Purpose
To analyze the feasibility of predicting gender–age–physiology (GAP) staging in patients
with connective tissue disease-associated interstitial lung disease (CTD-ILD) by radiomics
based on computed tomography (CT) of the chest.
Materials and Methods
Chest CT images of 184 patients with CTD-ILD were retrospectively analyzed. GAP staging
was performed on the basis of gender, age, and pulmonary function test results. GAP
I, II, and III have 137, 36, and 11 cases, respectively. The cases in GAP Ⅱ and Ⅲ
were then combined into one group, and the two groups of patients were randomly divided
into the training and testing groups with a 7:3 ratio. The radiomics features were
extracted using AK software. Multivariate logistic regression analysis was then conducted
to establish a radiomics model. A nomogram model was established on the basis of Rad-score
and clinical factors (age and gender).
Results
For the radiomics model, four significant radiomics features were selected to construct
the model and showed excellent ability to differentiate GAP I from GAP Ⅱ and Ⅲ in
both the training group (the area under the curve [AUC] = 0.803, 95% confidence interval
[CI]: 0.724–0.874) and testing group (AUC = 0.801, 95% CI:0.663–0.912). The nomogram
model that combined clinical factors and radiomics features improved higher accuracy
of both training (88.4% vs. 82.1%) and testing (83.3% vs. 79.2%).
Conclusion
The disease severity assessment of patients with CTD-ILD can be evaluated by applying
the radiomics method based on CT images. The nomogram model demonstrates better performance
for predicting the GAP staging.
Key Words
Abbreviations:
GAP (gender–age–physiology), CTD (connective tissue disease), ILD (interstitial lung disease), CT (computed tomography), AUC (the area under the curve), SSc (systemic sclerosis), RA (rheumatoid arthritis), IPF (idiopathic pulmonary fibrosis), FVC (forced vital capacity), DLCO (diffusing capacity for carbon monoxide), NSIP (nonspecific interstitial pneumonia), PFT (pulmonary function test), FEV1 (forced expiratory volume in 1.0 s), VA (alveolar ventilation), TLC (total lung capacity), VOI (volume of interest)To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to Academic RadiologyAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
References
- Connective tissue disease-related interstitial lung disease: prevalence, patterns, predictors, prognosis, and treatment.Lung. 2020; 198: 735-759
- 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.Arthritis Rheumatol. 2019; 71: 182-195
- Changes in causes of death in systemic sclerosis, 1972-2002.Ann Rheum Dis. 2007; 66: 940-944
- Causes and risk factors for death in systemic sclerosis: a study from the EULAR Scleroderma Trials and Research (EUSTAR) database.Ann Rheum Dis. 2010; 69: 1809-1815
- A population-based cohort study of rheumatoid arthritis-associated interstitial lung disease: comorbidity and mortality.Ann Rheum Dis. 2017; 76: 1700-1706
- Rheumatoid arthritis-interstitial lung disease in the United States: prevalence, incidence, and healthcare costs and mortality.J Rheumatol. 2019; 46: 360-369
- An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management.American J Respir Crit Care Med. 2011; 183: 788-824
- CT in idiopathic pulmonary fibrosis: diagnosis and beyond.AJR Am J Roentgenol. 2016; 206: 495-507
- Diagnostic certainty of idiopathic pulmonary fibrosis/usual interstitial pneumonia: the effect of the integrated clinico-radiological assessment.Eur J Radiol. 2015; 84: 2640-2645
- Interobserver agreement for the ATS/ERS/JRS/ALAT criteria for a UIP pattern on CT.Thorax. 2016; 71: 45-51
- Multicentre evaluation of multidisciplinary team meeting agreement on diagnosis in diffuse parenchymal lung disease: a case-cohort study.Lancet Respir Med. 2016; 4: 557-565
- Artificial Intelligence for interstitial lung disease analysis on chest computed tomography: a systematic review.Acad Radiol. 2022; 29: S226-SS35
- Short-term automated quantification of radiologic changes in the characterization of idiopathic pulmonary fibrosis versus nonspecific interstitial pneumonia and prediction of long-term survival.J Thorac Imaging. 2018; 33: 124-131
- Mortality prediction in idiopathic pulmonary fibrosis: evaluation of computer-based CT analysis with conventional severity measures.Eur Respir J. 2017; 49: 1601011
- Automated quantification of radiological patterns predicts survival in idiopathic pulmonary fibrosis.Eur Respir J. 2014; 43: 204-212
- Radiomics: extracting more information from medical images using advanced feature analysis.Eur J Cancer. 2012; 48: 441-446
- Radiomics for Classification of lung cancer histological subtypes based on nonenhanced computed tomography.Acad Radiol. 2019; 26: 1245-1252
- A quantitative imaging biomarker for predicting disease-free-survival-associated histologic subgroups in lung adenocarcinoma.Eur Radiol. 2020; 30: 3614-3623
- Detection of local cancer recurrence after stereotactic ablative radiation therapy for lung cancer: physician performance versus radiomic assessment.Int J Radiat Oncol Biol Phys. 2016; 94: 1121-1128
- Applicability of radiomics in interstitial lung disease associated with systemic sclerosis: proof of concept.Eur Radiol. 2021; 31: 1987-1998
- A handcrafted radiomics-based model for the diagnosis of usual interstitial pneumonia in patients with idiopathic pulmonary fibrosis.J Pers Med. 2022; 12: 373
- A computed tomography radiomics-based prediction model on interstitial lung disease in anti-MDA5-positive dermatomyositis.Front Med. 2021; 8768052
- A multidimensional index and staging system for idiopathic pulmonary fibrosis.Ann Intern Med. 2012; 156: 684-691
- Staging systems and disease severity assessment in interstitial lung diseases.Curr Opin Pulm Med. 2015; 21: 463-469
- Predicting survival across chronic interstitial lung disease: the ILD-GAP model.Chest. 2014; 145: 723-728
- Diagnosis of idiopathic pulmonary fibrosis. An official ATS/ERS/JRS/ALAT clinical practice guideline.Am J Respir Crit Care Med. 2018; 198: e44-e68
- A CT algorithm can elevate the differential diagnosis of interstitial lung disease by non-specialists to equal that of specialist thoracic radiologists.Acad Radiol. 2022; 29: S181-SS90
- Automatic lung segmentation based on texture and deep features of HRCT images with interstitial lung disease.Biomed Res Int. 2019; 20192045432
- Semantic segmentation of pathological lung tissue with dilated fully convolutional networks.IEEE J Biomed Health Inform. 2019; 23: 714-722
- Lung segmentation on HRCT and volumetric CT for diffuse interstitial lung disease using deep convolutional neural networks.J Digit Imaging. 2019; 32: 1019-1026
- Building a reference multimedia database for interstitial lung diseases.Comput Med Imaging Graph. 2012; 36: 227-238
- Radiogenomics in personalized management of lung cancer patients: where are we?.Clin Imaging. 2022; 84: 54-60
- Radiomic measures from chest high-resolution computed tomography associated with lung function in sarcoidosis.Eur Respir J. 2019; 54: 1900371
- Idiopathic pulmonary fibrosis: CT and risk of death.Radiology. 2014; 273: 570-579
Article info
Publication history
Published online: March 02, 2023
Accepted:
January 29,
2023
Received in revised form:
January 29,
2023
Received:
December 17,
2022
Publication stage
In Press Corrected ProofIdentification
Copyright
© 2023 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
