在组织学中使用本福德定律
Jasmine Caballero1, Daniel Gonzalez2, Dustin La Fleur3
1Universidad Autónoma de Guadalajara, Guadalajara, Mexico.
Journal of pathology informatics
|July 24, 2025
概括
本福德定律可以通过分析细胞染色模式,在数字病理幻灯片中检测癌症. 这种统计工具显示正常和癌症肝细胞之间的显著差异,有助于疾病检测.
科学领域:
- 数字病理学数字病理学
- 计算病理学计算病理学
- 医学中的统计分析.
背景情况:
- 数字病理学比传统方法具有优势,可以进行远程分析并降低成本.
- 数字病理学的数据量不断增加,需要新的分析工具.
- 班福德定律是分析第一和第二位数频率的统计工具,在数字病理学中具有潜在的应用.
研究的目的:
- 调查本福德定律在数字病理学中分析全幻灯片图像的适用性.
- 为了确定本福德定律是否可以根据定量组织形态测量数据区分正常和癌症肝脏组织.
- 评估本福德定律在识别疾病引起的细胞生长模式中障碍的有用性.
主要方法:
- 用QuPath软件对肝脏组织的全幻灯片图像进行了定量组织形态测量.
- 分析了来自323,039个细胞的数据 (20个幻灯片:15个癌症,5个正常).
- 本福德的自然性定律应用于13个数据类别,重点关注污点吸收和尺寸测量,将结果与基平方适合性测试进行比较.
主要成果:
- 两个数据类别,特别是与污点吸收相关的数据类别,满足了Benford定律的Chi-square适合性标准.
- 超过临界值的斑点吸收率数据的幻灯片在62.5%的病例中与癌症有关.
- 癌症肝脏组织显示测试统计数据高于6,而正常组织显示统计数据低于1.5,表明与本福德定律有很强的相关性.
结论:
- 班福德定律可以作为一个有效的统计工具来分析数字病理学数据,特别是检测细胞特征的异常,如染色吸收.
- 在使用本福德定律分析时,观察到正常和癌症肝脏组织之间的明显统计签名表明其在数字病理学中用于自动癌症检测的潜力.
- 对本福德定律应用的进一步研究可以提高在快速发展的数字病理学领域中疾病检测的效率和准确性.
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