Current Insights into Oral Cancer Diagnostics.
Yee-Fun SuYi-Ju ChenFa-Tzu TsaiWan-Chun LiMing-Lun HsuDing-Han WangCheng-Chieh YangPublished in: Diagnostics (Basel, Switzerland) (2021)
Oral cancer is one of the most common head and neck malignancies and has an overall 5-year survival rate that remains below 50%. Oral cancer is generally preceded by oral potentially malignant disorders (OPMDs) but determining the risk of OPMD progressing to cancer remains a difficult task. Several diagnostic technologies have been developed to facilitate the detection of OPMD and oral cancer, and some of these have been translated into regulatory-approved in vitro diagnostic systems or medical devices. Furthermore, the rapid development of novel biomarkers, electronic systems, and artificial intelligence may help to develop a new era where OPMD and oral cancer are detected at an early stage. To date, a visual oral examination remains the routine first-line method of identifying oral lesions; however, this method has certain limitations and as a result, patients are either diagnosed when their cancer reaches a severe stage or a high-risk patient with OPMD is misdiagnosed and left untreated. The purpose of this article is to review the currently available diagnostic methods for oral cancer as well as possible future applications of novel promising technologies to oral cancer diagnosis. This will potentially increase diagnostic options and improve our ability to effectively diagnose and treat oral cancerous-related lesions.
Keyphrases
- artificial intelligence
- early stage
- papillary thyroid
- end stage renal disease
- machine learning
- big data
- deep learning
- chronic kidney disease
- ejection fraction
- newly diagnosed
- loop mediated isothermal amplification
- squamous cell carcinoma
- early onset
- peritoneal dialysis
- radiation therapy
- patient reported outcomes
- sentinel lymph node
- patient reported