一个全面和可靠的协议,用于人工分段的人类关闭体,使用高分辨率的MRI
Steven Seung-Suk Kang1, Joseph Bodenheimer2, Kayley Morris3
1Department of Biomedical Sciences, University of Missouri-Kansas City, Kansas City, MO, USA. kangseung@umkc.edu.
Brain structure & function
|August 13, 2025
概括
我们开发了一种可靠的方法来细分人类的关闭体,这是一个对理解神经精神疾病至关重要的大脑结构. 这个协议可以为未来的研究提供精确的神经成像.
科学领域:
- 神经成像是一种神经成像.
- 人类大脑解剖学 人类大脑解剖学
背景情况:
- 关闭层是一个高度连接的大脑结构,在人类认知和神经精神疾病中作用不明.
- 它复杂而薄的形态阻碍了标准神经成像中准确的划分和分析.
- 之前的MRI研究还没有清楚地描述了关节的下部部分.
研究的目的:
- 开发一个全面和可靠的人工分段协议,用于人类关闭.
- 建立一个解剖学精确的神经成像调查的方法.
- 提出一个几何方法,以分隔封闭区到子区域.
主要方法:
- 开发了一种手动细分协议,使用细胞分辨率的大脑图谱和高分辨率MRI (0.7毫米同otropic).
- 包含了详细的指导方针来划分整个封闭区,包括劣势地区.
- 提出了一种几何方法,将闭层分为背部,腹部和部的子区域.
主要成果:
- 该协议显示了高的inter-和intra-rater可靠性 (ICC> 0.89,DSC> 0.85),证实了可复制性.
- 年轻成年人的平均双边关闭体积为3307.5毫米3 (约. 0.21%的内体积).
- 成功地划出了整个关闭区域,包括以前未被描述的下部部分.
结论:
- 开发的手动细分协议为准确的人类关闭空间神经成像提供了坚实的基础.
- 这一协议有助于未来研究关闭层在正常和异常大脑功能中的作用.
- 拟议的次区域分片为调查关闭体解剖学和功能提供了一个新的框架.
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