Designing and Development of Iran CDX Software Program for the Diagnosis of Malignancies and Dysplasia in Oral Brush Cytology Samples and Evaluation of Its Performance

Document Type : Original Articles

Authors

1 Postgraduate, Department of Oral Medicine, School of Dentistry, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.

2 Department of Oral Medicine, School of Dentistry, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.

3 Department of Pathology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.

4 Postgraduate, Department of Materials, Isfahan University of Technology, Isfahan, Iran.

5 Department of Electrical and Computer, Isfahan University of Technology, Isfahan, Iran.

10.48305/v0i0.1394

Abstract

Introduction: Due to high mortality rate and prevalence of cancer, early detection is vital and important. Precancerous oral lesions have the potential to lead to SCC and therefore they should be carefully assessed. Brush cytology is a simple method, which obtains a sample from the epithelium. Computer analyses have an important role in interpretation of pathologic samples.
Materials & Methods: An engineering team designed the software with neural networks, and the algorithm was trained with samples obtained from patients. In the second stage, brush cytology samples were collected from 20 patients with cancer and 20 healthy individuals. From each slide 50 digital images was captured with a camera under a microscope. The images were separately entered into the software program. The results were recorded as healthy and unhealthy. Statistical analyses were performed using Excel program.
Results: The software had 91 errors in a total of 2000 digital images. Comparison of the results provided by the software program and those of the scalpel biopsy of the patients with Fisher's exact test did not reveal any significant differences (p value = 0.004).
Conclusion: Based on the results of this study, the designed software exhibited high specificity and sensitivity.
Key words: Brush cytology, Neural networks, SCC.

References

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Journal of Isfahan Dental School
Volume 14, Issue 4 - Serial Number 4
October 2018
Pages 348-358

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