Perspectives in pathomics in head and neck cancer

Area of Science:

• Pathomics leverages artificial intelligence (AI) and digital pathology for advanced cancer diagnostics.
• The field integrates deep learning with Whole Slide Images for enhanced analysis.

Background:

• Pathology is fundamental to cancer care.
• Pathomics is an emerging field poised to transform pathology.
• Digital pathology and AI are rapidly advancing.

Purpose of the Study:

• To provide an overview of pathomics.
• To discuss current and future applications of pathomics.
• To highlight pathomics' relevance in Head and Neck cancer care.

Main Methods:

• Review of current literature on pathomics and AI in digital pathology.
• Analysis of pathomics applications across various cancer types.
• Focus on applications and challenges in Head and Neck cancers.

Main Results:

• AI in pathology, particularly deep learning with Whole Slide Images, is a rapidly growing area.
• Pathomics applications include computer-assisted diagnosis, molecular anomaly prediction, tumor microenvironment analysis, biomarker identification, and prognosis evaluation.
• Studies show promising results in breast, prostate, lung, and Head and Neck cancers.

Conclusions:

• Pathomics is a powerful tool for improving diagnosis and identifying prognostic factors and biomarkers in Head and Neck cancer care.
• Clinical implementation faces challenges including AI decision transparency, digital pathology deployment, and data validation for regulatory approval.
• Pathomics is expected to significantly enhance pathology, including Head and Neck cancer care.