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Description
Head and neck squamous cell carcinomas (HNSCCs) originate from the mucosal lining of the upper aerodigestive tract and radiation therapy has become a fundamental component in the standard care for these patients. However, the treatment's unique dynamics can lead to disparities in outcomes and biological responses in both tumor and normal tissues. A significant challenge remains in predicting individual patient responses to radiation, with variability often resulting in under or over-treatment and potentially adverse effects. The absence of reliable biomarkers highlights the need for predictive measures to guide clinical decisions in real-time. The integration of mathematical models in radiation therapy offers a promising solution, with models incorporating a global lambda demonstrating the ability to predict treatment responses beyond initial weeks. These models provide a framework to address patient response variability, potentially improving survival rates and quality of life.
Program Affiliation
Radiation Oncology Summer Experience Program
Publication Date
Summer 8-1-2024
Keywords
Digital Twin, Quantitative Personalized Oncology, Radiation Oncology, Mathematical Modeling in Radiation Oncology
Recommended Citation
Vijayvikram, Rohan; Schlicke, Pirmin; Zahid, Mohammad U.; El-Habashy, Dina M.; Dede, Cem; Fuller, Clifton D.; and Enderling, Heiko, "Math meets the Clinic: Modeling Patient Specific HNSCC Radiation Response Dynamics" (2024). Radiation Oncology Medical Student Program. 5.
https://openworks.mdanderson.org/radonc24/5
