Viewpoint: a multidisciplinary approach to the assessment of patients with systemic sclerosis-associated interstitial lung disease.
Soumya ChatterjeeApostolos PerelasRuchi YadavDonald F KirbyAmandeep SinghPublished in: Clinical rheumatology (2022)
Systemic sclerosis (SSc) is a rare and heterogeneous disease affecting the skin and internal organs. SSc-associated ILD (SSc-ILD) is a common and often early manifestation of SSc. This article discusses the rationale for a multidisciplinary approach (MDA) to the early identification and assessment of patients with SSc-ILD. Diagnosis of SSc-ILD is often challenging as patients with early disease can be asymptomatic, and SSc-ILD symptoms, such as exertional dyspnea and cough, are non-specific. High-resolution computed tomography (HRCT) of the lungs is the gold standard for diagnosis of SSc-ILD since pulmonary function tests lack sensitivity and specificity, especially in early disease. On HRCT, most patients with SSc-ILD have a non-specific interstitial pneumonia (NSIP) pattern. In addition, findings of pulmonary hypertension and esophageal dysmotility may be present. The multi-organ involvement of SSc and the diverse spectrum of symptoms support an MDA for the diagnosis and assessment of patients with SSc-ILD, with input from rheumatologists, pulmonologists, gastroenterologists, radiologists, and other specialists. Key Points • Interstitial lung disease (ILD) is a common manifestation of systemic sclerosis (SSc). • Early diagnosis is key to reducing the morbidity and mortality associated with SSc-ILD and other manifestations of SSc. • The multi-organ involvement of SSc supports a multidisciplinary approach to the diagnosis and assessment of patients with SSc-ILD, with input from rheumatologists, pulmonologists, gastroenterologists, radiologists, and other specialists.
Keyphrases
- interstitial lung disease
- systemic sclerosis
- rheumatoid arthritis
- idiopathic pulmonary fibrosis
- computed tomography
- high resolution
- pulmonary hypertension
- clinical trial
- magnetic resonance imaging
- machine learning
- magnetic resonance
- artificial intelligence
- physical activity
- positron emission tomography
- pet ct
- heat stress
- liquid chromatography