使用MRI对人类舌头肌肉的细分:运动神经元疾病的实地指南和验证
Thomas B Shaw1, Fernanda L Ribeiro2, Xiangyun Zhu3
1School of Electrical Engineering and Computer Science, The University of Queensland, St Lucia, QLD, Australia; Centre for Advanced Imaging, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, QLD, Australia; Department of Neurology, Royal Brisbane and Women's Hospital, Herston, QLD, Australia.
Computers in biology and medicine
|July 29, 2025
概括
量化人类舌头肌肉是一个挑战. 这项研究介绍了一种使用MRI扫描和AI测量舌头肌肉的半自动化方法,揭示了言语和吞缺陷的个体的较小体积.
科学领域:
- 生物医学工程 生物医学工程
- 神经成像是一种神经成像.
- 人体解剖学 解剖学 解剖学
背景情况:
- 由于它们的复杂,交织的结构,很难准确量化人类舌头肌肉.
- 现有的舌头肌肉测量方法缺乏精度和可扩展性.
- 舌头肌肉形态与各种神经和语言障碍有关.
研究的目的:
- 开发和验证一种半自动化方法,使用MRI精确测量人类舌头关键肌肉.
- 为了研究舌头肌肉体积与语言和吞缺陷之间的关系.
- 为了在现有的神经成像数据集中对舌头肌肉形态进行大规模的后期分析.
主要方法:
- 开发了一种半自动化细分管道,结合了人工智能辅助,以地图集为基础和手动方法.
- 一个手动策划的MRI扫描数据集被用于培训和验证.
- 该方法在178个MRI扫描上得到了验证,包括细分验证 (n=103) 和运动神经元疾病患者 (n=132) 的临床应用.
主要成果:
- 开发的方法准确地测量了五个关键的舌头肌肉.
- 发言和吞缺陷的个体表现出较小的舌头肌肉体积.
- 引入了一个规范化策略,以考虑到肌肉体积测量中的混人口因素.
结论:
- 半自动化方法提供了一种可靠的方法,用于从MRI数据中量化舌头肌肉形态.
- 减少舌头肌肉体积与言语和吞障碍有关,特别是在神经退行性疾病中.
- 这条管道有助于使用舌头肌肉分析作为各种影响舌头功能疾病的潜在生物标志物.
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