CT-based body composition analysis and pulmonary fat attenuation volume as biomarkers to predict overall survival in patients with non-specific interstitial pneumonia.

IF 3.7 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Luca Salhöfer, Francesco Bonella, Mathias Meetschen, Lale Umutlu, Michael Forsting, Benedikt M Schaarschmidt, Marcel Opitz, Nikolas Beck, Sebastian Zensen, René Hosch, Vicky Parmar, Felix Nensa, Johannes Haubold
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引用次数: 0

Abstract

Background: Non-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.

Methods: In 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.

Results: Patients 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).

Conclusion: Fully 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.

以 CT 为基础的身体成分分析和肺脂肪衰减体积作为生物标志物,预测非特异性间质性肺炎患者的总生存率。
背景:非特异性间质性肺炎(NSIP非特异性间质性肺炎(NSIP)是一种可导致终末期纤维化的间质性肺病。我们研究了身体成分和肺脂肪衰减体积(CTpfav)对非特异性间质性肺炎患者总生存期(OS)的影响:在这项回顾性单中心研究中,纳入了 2009 年 8 月至 2018 年 2 月期间接受过计算机断层扫描的 71 例 NSIP 患者,中位年龄为 65 岁(四分位数间距为 21.5),女性 39 例(55%),其中 38 例(54%)在随访期间死亡。身体成分分析使用基于 nnU-Net 的开源框架进行。特征合并为肌少症(肌肉/骨骼);脂肪(总脂肪组织/骨骼);肌肥大症(肌间/肌内脂肪组织/总脂肪组织);纵隔(纵隔脂肪组织/骨骼);肺脂肪指数(CTpfav/肺容积)。生存分析采用卡普兰-梅耶分析和对数秩检验以及多变量考克斯回归:结果: Sarcopenia 值较高(大于中位数)的患者和 Sarcopenia 值较低的患者(结论:全自动身体成分分析仪为患者提供了一种新的分析方法:全自动的身体成分分析为NSIP患者提供了有趣的视角。肺脂肪指数是预测 OS 的独立指标:肺脂肪指数是NSIP患者OS的独立预测指标,证明了全自动、深度学习驱动的身体成分分析作为预后评估生物标志物的潜力:这是第一项评估基于 CT 的身体成分分析在非特异性间质性肺炎(NSIP)患者中应用潜力的研究。该研究对 71 名经委员会确诊为非特异性间质性肺炎的患者进行了单中心分析,结果显示,肌肉、纵隔脂肪和肺脂肪衰减体积相关指数与单变量分析中的生存率显著相关。根据肺容积归一化的 CT 肺脂肪衰减体积是预测死亡的独立指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
European Radiology Experimental
European Radiology Experimental Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
6.70
自引率
2.60%
发文量
56
审稿时长
18 weeks
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