Utilizing Artificial Intelligence for Head and Neck Cancer Outcomes Prediction From Imaging
Tricia Chinnery1, Andrew Arifin2, Keng Yeow Tay3
1Department of Medical Biophysics, 6221Western University, London, Ontario, Canada.
Summary
Artificial intelligence (AI) models using radiomics show promise for predicting head and neck cancer outcomes and treatment toxicity. Further validation and prospective trials are needed for clinical use.
Area of Science:
- Oncology
- Medical Imaging
- Artificial Intelligence
Background:
- Artificial intelligence (AI) models are increasingly utilized in predictive medicine.
- Medical imaging and radiomics are crucial components of AI-driven predictive models.
- Head and neck cancer research is a key area for AI applications.
Purpose of the Study:
- To review recent advancements in radiomics for AI in head and neck cancer.
- To summarize the development of AI models for predicting oncologic outcomes, treatment toxicity, and pathological findings.
- To identify the current limitations and future directions for clinical translation.
Main Methods:
- Review of recent literature on AI and radiomics in head and neck cancer.
- Analysis of studies focusing on predictive models for various cancer-related outcomes.
- Assessment of the current state of validation and clinical translation.
Main Results:
- AI-based radiomics models have been developed for predicting oncologic outcomes, treatment toxicity, and pathological findings in head and neck cancer.
- Exploratory studies demonstrate promising results in utilizing radiomics for AI applications.
- A significant gap exists in validation studies demonstrating consistency, reproducibility, and prognostic impact.
Conclusions:
- Radiomics holds significant potential for AI in head and neck cancer management.
- Current research is largely exploratory, with a need for robust validation.
- Prospective clinical trials with standardized protocols are essential for integrating these AI models into clinical practice.
