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基于计算机断层扫描的人体成分分析及其在肺癌治疗中的作用。

Computed Tomography-based Body Composition Analysis and Its Role in Lung Cancer Care.

机构信息

Departments of Radiology, Division of Thoracic Imaging and Intervention.

Surgery, Division of Thoracic Surgery.

出版信息

J Thorac Imaging. 2020 Mar;35(2):91-100. doi: 10.1097/RTI.0000000000000428.

Abstract

Body composition analysis, also referred to as analytic morphomics, morphomics, or morphometry, describes the measurement of imaging biomarkers of body composition such as muscle and adipose tissue, most commonly on computed tomography (CT) images. A growing body of literature supports the use of such metrics derived from routinely acquired CT images for risk prediction in various patient populations, including those with lung cancer. Metrics include cross-sectional area and attenuation of skeletal muscle and subcutaneous, visceral, and intermuscular adipose tissue. The purpose of this review is to provide an overview of the concepts, definitions, assessment tools, segmentation techniques and associated pitfalls, interpretation of those measurements on chest and abdomen CT, and a discussion of reported outcomes associated with body composition metrics in patients with early-stage and advanced lung cancer.

摘要

身体成分分析,也称为分析形态学、形态学或形态计量学,描述了对身体成分成像生物标志物的测量,如肌肉和脂肪组织,最常用于计算机断层扫描(CT)图像。越来越多的文献支持使用从常规 CT 图像中获得的此类指标来预测各种患者群体(包括肺癌患者)的风险。这些指标包括骨骼肌和皮下、内脏和肌间脂肪组织的横截面积和衰减。本综述的目的是提供一个概述,介绍概念、定义、评估工具、分割技术和相关陷阱、胸部和腹部 CT 上的这些测量的解读,以及讨论与早期和晚期肺癌患者的身体成分指标相关的报告结果。

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