(1)背景:肌肉质量的评估在结直肠癌(CRC)患者的营养评估中至关重要。由于肌肉质量下降与并发症增加和预后较差有关。这项研究旨在评估AI辅助L3CT在评估身体成分和确定低肌肉质量方面的实用性,同时使用全球营养不良领导倡议(GLIM)营养不良标准和欧洲老年人肌肉减少症工作组(EWGSOP2)CRC患者手术前的肌肉减少症标准。此外,我们旨在建立男性和女性肌肉质量的分界点,并提出其在这些诊断框架中的应用。(2)方法:这项回顾性观察性研究包括由马拉加地区大学医院内分泌学和营养服务评估的CRC患者,马拉加的VirgendelaVictoria,和巴塞罗那的Valld\'Hebrón,从2018年10月到2023年7月。形态功能评估,包括人体测量,生物阻抗分析(BIA),和握力,进行应用GLIM营养不良标准和EWGSOP2肌肉减少症标准。通过AI辅助分析L3水平的CT图像进行身体成分评估。ROC分析用于确定从CT分析得出的关于低肌肉质量诊断的变量的预测能力并描述截止点。(3)结果:共纳入586例患者,平均年龄68.4±10.2岁。使用GLIM标准,245例患者(41.8%)被诊断为营养不良。应用EWGSOP2标准,56例(9.6%)被诊断为肌肉减少症。骨骼肌指数(SMI)的ROC曲线分析显示,肌肉面积具有很强的判别能力,可以检测低脂质量指数(FFMI)(AUC=0.82,95%CI0.77-0.87,p<0.001)。确定的用于诊断低FFMI的SMI截止值为32.75cm2/m2(Sn77%,Sp64.3%;女性AUC=0.79,95%CI0.70-0.87,p<0.001),和39.9cm2/m2(Sn77%,Sp72.7%;男性AUC=0.85,95%CI0.80-0.90,p<0.001)。此外,骨骼肌面积(SMA)对检测低阑尾骨骼肌质量(ASMM)具有良好的判别能力(AUC=0.71,95%CI0.65-0.76,p<0.001)。用于诊断低ASMM的确定的SMA截止点为83.2cm2(Sn76.7%,Sp55.3%;女性AUC=0.77,95%CI0.69-0.84,p<0.001)和112.6cm2(Sn82.3%,Sp58.6%;男性AUC=0.79,95%CI0.74-0.85,p<0.001)。(4)结论:使用CT进行AI辅助的身体成分评估是结直肠癌患者手术前形态功能评估的有价值的工具。CT为应用GLIM营养不良标准和EWGSOP2肌肉减少症标准提供了肌肉质量的定量数据,具有为诊断用途建立的特定截止点。
(1) Background: The assessment of muscle mass is crucial in the nutritional evaluation of patients with colorectal cancer (CRC), as decreased muscle mass is linked to increased complications and poorer prognosis. This study aims to evaluate the utility of AI-assisted L3 CT for assessing body composition and determining low muscle mass using both the Global Leadership Initiative on Malnutrition (GLIM) criteria for malnutrition and the European Working Group on Sarcopenia in Older People (EWGSOP2) criteria for sarcopenia in CRC patients prior to surgery. Additionally, we aim to establish cutoff points for muscle mass in men and women and propose their application in these diagnostic frameworks. (2) Methods: This retrospective observational study included CRC patients assessed by the Endocrinology and Nutrition services of the Regional University Hospitals of Malaga, Virgen de la Victoria of Malaga, and Vall d\'Hebrón of Barcelona from October 2018 to July 2023. A morphofunctional assessment, including anthropometry, bioimpedance analysis (BIA), and handgrip strength, was conducted to apply the GLIM criteria for malnutrition and the EWGSOP2 criteria for sarcopenia. Body composition evaluation was performed through AI-assisted analysis of CT images at the L3 level. ROC analysis was used to determine the predictive capacity of variables derived from the CT analysis regarding the diagnosis of low muscle mass and to describe cutoff points. (3) Results: A total of 586 patients were enrolled, with a mean age of 68.4 ± 10.2 years. Using the GLIM criteria, 245 patients (41.8%) were diagnosed with malnutrition. Applying the EWGSOP2 criteria, 56 patients (9.6%) were diagnosed with sarcopenia. ROC curve analysis for the skeletal muscle index (SMI) showed a strong discriminative capacity of muscle area to detect low fat-free mass index (FFMI) (AUC = 0.82, 95% CI 0.77-0.87, p < 0.001). The identified SMI cutoff for diagnosing low FFMI was 32.75 cm2/m2 (Sn 77%, Sp 64.3%; AUC = 0.79, 95% CI 0.70-0.87, p < 0.001) in women, and 39.9 cm2/m2 (Sn 77%, Sp 72.7%; AUC = 0.85, 95% CI 0.80-0.90, p < 0.001) in men. Additionally, skeletal muscle area (SMA) showed good discriminative capacity for detecting low appendicular skeletal muscle mass (ASMM) (AUC = 0.71, 95% CI 0.65-0.76, p < 0.001). The identified SMA cutoff points for diagnosing low ASMM were 83.2 cm2 (Sn 76.7%, Sp 55.3%; AUC = 0.77, 95% CI 0.69-0.84, p < 0.001) in women and 112.6 cm2 (Sn 82.3%, Sp 58.6%; AUC = 0.79, 95% CI 0.74-0.85, p < 0.001) in men. (4) Conclusions: AI-assisted body composition assessment using CT is a valuable tool in the morphofunctional evaluation of patients with colorectal cancer prior to surgery. CT provides quantitative data on muscle mass for the application of the GLIM criteria for malnutrition and the EWGSOP2 criteria for sarcopenia, with specific cutoff points established for diagnostic use.