Hyperspectral imaging in oral oncology: a scoping review

Introduction: Oral cancer accounts for 177,000 deaths annually. Despite advances in surgical techniques and adjuvant therapies, the five-year survival rate for oral malignancies has shown limited improvement. Hyperspectral imaging (HSI) is a new non-invasive optical modality that extends medical imaging beyond the visible spectrum. This scoping review aims to map the extent, nature, and methodological characteristics of the existing literature on the application of HSI for the detection and characterization of oral cancer. It explores the clinical applications of HSI in oral oncology, outlines the technical and analytical approaches used, and evaluates its diagnostic performance and translational readiness in clinical practice. Methods: This scoping review used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines and followed the Population-Concept-Context(PCC) framework. A comprehensive search strategy was formulated to search across PubMed, ScienceDirect, Nature, LILACS, and Cochrane Library, and citation searching. Search was conducted by two independent reviewers using predefined inclusion and exclusion criteria. Microsoft Excel was used for data extraction. Descriptive synthesis was used to map the extent and nature of existing evidence, and narrative synthesis was used to identify patterns and methodological characteristics. Most studies primarily focused on oral squamous cell carcinoma. All studies used reflectance based HSI with macroscopic and microscopic systems across visible-near-infrared ranges. Machine and deep learning methods were used. Clinical applications of HSI included diagnosis, margin assessment, and segmentation. Studies showed strong diagnostic performance with high sensitivity and specificity and area under the curve values. Conclusion: HSI is a new emerging technology with applications in oral oncology. It provides a non-contact, objective and rapid alternative for margin assessment. With improved standardization, robust analytical models and clinical validation, it has the potential to be integrated into routine oral cancer management. Systematic Review Registration: https://doi.org/10.17605/OSF.IO/JQEGU.