Nie Han
*
Lin Jin
*The final, formatted version of the article will be published soon.
ORIGINAL RESEARCH article
Front. Immunol.
Sec. Autoimmune and Autoinflammatory Disorders : Autoimmune Disorders
Volume 15 - 2024 |
doi: 10.3389/fimmu.2024.1417156
This article is part of the Research Topic Deep Learning for Medical Imaging Applications View all 3 articles
A Nomogram Model Combining Computed Tomographybased Radiomics and Krebs von den Lungen-6 for Identifying Low-risk Rheumatoid Arthritis-associated Interstitial Lung Disease
Provisionally accepted- Shanghai Guanghua Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai, China
Objectives: Quantitively assess the severity and predict the mortality of interstitial lung disease (ILD) associated with Rheumatoid arthritis (RA) was a challenge for clinicians. This study aimed to construct a radiomics nomogram based on chest computed tomography (CT) imaging by using the ILD-GAP (gender, age, and pulmonary physiology) index system for clinical management.Methods: Chest CT images of patients with RA-ILD were retrospectively analyzed and staged using the ILD-GAP index system. The balanced dataset was then divided into training and testing cohorts at a 7:3 ratio. A clinical factor model was created using Results: A total of 177 patients were divided into two groups (Group I, n = 107; Group II, n = 63). Krebs von den Lungen-6, and nineteen radiomics features were used to build the nomogram, which showed favorable calibration and discrimination in the training cohort [AUC, 0.948 (95% CI: 0.910-0.986)] and the testing validation cohort [AUC, 0.923 (95% CI: 0.853-0.993)]. Decision curve analysis demonstrated that the nomogram performed well in terms of clinical usefulness.The CT-based radiomics nomogram model achieved favorable efficacy in predicting low-risk RA-ILD patients.
Keywords: computed tomography, Radiomics, KL-6, Rheumatoid arthritis, Interstitial Lung Disease
Received: 14 Apr 2024; Accepted: 22 Jul 2024.
Copyright: © 2024 Han, Guo, Zhu, Zhang, Qin, Li, Gu and Jin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Nie Han, Shanghai Guanghua Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai, China
Zhinan Guo, Shanghai Guanghua Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai, China
Diru Zhu, Shanghai Guanghua Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai, China
Yu Zhang, Shanghai Guanghua Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai, China
Yayi Qin, Shanghai Guanghua Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai, China
Guanheng Li, Shanghai Guanghua Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai, China
Xiaoli Gu, Shanghai Guanghua Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai, China
Lin Jin, Shanghai Guanghua Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.