Chen Moxi, Wang Xue, Han Meifen, Li Yunzhu, Yu Nanze, Long Xiao, Chen Wei
Department of Clinical Nutrition, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Department of Pharmacy, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China.
Front Nutr. 2023 Mar 13;10:1115079. doi: 10.3389/fnut.2023.1115079. eCollection 2023.
Prompt diagnosis of malnutrition and appropriate interventions can substantially improve the prognosis of patients with cancer; however, it is difficult to unify the tools for screening malnutrition risk. 3D imaging technology has been emerging as an approach to assisting in the diagnosis of diseases, and we designed this study to explore its application value in identifying the malnutrition phenotype and evaluating nutrition status.
Hospitalized patients treating with maintenance chemotherapy for advanced malignant tumor of digestive system were recruited from the Department of Oncology, whose NRS 2002 score > 3. Physical examination and body composition data of patients at risk for malnutrition were analyzed by physicians trained to complete a subjective global assessment. The facial depression index was recognized using the Antera 3D® system, temporal and periorbital depression indexes were acquired using the companion software Antera Pro. This software captures quantitative data of depression volume, affected area, and maximum depth of temporal and periorbital concave areas.
A total of 53 inpatients with malnutrition-related indicators were included. The volume of temporal depression was significantly negatively correlated with upper arm circumference ( = -0.293, = 0.033) and calf circumference ( = -0.285, = 0.038). The volume and affected area of periorbital depression were significantly negatively correlated with fat mass index ( = -0.273, = 0.048 and = -0.304, = 0.026, respectively) and percent body fat ( = -0.317, = 0.021 and = -0.364, = 0.007, respectively). The volume and affected area of temporal depression in patients with muscle loss phenotype (low arm circumference/low calf circumference/low handgrip strength/low fat-free mass index) were significantly higher than those in patients without muscle loss. Moreover, patients with fat mass loss phenotype (low fat mass index) showed a significant increase in the volume and affected area of periorbital depression.
The facial temporal region, and periorbital depression indicators extracted by 3D image recognition technology were significantly associated with the phenotype of malnutrition-related muscle and fat loss and showed a trend of grade changes in the population of different subjective global assessment nutritional classifications.
及时诊断营养不良并采取适当干预措施可显著改善癌症患者的预后；然而，营养不良风险筛查工具难以统一。三维成像技术已成为辅助疾病诊断的一种方法，我们设计本研究以探索其在识别营养不良表型和评估营养状况方面的应用价值。
从肿瘤科招募接受维持化疗的晚期消化系统恶性肿瘤住院患者，其NRS 2002评分>3。由经过培训以完成主观全面评定的医生分析有营养不良风险患者的体格检查和身体成分数据。使用Antera 3D®系统识别面部凹陷指数，使用配套软件Antera Pro获取颞部和眶周凹陷指数。该软件可采集颞部和眶周凹陷区域的凹陷体积、受影响面积和最大深度的定量数据。
共纳入53例有营养不良相关指标的住院患者。颞部凹陷体积与上臂围显著负相关（r = -0.293，P = 0.033）和小腿围显著负相关（r = -0.285，P = 0.038）。眶周凹陷体积和受影响面积与脂肪质量指数显著负相关（分别为r = -0.273，P = 0.048和r = -0.304，P = 0.026）以及与体脂百分比显著负相关（分别为r = -0.317，P = 0.021和r = -0.364，P = 0.007）。有肌肉减少表型（低上臂围/低小腿围/低握力/低脂瘦体重指数）患者的颞部凹陷体积和受影响面积显著高于无肌肉减少的患者。此外，有脂肪量减少表型（低脂肪质量指数）的患者眶周凹陷体积和受影响面积显著增加。
通过三维图像识别技术提取的面部颞部区域和眶周凹陷指标与营养不良相关的肌肉和脂肪减少表型显著相关，并在不同主观全面评定营养分类人群中呈现等级变化趋势。
