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Viewpoint: a multidisciplinary approach to the assessment of patients with systemic sclerosis-associated interstitial lung disease.

ABSTRACT: 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.

SUBMITTER: Chatterjee S

PROVIDER: S-EPMC9935731 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Viewpoint: a multidisciplinary approach to the assessment of patients with systemic sclerosis-associated interstitial lung disease.

Chatterjee Soumya S Perelas Apostolos A Yadav Ruchi R Kirby Donald F DF Singh Amandeep A

Clinical rheumatology 20221021 3

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. Hig ...[more]

PMID: 36271064

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Project description:PurposeTo develop a deep learning algorithm for the automatic assessment of the extent of systemic sclerosis (SSc)-related interstitial lung disease (ILD) on chest CT images.Materials and methodsThis retrospective study included 208 patients with SSc (median age, 57 years; 167 women) evaluated between January 2009 and October 2017. A multicomponent deep neural network (AtlasNet) was trained on 6888 fully annotated CT images (80% for training and 20% for validation) from 17 patients with no, mild, or severe lung disease. The model was tested on a dataset of 400 images from another 20 patients, independently partially annotated by three radiologist readers. The ILD contours from the three readers and the deep learning neural network were compared by using the Dice similarity coefficient (DSC). The correlation between disease extent obtained from the deep learning algorithm and that obtained by using pulmonary function tests (PFTs) was then evaluated in the remaining 171 patients and in an external validation dataset of 31 patients based on the analysis of all slices of the chest CT scan. The Spearman rank correlation coefficient (ρ) was calculated to evaluate the correlation between disease extent and PFT results.ResultsThe median DSCs between the readers and the deep learning ILD contours ranged from 0.74 to 0.75, whereas the median DSCs between contours from radiologists ranged from 0.68 to 0.71. The disease extent obtained from the algorithm, by analyzing the whole CT scan, correlated with the diffusion lung capacity for carbon monoxide, total lung capacity, and forced vital capacity (ρ = -0.76, -0.70, and -0.62, respectively; P < .001 for all) in the dataset for the correlation with PFT results. The disease extents correlated with diffusion lung capacity for carbon monoxide, total lung capacity, and forced vital capacity were ρ = -0.65, -0.70, and -0.57, respectively, in the external validation dataset (P < .001 for all).ConclusionThe developed algorithm performed similarly to radiologists for disease-extent contouring, which correlated with pulmonary function to assess CT images from patients with SSc-related ILD.Supplemental material is available for this article.© RSNA, 2020.

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Viewpoint: a multidisciplinary approach to the assessment of patients with systemic sclerosis-associated interstitial lung disease.

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Viewpoint: a multidisciplinary approach to the assessment of patients with systemic sclerosis-associated interstitial lung disease.

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