Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, 101, Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
Institute of Radiation Medicine, Seoul National University Medical Research Center, 101, Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
Respir Res. 2024 Feb 28;25(1):103. doi: 10.1186/s12931-024-02712-6.
The prognostic role of changes in body fat in patients with idiopathic pulmonary fibrosis (IPF) remains underexplored. We investigated the association between changes in body fat during the first year post-diagnosis and outcomes in patients with IPF.
This single-center, retrospective study included IPF patients with chest CT scan and pulmonary function test (PFT) at diagnosis and a one-year follow-up between January 2010 and December 2020. The fat area (cm, sum of subcutaneous and visceral fat) and muscle area (cm) at the T12-L1 level were obtained from chest CT images using a fully automatic deep learning-based software. Changes in the body composition were dichotomized using thresholds dividing the lowest quartile and others, respectively (fat area: -52.3 cm, muscle area: -7.4 cm). Multivariable Cox regression analyses adjusted for PFT result and IPF extent on CT images and the log-rank test were performed to assess the association between the fat area change during the first year post-diagnosis and the composite outcome of death or lung transplantation.
In total, 307 IPF patients (69.3 ± 8.1 years; 238 men) were included. During the first year post-diagnosis, fat area, muscle area, and body mass index (BMI) changed by -15.4 cm, -1 cm, and - 0.4 kg/m, respectively. During a median follow-up of 47 months, 146 patients had the composite outcome (47.6%). In Cox regression analyses, a change in the fat area < -52.3 cm was associated with composite outcome incidence in models adjusted with baseline clinical variables (hazard ratio [HR], 1.566, P = .022; HR, 1.503, P = .036 in a model including gender, age, and physiology [GAP] index). This prognostic value was consistent when adjusted with one-year changes in clinical variables (HR, 1.495; P = .030). However, the change in BMI during the first year was not a significant prognostic factor (P = .941). Patients with a change in fat area exceeding this threshold experienced the composite outcome more frequently than their counterparts (58.4% vs. 43.9%; P = .007).
A ≥ 52.3 cm decrease in fat area, automatically measured using deep learning technique, at T12-L1 in one year post-diagnosis was an independent poor prognostic factor in IPF patients.
特发性肺纤维化(IPF)患者体脂变化的预后作用仍未得到充分探索。我们研究了诊断后第一年体脂变化与 IPF 患者结局之间的关系。
这是一项单中心、回顾性研究,纳入了 2010 年 1 月至 2020 年 12 月期间在诊断时和诊断后一年进行胸部 CT 扫描和肺功能检查(PFT)的 IPF 患者。使用基于深度学习的全自动软件从胸部 CT 图像中获取 T12-L1 水平的脂肪面积(cm,皮下脂肪和内脏脂肪之和)和肌肉面积(cm)。使用截断值将身体成分变化分为最低四分位数和其他组(脂肪面积:-52.3cm,肌肉面积:-7.4cm)。使用多变量 Cox 回归分析调整 PFT 结果和 CT 图像上的 IPF 程度,并进行对数秩检验,以评估诊断后第一年体脂变化与死亡或肺移植复合结局之间的关系。
共纳入 307 例 IPF 患者(69.3±8.1 岁;238 例男性)。在诊断后第一年,脂肪面积、肌肉面积和 BMI 分别变化了-15.4cm、-1cm 和-0.4kg/m2。在中位随访 47 个月期间,146 例患者发生复合结局(47.6%)。在 Cox 回归分析中,调整基线临床变量后,脂肪面积< -52.3cm 与复合结局发生率相关(风险比[HR],1.566,P=0.022;HR,1.503,P=0.036,纳入性别、年龄和生理学[GAP]指数模型)。当调整一年内临床变量的变化时,该预后价值仍然一致(HR,1.495;P=0.030)。然而,诊断后第一年 BMI 的变化不是一个显著的预后因素(P=0.941)。脂肪面积变化超过该阈值的患者比其他患者更频繁地发生复合结局(58.4%比 43.9%;P=0.007)。
使用深度学习技术自动测量的 T12-L1 处一年后脂肪面积减少≥52.3cm 是 IPF 患者的独立不良预后因素。