicting tumor invasiveness of lung adenocarcinomas manifesting as radiological part-solid nodules.Frontiers in oncology · 2023Article
- Effects of Automatic Deep-Learning-Based Lung Analysis on Quantification of Interstitial Lung Disease: Correlation with Pulmonary Function Test Results and Prognosis.Diagnostics (Basel, Switzerland) · 2022Article
- Surgomics: personalized prediction of morbidity, mortality and long-term outcome in surgery using machine learning on multimodal data.Surgical endoscopy · 2022Article
- The applications of CT with artificial intelligence in the prognostic model of idiopathic pulmonary fibrosis.Therapeutic advances in respiratory diseaseReview
Corrections and comments
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Authors and funding
8 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Antifibrotic therapy has changed the treatment paradigm for idiopathic pulmonary fibrosis (IPF); however, a subset of patients still experienced rapid disease progression despite treatment. This study aimed to determine whether CT-based radiomic features can predict therapeutic response to antifibrotic agents. In this retrospective study, 35 patients with IPF on antifibrotic treatment enrolled from two centers were divided into training (
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