完全自动化的CT衍生体质组合分析揭示了功能性上腺皮层癌症的萨尔科佩尼亚
Prasanna Santhanam1, Roshan Dinparastisaleh2, Karteek Popuri3
1Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Asthma and Allergy Center, Johns Hopkins University School of Medicine, 5501 Hopkins Bayview Circle, Suite 3 B 73, Baltimore, MD, 21224, USA. psantha1@jhmi.edu.
Scientific reports
|May 28, 2024
概括
额外皮层癌 (ACC) 与良性病变相比,显示出显著的肌肉损失 (肉症). 功能性ACC表现出加速的肉,这表明身体组成分析有助于了解癌症进展和预后.
科学领域:
- 在瘤学瘤学.
- 放射学 放射学是一门学科.
- 身体组成分析 身体成分分析
背景情况:
- 身体构成,特别是肌肉质量 (sarcopenia),对于癌症预后至关重要.
- 基于手动CT的肌肉质量估计是耗时和劳动密集的.
- 自动化身体成分分析提供了一个快速而准确的替代方案.
研究的目的:
- 为了评估上皮癌 (ACC) 和良性上腺病变之间的身体组成差异.
- 为了研究ACC功能和肉症之间的关联.
- 探索自动化身体组成分析在ACC研究中的实用性.
主要方法:
- 使用完全自动化的身体组成分析技术.
- 分析了来自癌症成像档案 (TCIA) 和高等学术中心的医学图像.
- 在ACC和良性上腺病变之间,比较了身体组成指标,重点是肌肉质量.
主要成果:
- 与良性上腺病变相比,上腺皮质癌 (ACC) 显示出显著更大的肉症.
- 功能性ACCs比非功能性ACCs表现出更加速的肉症.
- 自动化分析证实了高准确度的身体组成的确定.
结论:
- 自动化体质成分分析是评估ACC. sarcopenia的一种可行的工具.
- 皮症是上腺皮癌的一个重要因素,可能会影响预后.
- 对身体组成和ACC预后的进一步研究可能会为癌症治疗中的营养策略提供信息.
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