Belaldavar Chetan, Angadi Punnya V, Mudenagudi Uma
Department of Oral Pathology and Microbiology, KLE VK Institute of Dental Sciences and Hospital, KLE Academy of Higher Education and Research (KAHER), Belgaum, Karnataka, India.
School of ECE, KLE Technological University, Hubli, Karnataka, India.
J Oral Maxillofac Pathol. 2024 Jul-Sep;28(3):381-386. doi: 10.4103/jomfp.jomfp_499_23. Epub 2024 Oct 15.
Grading of oral epithelial dysplasia (OED) has been plagued with intra-observer and inter-observer variations. To overcome this subjectivity, a more objective digital image analysis is obligatory using computer-aided software. The use of open-source software like QuPath, which is a new bio-image evaluation software program, may fulfil this growing need in virtual pathology. This study used the QuPath software for automatic analysis of morphometric parameters in hematoxylin and eosin (H and E)-stained digital images of oral epithelial dysplasia.
150 H and E digital images of varying grades of OED captured under 40x magnification were processed using QuPath software for automatic analysis of cellular and nuclear parameters.
The parameters that showed statistical significance included nuclear hematoxylin OD, nuclear eosin OD, cellular hematoxylin OD, cellular eosin OD, cytoplasm hematoxylin OD, and cytoplasmic eosin OD ( < 0.05), while none of the other parameters showed statistically significant differences. A prediction accuracy of 76%, 74%, and 70% for mild, moderate, and severe dysplasia was obtained, respectively.
The quantitative results outlined in this paper are encouraging to indicate that the use of this technique may improve the diagnostic reliability of OED. Morphometric analysis of OED using Qupath software can be fast and reproducible and can be quantitated automatically.
口腔上皮发育异常(OED)的分级一直存在观察者内和观察者间的差异。为克服这种主观性,使用计算机辅助软件进行更客观的数字图像分析是必要的。使用像QuPath这样的开源软件(一种新的生物图像评估软件程序)可能满足虚拟病理学中这种不断增长的需求。本研究使用QuPath软件对苏木精和伊红(H&E)染色的口腔上皮发育异常数字图像中的形态计量学参数进行自动分析。
使用QuPath软件对在40倍放大倍数下拍摄的150张不同等级OED的H&E数字图像进行处理,以自动分析细胞和细胞核参数。
具有统计学意义的参数包括细胞核苏木精光密度、细胞核伊红光密度、细胞苏木精光密度、细胞伊红光密度、细胞质苏木精光密度和细胞质伊红光密度(<0.05),而其他参数均未显示出统计学显著差异。轻度、中度和重度发育异常的预测准确率分别为76%、74%和70%。
本文概述的定量结果令人鼓舞,表明使用该技术可能提高OED的诊断可靠性。使用QuPath软件对OED进行形态计量分析可以快速且可重复,并且可以自动定量。