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article · Clinical and Translational Discovery

Exosomics integrates digital imaging for head and neck cancer diagnosis

Abstract

Abstract Cancers that can manifest in the oral cavity, nasal cavity, larynx, pharynx, sinuses, and other head and neck areas are collectively called “head and neck cancers” (HNC). HNC can be broadly classified into five types: salivary gland; oral and oropharyngeal; nasal cavity and paranasal sinus; nasopharyngeal, and laryngeal and hypopharyngeal cancers. HNC accounts for one million new diagnoses annually, making it the seventh most common form of the disease globally. Among all HNCs, 90% are head and neck squamous cell carcinoma (HNSCC) which is highly heterogenous, relapsing, and metastatic with poor survival. Despite the availability of new treatments, the five‐year survival rate for HNSCC patients has been reported to be approximately 50%. An early diagnosis may increase the disease management and outcomes, but it is challenging to detect smaller‐sized lesions and differentiate malignant and non‐malignant lesions with the available tools. Current circumstances demand an improvement in existing diagnostic strategies and the advent of novel diagnostic tools.

Research topics

  • Extracellular vesicles in disease
  • Radiomics and Machine Learning in Medical Imaging
  • Cancer-related molecular mechanisms research

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DOI: 10.1002/ctd2.307

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