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使用自动化和半自动化方法优化局部细胞计数

Hasita V Nalluri¹, Shantelle A Graff², Dragan Maric³

¹Surgical Neurology Branch, Flow and Imaging Cytometry Core Facility, Bethesda, MD, USA.

Neuroinformatics

|March 21, 2025

概括

自动化和半自动化基于对象的局部化分析 (OBCA) 可靠地量化脊髓状组织中的免疫细胞. 与手动计数相比,这些方法显著减少了分析时间,对于大型组织学数据集非常有价值.

科学领域:

神经免疫学神经免疫学
组织病理学组织病理学
计算生物学计算生物学

背景情况:

脊柱下椎空间的炎症会导致椎细胞的高细胞化.
多重复合免疫组织化学 (MP-IHC) 量化免疫细胞,但手动计数是有偏见的和耗时的.
现有的自动化方法面临着细胞形态学和局部化准确性方面的挑战.

研究的目的:

评估半自动和自动的基于对象的局部化分析 (OBCA),用于量化人类状组织中的免疫细胞.
在准确性,可靠性和效率方面,将OBCA方法与手动计数进行比较.
评估OBCA用于分析具有多种细胞形态的组织样本的实用性.

主要方法:

半自动化和自动化OBCA技术被应用于人类状组织部分.
使用OBCA方法和手动计数,量化了免疫细胞的局部化.
统计分析,包括相关性 (R2),用于比较方法.

主要成果:

半自动化和自动化OBCA在各种细胞形态学中都表现出高可靠性 (P < 0.0001).
自动计数显示与手动计数有很强的相关性 (R2 = 0.7764-0.9954),表明非关键精确计数的可靠性.
与手动计数相比,这两种OBCA技术显著减少了分析时间.

结论:

自动化和半自动化OBCA是可靠和高效的工具,用于量化免疫细胞在组织学样本.
这些方法比手动计数提供了显著的节省时间的优势,特别是对于大型数据集.
推OBCA用于分析免疫细胞透情况,如脊髓状炎症.

关键词:

在本地化,在本地化.量化量化量化量化组织组织组织组织.

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