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A feasibility study: Selection of a personalized radiotherapy fractionation schedule using spatiotemporal
Minsun Kim1, Robert D Stewart1, Mark H Phillips2
1Department of Radiation Oncology, University of Washington, Seattle, Washington 98195-6043.
Medical Physics
|November 2, 2015
Summary
Spatiotemporal optimization significantly increases tumor biologically equivalent dose (BED) for certain patients, potentially improving tumor control. This advanced method also allows for shorter treatment courses, enhancing patient convenience and resource allocation in radiation therapy.
Area of Science:
- Radiation Oncology
- Medical Physics
- Biomedical Engineering
Background:
- Conventional radiation therapy planning optimizes spatial dose distribution.
- Fractionation schedules are often standardized, not personalized to tumor biology or anatomy.
- Maximizing tumor biologically equivalent dose (BED) is crucial for effective tumor control.
Purpose of the Study:
- To investigate spatiotemporal optimization for selecting patient-specific fractionation schedules.
- To maximize tumor BED while adhering to organ-at-risk (OAR) dose constraints.
- To assess the impact on tumor control and treatment course duration.
Main Methods:
- Applied spatiotemporal optimization to lung phantom cases.
- Optimized the number of fractions (N) to maximize 3D tumor BED.
- Used linear-quadratic model and patient-specific parameters (α/β, Td, Tk).
- Compared optimized plans to conventional intensity-modulated radiation therapy (IMRT).
Main Results:
- Achieved up to 19-21% higher tumor BED compared to conventional IMRT.
- Tumor equivalent uniform dose (EUD) increased by up to 17%.
- For fast-proliferating tumors (Td < 10 days), BED gains were minimal, but treatment could be shortened.
- Improvements were more pronounced for smaller tumors.
Conclusions:
- Spatiotemporal optimization can significantly improve local tumor control for patients with favorable geometry.
- Equivalent outcomes were observed for less favorable geometries and fast-growing tumors, but with shorter treatment times.
- Personalized optimization enhances patient convenience and clinical resource efficiency.
- Identifies patients suitable for non-conventional fractionation schedules.
