The role of lung ultrasound B-lines and serum KL-6 in the screening and follow-up of rheumatoid arthritis patients for an identification of interstitial lung disease: review of the literature, proposal for a preliminary algorithm, and clinical application to cases.
Yukai WangShaoqi ChenShaoyu ZhengJianqun LinShijian HuJinghua ZhuangQisheng LinXuezhen XieKedi ZhengWeijin ZhangGuangzhou DuGuohong ZhangAnna-Maria Hoffmann-VoldMarco Matucci-CerinicDaniel E FurstPublished in: Arthritis research & therapy (2021)
Screening and follow-up of interstitial lung disease associated with rheumatoid arthritis (RA-ILD) is a challenge in clinical practice. In fact, the majority of RA-ILD patients are asymptomatic and optimal tools for early screening and regular follow-up are lacking. Furthermore, some patients may remain oligosymptomatic despite significant radiological abnormalities. In RA-ILD, usual interstitial pneumonia (UIP) is the most frequent radiological and pathological pattern, associated with a poor prognosis and a high risk to develop acute exacerbations and infections. If RA-ILD can be identified early, there may be an opportunity for an early treatment and close follow-up that might delay ILD progression and improve the long-term outcome.In connective tissue disease-associated interstitial lung disease (CTD-ILD), lung ultrasound (LUS) with the assessment of B-lines and serum Krebs von den Lungen-6 antigen (KL-6) has been recognized as sensitive biomarkers for the early detection of ILD. B-line number and serum KL-6 level were found to correlate with high-resolution computed tomography (HRCT), pulmonary function tests (PFTs), and other clinical parameters in systemic sclerosis-associated ILD (SSc-ILD). Recently, the significant correlation between B-lines and KL-6, two non-ionizing and non-invasive biomarkers, was demonstrated. Hence, the combined use of LUS and KL-6 to screen and follow up ILD in RA patients might be useful in clinical practice in addition to existing tools. Herein, we review relevant literature to support this concept, propose a preliminary screening algorithm, and present 2 cases where the algorithm was used.
Keyphrases
- interstitial lung disease
- systemic sclerosis
- rheumatoid arthritis
- idiopathic pulmonary fibrosis
- disease activity
- end stage renal disease
- poor prognosis
- ejection fraction
- high resolution
- newly diagnosed
- clinical practice
- computed tomography
- magnetic resonance imaging
- prognostic factors
- chronic kidney disease
- chronic obstructive pulmonary disease
- systematic review
- machine learning
- patient reported outcomes
- ankylosing spondylitis
- low dose
- magnetic resonance
- deep learning
- acute respiratory distress syndrome
- respiratory failure
- neural network
- contrast enhanced