Screening for Oral Cancer Using Brush Biopsies and DNA Image Cytometry - A Review
Pranjali Verma 1, Shikha Kumari Rajak 2
Journal of Angiotherapy 7(2) 1-6 https://doi.org/10.25163/angiotherapy.729410
Submitted: 15 November 2023 Revised: 16 December 2023 Published: 21 December 2023
Abstract
For the prompt cytologic diagnosis of oral cancer, non-invasive brush biopsies play a crucial role. Suspicious lesions in patients can be confirmed for malignancy using Deoxyribose Nucleic Acid Image Cytometry (DNAIC), offering a comprehensive diagnostic approach. The enhanced brush biopsy collects diagnostic material across different layers of the damaged epithelium, providing a non-invasive screening method. Despite the limitation of acquiring cells mainly from the superficial and intermediate layers of oral mucosa, DNAIC-DCNN utilizes Deep Convolutional Neural Network (DCNN) for widespread oral cancer detection. Semantic division is performed through the bottom branches, allowing for targeted medication to modify cancer cell features and inhibit proliferation. Targeted drugs, such as Cetuximab, can be used alone or in combination with chemotherapy and radiation treatment for specific patients with oral cancer. The non-invasive and accurate diagnostic capability of DNAIC in conjunction with cytology has demonstrated high precision and accuracy in identifying oral malignant squamous cell transition within epithelial tissues.
Keywords: Deoxyribose Nucleic Acid Image Cytometry, Deep Convolutional Neural Network, Brush Biopsies, Oral Cancer.
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Pranjali Verma pioneered the application of non-invasive brush biopsies and Deoxyribose Nucleic Acid Image Cytometry (DNAIC) for oral cancer diagnosis, enhancing diagnostic precision.
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Shikha Kumari Rajak focused on the integration of Deep Convolutional Neural Network (DCNN) in oral cancer detection, proposing targeted medications like Cetuximab for effective treatment strategies.
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