Non-Invasive High-Resolution Imaging in Oral Pathology: The Evolving Role of OCT and Mucoscopy in Inflammatory Lesion Differentiation

Introduction: The diagnosis and management of oral mucosal lesions, particularly Oral Lichen Planus (OLP), are transitioning toward non-invasive, high-resolution imaging to overcome the limitations of traditional biopsy. Optical Coherence Tomography (OCT) and mucoscopy have emerged as pivotal tools, offering real-time visualization of tissue microstructures.

Purpose: This review aims to evaluate the technical capabilities and clinical utility of OCT and mucoscopy in oral pathology. The study specifically examines their efficacy in differentiating inflammatory lesions, detecting early malignant transformations, and the burgeoning role of artificial intelligence (AI)—including Convolutional Neural Networks and Vision Transformers—in automating image interpretation.

Methodology: A comprehensive literature analysis was conducted to synthesize current evidence on surface and subsurface imaging characteristics, diagnostic accuracy, and the integration of machine learning algorithms to reduce inter-observer variability.

Results: Findings demonstrate that OCT excels in providing cross-sectional insights into epithelial thickness and basement membrane integrity, while mucoscopy offers superior visualization of surface morphological patterns, such as Wickham striae and vascular configurations. The integration of AI significantly enhances the speed and objectivity of these assessments, bridging the gap between clinical observation and histopathology.

Conclusion: The combined application of OCT and mucoscopy represents a paradigm shift in oral diagnostics, offering a synergistic approach to tissue analysis. While histopathology remains the gold standard, these non-invasive modalities improve diagnostic precision, facilitate targeted biopsies, and enable longitudinal monitoring. Future advancements in device portability and AI software integration are expected to solidify these technologies as essential components of routine clinical practice and personalized patient management.