Abstract :

Oral cancer represents the sixteenth type 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 diagnosis  and prognosis of oral leukoplakia. The cell counting of these images was traditionally done manually, being time-consuming and not very reproducible due to intra- and inter-observer variability. The available softwares are not suitable for this task. The current paper presents the OralImmunoAnalyser software (registered by the University of Santiago de Compostela–USC), that 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 the automatic cell detection, with Zakaria A. Al-Tarawneh and Maite Pena-Cristobal et al. OralImmunoAnalyser an accuracy of 79.8% for the cell classification. Although expert’s supervision 16 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 the  biomedical labs. The software, forWindows 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.