Choi Seok-Jin, Yoon Soon Ho, Sung Jung-Joon, Lee Jong Hyuk
Department of Neurology, Seoul National University Hospital, Seoul, Republic of Korea.
Center for Hospital Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Ann Neurol. 2023 Dec;94(6):1116-1125. doi: 10.1002/ana.26775. Epub 2023 Sep 6.
The purpose of this study was to present the results of our investigation of the prognostic value of adipopenia and sarcopenia in patients with amyotrophic lateral sclerosis (ALS).
Consecutive patients with ALS with abdominal computed tomography (CT) were retrospectively identified at a single tertiary hospital between January 2010 and July 2021. Deep learning-based volumetric CT body composition analysis software was used to obtain abdominal waist fat volume, fat attenuation, and skeletal muscle area at the L3 level, then normalized to the fat volume index (FVI) and skeletal muscle index (SMI). Adipopenia and sarcopenia were defined as the sex-specific lowest quartile and SMI reference values, respectively. The associations of CT-derived body composition parameters with clinical variables, such as body mass index (BMI) and creatinine, were evaluated by Pearson correlation analyses, and associations with survival were assessed using the multivariable Cox regression analysis.
Eighty subjects (40 men, 65.5 ± 9.4 years of age) were investigated (median interval between disease onset and CT examination = 25 months). The mean BMI at the CT examination was 20.3 ± 4.3 kg/m . The BMI showed a positive correlation with both FVI (R = 0.70, p < 0.001) and SMI (R = 0.63, p < 0.001), and the serum creatinine level was associated with SMI (R = 0.68, p < 0.001). After adjusting for sex, age, King's stage, BMI, creatinine, progression rate, and sarcopenia, adipopenia was associated with shorter survival (hazard ratio [HR] = 5.94, 95% confidence interval [CI] = 1.01, 35.0, p = 0.049). In a subgroup analysis for subjects with nutritional failure (stage 4a), the HR of adipopenia was 15.1 (95% CI = 2.45, 93.4, p = 0.003).
Deep learning-based CT-derived adipopenia in patients with ALS is an independent poor prognostic factor for survival. ANN NEUROL 2023;94:1116-1125.
本研究旨在展示我们对肌萎缩侧索硬化症（ALS）患者脂肪减少和肌肉减少症的预后价值的调查结果。
在2010年1月至2021年7月期间，在一家单一的三级医院对连续的接受腹部计算机断层扫描（CT）的ALS患者进行回顾性识别。使用基于深度学习的容积CT身体成分分析软件获取腹部腰围脂肪体积、脂肪衰减以及L3水平的骨骼肌面积，然后将其标准化为脂肪体积指数（FVI）和骨骼肌指数（SMI）。脂肪减少症和肌肉减少症分别定义为特定性别的最低四分位数和SMI参考值。通过Pearson相关性分析评估CT衍生的身体成分参数与临床变量（如体重指数[BMI]和肌酐）之间的关联，并使用多变量Cox回归分析评估与生存率的关联。
对80名受试者（40名男性，年龄65.5±9.4岁）进行了调查（疾病发作与CT检查之间的中位间隔时间=25个月）。CT检查时的平均BMI为20.3±4.3kg/m²。BMI与FVI（R=0.70，p<0.001）和SMI（R=0.63，p<0.001）均呈正相关，血清肌酐水平与SMI相关（R=0.68，p<0.001）。在调整性别、年龄、King分期、BMI、肌酐、进展率和肌肉减少症后，脂肪减少症与较短的生存期相关（风险比[HR]=5.94，95%置信区间[CI]=1.01，35.0，p=0.049）。在营养衰竭（4a期）受试者的亚组分析中，脂肪减少症的HR为15.1（95%CI=2.45，93.4，p=0.003）。
基于深度学习的CT衍生的脂肪减少症是ALS患者生存的独立不良预后因素。《神经病学年鉴》2023年；94：1116 - 1125。
