Photo Credit: Outflow Designs

A CT-based radiomics nomogram model achieved favorable efficacy for predicting low-risk patients with rheumatoid arthritis (RA)-associated interstitial lung disease (ILD), according to a study published in Frontiers in Immunology. The researchers retrospectively analyzed chest CT images of patients with RA-ILD and staged them using the ILD-Gender-Age-Physiology index. The researchers then divided the dataset of 177 patients into training and testing cohorts in a 7:3 ratio, respectively. The nomogram model was established based on the Rad-score and clinical factors, combined with the radiomics signature and independent clinical factors. The researchers built the nomogram using the Krebs von den Lungen-6 (KL-6) and 19 radiomics features. The model’s calibration and discrimination were favorable in the training and testing validation cohorts (areas under the receiver operating characteristic curve, 0.948 and 0.923, respectively). In terms of clinical usefulness, the nomogram performed well in a decision curve analysis.