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文章:

结直肠癌表型的多参数评估方法:整合形态功能评估与计算机断层扫描

Multiparametric Approach to the Colorectal Cancer Phenotypes Integrating Morphofunctional Assessment and Computer Tomography

原文发布日期:15 October 2024

DOI: 10.3390/cancers16203493

类型: Article

开放获取: 是

 

英文摘要:

(1) Background: Accurate body composition assessment in CCR patients is crucial due to the high prevalence of malnutrition, sarcopenia, and cachexia affecting survival. This study evaluates the correlation between body composition assessed by CT imaging as a reference technique, BIVA, nutritional ultrasound, and handgrip strength in CCR patients. (2) Methods: This retrospective study included CCR patients assessed by the Endocrinology and Nutrition Services of Virgen de la Victoria in Malaga and Vall d’Hebron in Barcelona from October 2018 to July 2023. Assessments included anthropometry, BIVA, NU, HGS, and AI-assisted CT analysis at the L3 level for body composition. Pearson’s analysis determined the correlation of CT-derived variables with BIVA, NU, and HGS. (3) Results: A total of 267 CCR patients (mean age 68.2 ± 10.9 years, 61.8% men) were studied. Significant gender differences were found in body composition and strength. CT-SMI showed strong correlations with body cell mass (r = 0.65), rectus femoris cross-sectional area (r = 0.56), and handgrip strength (r = 0.55), with a Cronbach’s alpha of 0.789. CT-based adipose tissue measurements showed significant correlations with fat mass (r = 0.56), BMI (r = 0.78), A-SAT (r = 0.49), and L-SAT (r = 0.66). Regression analysis indicated a high predictive power for CT-SMI, explaining approximately 80% of its variance (R2= 0.796). (4) Conclusions: Comprehensive screening of colorectal cancer patients through BIVA, NU, HGS, and CT optimizes the results of the evaluation. These methods complement each other in assessing muscle mass, fat distribution, and nutritional status in CCR. When CT is unavailable or bedside assessment is needed, HGS, BIVA, and NU provide an accurate assessment of body composition.

 

摘要翻译: 

(1)背景:结直肠癌患者营养不良、肌肉减少症及恶病质高发,严重影响生存率,因此准确评估其身体成分至关重要。本研究以CT影像评估为参照标准,探讨其与生物电阻抗矢量分析、营养超声及握力测量在结直肠癌患者身体成分评估中的相关性。(2)方法:这项回顾性研究纳入2018年10月至2023年7月期间马拉加维多利亚医院与巴塞罗那瓦尔德希伯伦医院内分泌营养科评估的结直肠癌患者。评估内容包括人体测量学、生物电阻抗矢量分析、营养超声、握力测试,以及通过人工智能辅助的第三腰椎水平CT扫描进行身体成分分析。采用皮尔逊分析法确定CT衍生变量与生物电阻抗矢量分析、营养超声及握力测试指标的相关性。(3)结果:共纳入267例结直肠癌患者(平均年龄68.2±10.9岁,男性占61.8%)。身体成分与力量指标存在显著性别差异。CT骨骼肌指数与体细胞质量(r=0.65)、股直肌横截面积(r=0.56)及握力(r=0.55)呈强相关,克隆巴赫系数为0.789。基于CT的脂肪组织测量指标与脂肪质量(r=0.56)、体重指数(r=0.78)、腹部皮下脂肪面积(r=0.49)及腰部皮下脂肪面积(r=0.66)显著相关。回归分析显示CT骨骼肌指数具有高预测效力,可解释约80%的变异度(R²=0.796)。(4)结论:通过生物电阻抗矢量分析、营养超声、握力测试与CT扫描对结直肠癌患者进行综合筛查,可优化评估结果。这些方法在评估肌肉质量、脂肪分布和营养状况方面具有互补性。当无法进行CT检查或需床旁评估时,握力测试、生物电阻抗矢量分析与营养超声可提供准确的身体成分评估。

 

原文链接:

Multiparametric Approach to the Colorectal Cancer Phenotypes Integrating Morphofunctional Assessment and Computer Tomography

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