Program Information
Innovation in Radiation Therapy Planning I: Knowledge Guided Treatment Planning
Q Wu1*, L Olsen2*, (1) Duke University Medical Center, Durham, NC, (2)
Presentations
WE-A-BRD-1 Wednesday 7:30AM - 8:25AM Room: Ballroom DIntensity modulated radiation therapy (IMRT) and Volumetric Modulated Arc Therapy (VMAT) offer the capability of normal tissues and organs sparing. However, the exact amount of sparing is often unknown until the plan is complete. This lack of prior guidance has led to the iterative, trial-and-error approach in current planning practice. Even with this effort the search for patient-specific optimal organ sparing is still strongly influenced by planner’s experience. While experience generally helps in maximizing the dosimetric advantages of IMRT/VMAT, there have been several reports showing unnecessarily high degree of plan quality variability at individual institutions and amongst different institutions, even with a large amount of experience and the best available tools. Further, when physician and physicist evaluate a plan, the dosimetric quality of the plan is often compared with a standard protocol that ignores individual patient anatomy and tumor characteristic variations.
In recent years, developments of knowledge models for clinical IMRT/VMAT planning guidance have shown promising clinical potentials. These knowledge models extract past expert clinical experience into mathematical models that predict dose sparing references at patient-specific level. For physicians and planners, these references provide objective values that reflect best achievable dosimetric constraints. For quality assurance, applying patient-specific dosimetry requirements will enable more quantitative and objective assessment of protocol compliance for complex IMRT planning.
Learning Objectives:
1. Modeling and representation of knowledge for knowledge-guided treatment planning.
2. Demonstrations of knowledge-guided treatment planning with a few clinical caanatomical sites.
3. Validation and evaluation of knowledge models for cost and quality effective standardization of plan optimization.
Handouts
- 90-25530-334462-103358.pdf (Q Wu)
- 90-25531-334462-105762.pdf (L Olsen)
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