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口腔免疫分析仪:一种使用图像分割和分类模型对口腔白斑进行免疫组织化学评估的软件工具。

OralImmunoAnalyser: a software tool for immunohistochemical assessment of oral leukoplakia using image segmentation and classification models.

作者信息

Al-Tarawneh Zakaria A, Pena-Cristóbal Maite, Cernadas Eva, Suarez-Peñaranda José Manuel, Fernández-Delgado Manuel, Mbaidin Almoutaz, Gallas-Torreira Mercedes, Gándara-Vila Pilar

机构信息

Computer Science Department, Mutah University, Karak, Jordan.

Centro Singular de Investigación en Tecnoloxías Intelixentes da USC, Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain.

出版信息

Front Artif Intell. 2024 Feb 26;7:1324410. doi: 10.3389/frai.2024.1324410. eCollection 2024.

Abstract

Oral cancer ranks sixteenth amongst types of cancer by number of deaths. Many oral cancers are developed from potentially malignant disorders such as oral leukoplakia, whose most frequent predictor is the presence of epithelial dysplasia. Immunohistochemical staining using cell proliferation biomarkers such as ki67 is a complementary technique to improve the diagnosis and prognosis of oral leukoplakia. The cell counting of these images was traditionally done manually, which is time-consuming and not very reproducible due to intra- and inter-observer variability. The software presently available is not suitable for this task. This article presents the OralImmunoAnalyser software (registered by the University of Santiago de Compostela-USC), which combines automatic image processing with a friendly graphical user interface that allows investigators to oversee and easily correct the automatically recognized cells before quantification. OralImmunoAnalyser is able to count the number of cells in three staining levels and each epithelial layer. Operating in the daily work of the Odontology Faculty, it registered a sensitivity of 64.4% and specificity of 93% for automatic cell detection, with an accuracy of 79.8% for cell classification. Although expert supervision is needed before quantification, OIA reduces the expert analysis time by 56.5% compared to manual counting, avoiding mistakes because the user can check the cells counted. Hence, the SUS questionnaire reported a mean score of 80.9, which means that the system was perceived from good to excellent. OralImmunoAnalyser is accurate, trustworthy, and easy to use in daily practice in biomedical labs. The software, for Windows and Linux, with the images used in this study, can be downloaded from https://citius.usc.es/transferencia/software/oralimmunoanalyser for research purposes upon acceptance.

摘要

口腔癌在癌症死亡类型中排名第十六。许多口腔癌是由潜在恶性疾病发展而来,如口腔白斑,其最常见的预测指标是上皮发育异常。使用细胞增殖生物标志物(如ki67)进行免疫组织化学染色是一种辅助技术,可改善口腔白斑的诊断和预后。这些图像的细胞计数传统上是手动完成的,由于观察者内部和观察者之间的差异,这既耗时又不太可重复。目前可用的软件不适合这项任务。本文介绍了OralImmunoAnalyser软件(由圣地亚哥德孔波斯特拉大学-USC注册),该软件将自动图像处理与友好的图形用户界面相结合,使研究人员在定量之前能够监督并轻松纠正自动识别的细胞。OralImmunoAnalyser能够对三个染色水平和每个上皮层中的细胞数量进行计数。在牙科学院的日常工作中运行时,其自动细胞检测的灵敏度为64.4%,特异性为93%,细胞分类的准确率为79.8%。尽管在定量之前需要专家监督,但与手动计数相比,OIA将专家分析时间减少了56.5%,避免了错误,因为用户可以检查计数的细胞。因此,SUS问卷报告的平均得分为80.9,这意味着该系统被认为从良好到优秀。OralImmunoAnalyser准确、可靠且易于在生物医学实验室的日常实践中使用。该软件适用于Windows和Linux,连同本研究中使用的图像,经接受后可从https://citius.usc.es/transferencia/software/oralimmunoanalyser下载用于研究目的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4da3/10925674/ec1bf03dc190/frai-07-1324410-g0001.jpg

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