医学
间质性肺病
肺活量
高分辨率计算机断层扫描
内科学
肺容积
心脏病学
肺
肺功能测试
放射科
霍恩斯菲尔德秤
定量计算机断层扫描
计算机断层摄影术
肺功能
扩散能力
骨密度
骨质疏松症
作者
Hiromasa Nakayasu,Yuzo Suzuki,Masato Kono,Dai Hashimoto,Shinpei Kato,Koshi Yokomura,Yusuke Inoue,Hideki Yasui,Hironao Hozumi,Masato Karayama,Kazuki Furuhashi,Noriyuki Enomoto,Tomoyuki Fujisawa,Naoki Inui,Takafumi Suda
出处
期刊:Respirology
[Wiley]
日期:2025-03-17
卷期号:30 (7): 652-661
摘要
ABSTRACT Background and Objective Interstitial lung disease (ILD) is a leading cause of morbidity and mortality in patients with systemic sclerosis (SSc). The disease course of SSc‐related ILD (SSc‐ILD) is heterogeneous, and several risk‐based models have been developed. This study aimed to quantitatively measure volume loss and disease extent and subsequently evaluate their associations with the development of end‐stage lung disease (ESLD). Methods Lung volume (LV) and disease extent were retrospectively and quantitatively evaluated in two cohorts (exploratory: n = 70; validation: n = 42) using high‐resolution computed tomography at the time of SSc‐ILD diagnosis, compared to controls ( n = 70). LV was quantitatively measured using three‐dimensional imaging (3D‐image) and standardised by predicted forced vital capacity (standardised LV). The ratio of the normally attenuated LV (range, −950 to −750 Hounsfield units) to the whole‐LV (NL%) was also measured using 3D‐image. The associations of these variables with ESLD were evaluated. Results Volume loss and normal lung area loss were noted in patients with SSc‐ILD compared with controls, especially in the lower lobes. Meanwhile, extended ILD lesions without volume reduction were observed in the upper lobes. Both decreased standardised LV and NL% were associated with ESLD development, and age and NL% were significant risk factors for ESLD independent of pulmonary function test parameters and standardised LV. A composite model consisting of age and NL% successfully stratified patients with SSc‐ILD based on the risk of ESLD. Conclusion 3D‐image may be a useful technique for assessing disease severity and predicting the risk for ESLD in patients with SSc‐ILD. image
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