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

IF 2 4区医学 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Journal of Thoracic Imaging Pub Date : 2024-08-26 DOI:10.1097/RTI.0000000000000803

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

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引用次数: 0

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=

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.

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自动三维人体成分分析作为特发性肺纤维化患者存活率的预测指标。

目的：特发性肺纤维化（IPF）是最常见的间质性肺病，中位生存时间为2至5年。本研究的重点是建立一种新型成像生物标志物：本研究对中位年龄为 70 岁的 79 名患者（19% 为女性）进行了回顾性研究。我们将全自动身体成分分析（BCA）特征（骨骼、肌肉、总脂肪组织、肌间脂肪组织和肌内脂肪组织）合并为 "肌肉疏松症"、"脂肪 "和 "肌骨骼疏松症 "指数，并对存活时间超过或少于 2 年的患者进行了比较。此外，我们还按中位数（高=≥中位数，低=结果）对组群进行了划分：肉质疏松症和脂肪指数高、骨质疏松指数低与中位生存期延长有关（肉质疏松症指数高与低分别为35个月和16个月，P=0.066；脂肪指数高与低分别为44个月和14个月，P=0.066）：全自动 BCA 为 IPF 患者的总生存期提供了具有预测价值的生物标志物。

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

Journal of Thoracic Imaging 医学-核医学

CiteScore

7.10

自引率

9.10%

发文量

审稿时长

6-12 weeks

期刊介绍： Journal of Thoracic Imaging (JTI) provides authoritative information on all aspects of the use of imaging techniques in the diagnosis of cardiac and pulmonary diseases. Original articles and analytical reviews published in this timely journal provide the very latest thinking of leading experts concerning the use of chest radiography, computed tomography, magnetic resonance imaging, positron emission tomography, ultrasound, and all other promising imaging techniques in cardiopulmonary radiology. Official Journal of the Society of Thoracic Radiology: Japanese Society of Thoracic Radiology Korean Society of Thoracic Radiology European Society of Thoracic Imaging.