自动三维身体成分分析作为特发性肺纤维化患者生存的预测指标

Automated 3D-Body Composition Analysis as a Predictor of Survival in Patients With Idiopathic Pulmonary Fibrosis.

作者信息

Salhöfer Luca, Bonella Francesco, Meetschen Mathias, Umutlu Lale, Forsting Michael, Schaarschmidt Benedikt Michael, Opitz Marcel Klaus, Kleesiek Jens, Hosch Rene, Koitka Sven, Parmar Vicky, Nensa Felix, Haubold Johannes

机构信息

Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.

Institute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany.

出版信息

J Thorac Imaging. 2025 Mar 1;40(2):e0803. doi: 10.1097/RTI.0000000000000803.

DOI:10.1097/RTI.0000000000000803

PMID:39183570

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11837968/

Abstract

PURPOSE

Idiopathic pulmonary fibrosis (IPF) is the most common interstitial lung disease, with a median survival time of 2 to 5 years. The focus of this study is to establish a novel imaging biomarker.

MATERIALS AND METHODS

In this study, 79 patients (19% female) with a median age of 70 years were studied retrospectively. Fully automated body composition analysis (BCA) features (bone, muscle, total adipose tissue, intermuscular, and intramuscular adipose tissue) were combined into Sarcopenia, Fat, and Myosteatosis indices and compared between patients with a survival of more or less than 2 years. In addition, we divided the cohort at the median (high=≥ median, low=<median) of the respective BCA index and tested the impact on the overall survival using the Kaplan-Meier methodology, a log-rank test, and adjusted multivariate Cox-regression analysis.

RESULTS

A high Sarcopenia and Fat index and low Myosteatosis index were associated with longer median survival (35 vs. 16 mo for high vs. low Sarcopenia index, P =0.066; 44 vs. 14 mo for high vs. low Fat index, P <0.001; and 33 vs. 14 mo for low vs. high Myosteatosis index, P =0.0056) and better 5-year survival rates (34.0% vs. 23.6% for high vs. low Sarcopenia index; 47.3% vs. 9.2% for high vs. low Fat index; and 11.2% vs. 42.7% for high vs. low Myosteatosis index). Adjusted multivariate Cox regression showed a significant impact of the Fat (HR=0.71, P =0.01) and Myosteatosis (HR=1.12, P =0.005) on overall survival.

CONCLUSION

The fully automated BCA provides biomarkers with a predictive value for the overall survival in patients with IPF.

摘要

目的

特发性肺纤维化（IPF）是最常见的间质性肺疾病，中位生存时间为2至5年。本研究的重点是建立一种新的影像学生物标志物。

材料与方法

本研究对79例患者（19%为女性）进行了回顾性研究，患者中位年龄为70岁。将全自动身体成分分析（BCA）特征（骨骼、肌肉、总脂肪组织、肌间和肌内脂肪组织）合并为肌肉减少症、脂肪和肌脂变性指数，并在生存时间大于或小于2年的患者之间进行比较。此外，我们将队列按照各自BCA指数的中位数（高=≥中位数，低=<中位数）进行划分，并使用Kaplan-Meier方法、对数秩检验和调整后的多变量Cox回归分析来测试其对总生存的影响。

结果

高肌肉减少症和脂肪指数以及低肌脂变性指数与更长的中位生存时间相关（高与低肌肉减少症指数分别为35个月和16个月，P =0.066；高与低脂肪指数分别为44个月和14个月，P <0.001；低与高肌脂变性指数分别为33个月和14个月，P =0.0056）以及更好的5年生存率（高与低肌肉减少症指数分别为34.0%和23.6%；高与低脂肪指数分别为47.3%和9.2%；高与低肌脂变性指数分别为11.2%和42.7%）。调整后的多变量Cox回归显示脂肪（HR=0.71，P =0.01）和肌脂变性（HR=1.12，P =0.005）对总生存有显著影响。