ArticleEuropean radiology experimental2024
CT-based body composition analysis and pulmonary fat attenuation volume as biomarkers to predict overall survival in patients with non-specific interstitial pneumonia.
Article in European radiology experimental, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of the role of quantitative CT in the prognostication and disease monitoring of interstitial lung disease.European respiratory review : an official journal of the European Respiratory Society · 2025Pooled it
- Radiation dose has no significant impact on CT-based bone mineral density measurements in a large-animal model.Scientific reports · 2026Article
- Pulmonary Fibrosis Beyond the Lung: Adipose Tissue as a Systemic Modifier of Fibrotic Remodeling.Diagnostics (Basel, Switzerland) · 2026Review
- AI-based volumetric six-tissue body composition quantification from CT cardiac attenuation scans for mortality prediction: a multicentre study.The Lancet. Digital health · 2025Article
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13 authors.
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Abstract
backgroundNon-specific interstitial pneumonia (NSIP) is an interstitial lung disease that can result in end-stage fibrosis. We investigated the influence of body composition and pulmonary fat attenuation volume (CTpfav) on overall survival (OS) in NSIP patients.
methodsIn this retrospective single-center study, 71 NSIP patients with a median age of 65 years (interquartile range 21.5), 39 females (55%), who had a computed tomography from August 2009 to February 2018, were included, of whom 38 (54%) died during follow-up. Body composition analysis was performed using an open-source nnU-Net-based framework. Features were combined into: Sarcopenia (muscle/bone); Fat (total adipose tissue/bone); Myosteatosis (inter-/intra-muscular adipose tissue/total adipose tissue); Mediastinal (mediastinal adipose tissue/bone); and Pulmonary fat index (CTpfav/lung volume). Kaplan-Meier analysis with a log-rank test and multivariate Cox regression were used for survival analyses.
resultsPatients with a higher (> median) Sarcopenia and lower (< median) Mediastinal Fat index had a significantly better survival probability (2-year survival rate: 83% versus 71% for high versus low Sarcopenia index, p = 0.023; 83% versus 72% for low versus high Mediastinal fat index, p = 0.006). In univariate analysis, individuals with a higher Pulmonary fat index exhibited significantly worse survival probability (2-year survival rate: 61% versus 94% for high versus low, p = 0.003). Additionally, it was an independent risk predictor for death (hazard ratio 2.37, 95% confidence interval 1.03-5.48, p = 0.043).
conclusionFully automated body composition analysis offers interesting perspectives in patients with NSIP. Pulmonary fat index was an independent predictor of OS. RELEVANCE STATEMENT: The Pulmonary fat index is an independent predictor of OS in patients with NSIP and demonstrates the potential of fully automated, deep-learning-driven body composition analysis as a biomarker for prognosis estimation. KEY POINTS: This is the first study assessing the potential of CT-based body composition analysis in patients with non-specific interstitial pneumonia (NSIP). A single-center analysis of 71 patients with board-certified diagnosis of NSIP is presented Indices related to muscle, mediastinal fat, and pulmonary fat attenuation volume were significantly associated with survival at univariate analysis. CT pulmonary fat attenuation volume, normalized by lung volume, resulted as an independent predictor for death.
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