Advances in Oral Exfoliative Cytology: From Cancer Diagnosis to Systemic Disease Detection.
Shan WangZe ZhengPublished in: Diagnostic cytopathology (2024)
Oral exfoliative cytology has emerged as a valuable tool in the early detection of oral cancer and other systemic diseases. This review comprehensively examines the current applications and recent advancements in oral exfoliative cytology techniques. We analyzed published literature from the past decade, focusing on methodological improvements, diagnostic accuracy, and emerging applications. Key findings include: (1) Enhanced cell collection and preparation methods have significantly improved sample quality and diagnostic reliability. (2) Integration of molecular markers and DNA analysis with traditional cytomorphological assessment has increased diagnostic sensitivity and specificity for oral cancer detection. (3) Novel applications in systemic disease detection, including diabetes and iron overload disorders, demonstrate the expanding utility of this technique. (4) Computer-assisted analysis and deep learning algorithms show promise in improving diagnostic accuracy and efficiency. Despite these advancements, challenges remain in standardization and widespread clinical implementation. This review provides a critical evaluation of oral exfoliative cytology's current status and future potential in oral and systemic disease diagnosis.
Keyphrases
- fine needle aspiration
- deep learning
- high grade
- primary care
- systematic review
- ultrasound guided
- machine learning
- loop mediated isothermal amplification
- cardiovascular disease
- type diabetes
- healthcare
- squamous cell carcinoma
- real time pcr
- stem cells
- label free
- papillary thyroid
- single cell
- insulin resistance
- climate change
- skeletal muscle
- cell therapy
- mass spectrometry
- adipose tissue
- cell free
- single molecule
- glycemic control
- convolutional neural network
- mesenchymal stem cells
- metabolic syndrome
- big data
- quantum dots
- high resolution
- nucleic acid
- human health