自动胸部CT三维量化身体组成:脂肪组织和准脊椎肌肉
Akinori Hata1,2,3, Yohei Muraguchi4, Minoru Nakatsugawa4
1Department of Radiology, Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. a-hata@radiol.med.osaka-u.ac.jp.
Scientific reports
|December 31, 2024
概括
开发了一种人工智能 (AI) 算法,用于在胸部CT扫描上自动3D细分脂肪组织和准脊椎肌肉. 这种人工智能工具证明了临床应用的高准确性和可行性.
科学领域:
- 放射学 放射学是一门学科.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 准确量化脂肪组织和骨肌肉对于评估患者的健康状况和疾病进展至关重要.
- 在CT扫描上手动细分这些组织是耗时的,容易引起观察者之间的变化.
研究的目的:
- 开发和评估自动化人工智能 (AI) 算法的可行性,用于胸部CT上的脂肪组织和准脊椎肌肉的3D细分.
- 与手动细分相比,评估AI算法的准确性 (基本真相).
主要方法:
- 一项回顾性研究利用波士顿肺癌研究 (2000-2011) 的数据.
- 开发一种人工智能算法,用于对皮下和内脏脂肪组织 (SAT和VAT) 以及准脊椎肌肉进行3D细分.
- 使用AI算法计算肌肉面积,平均衰减和肌肉间脂肪组织百分比 (IMAT%).
- 使用Dice分数和相关系数对独立测试集的手动细分进行性能评估.
主要成果:
- 人工智能算法在分段准确性方面获得了0.87以上的Dice分数.
- 对于VAT/SAT比率,肌肉衰减值和IMAT%与地面真相相比,观察到非常好的相关性 (r > 0.98,p < 0.001).
- 发现了最小的平均差异:VAT/SAT比率为0.7%,肌肉衰减为1 HU,IMAT%为<1%.
结论:
- 成功开发了一种可行且准确的AI算法,用于在胸部CT上自动3D细分脂肪组织和准脊椎肌肉.
- 人工智能工具显示出在临床实践中精简人体构成定量分析的潜力.
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