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Published on: February 6, 2019
Coverage optimized planning: probabilistic treatment planning based on dose coverage histogram criteria
1Department of Radiation Oncology, Virginia Commonwealth University, P.O. Box 980058, Richmond, Virginia 23298, USA. jgordon@mcvh-vcu.edu
Medical Physics
|March 17, 2010
Summary
Coverage Optimized Planning (COP) improves radiation therapy by using dose coverage histogram (DCH) criteria for better target coverage. This probabilistic approach optimizes treatment plans by considering geometric uncertainties, outperforming traditional methods.
Area of Science:
- Radiation Oncology
- Medical Physics
- Radiotherapy Planning
Background:
- Conventional radiotherapy planning relies on static dose distributions and planning target volumes (PTVs).
- Geometric uncertainties, such as patient setup errors, introduce variability in the delivered dose (Dv).
- Dose Volume Histograms (DVHs) traditionally assess dose-volume relationships, but do not inherently account for uncertainties.
Purpose of the Study:
- To introduce a probabilistic treatment planning framework, Coverage Optimized Planning (COP), utilizing dose coverage histogram (DCH) criteria.
- To implement and evaluate COP within the PINNACLE treatment planning system.
- To compare COP-generated plans against traditional PTV-based plans for prostate cancer anatomies.
Main Methods:
- Developed a COP framework based on DCH criteria, which plots coverage probability (Q) versus dose (D).
- Implemented COP in the PINNACLE system, replacing PTVs and planning organ at risk volumes with clinical target volumes (CTVs) and organs at risk (OARs).
- Optimized plans using DCH criteria for CTV minimum dose and conventional DVH criteria for other structures, comparing them to PTV-based plans.
Main Results:
- COP plans demonstrated improved target coverage compared to PTV-based plans across 28 prostate anatomies.
- COP effectively exploited 'slack' in OAR doses (doses below optimization limits) to enhance target coverage.
- COP plans allowed for wider dosimetric margins around the CTV without exceeding OAR dose constraints.
Conclusions:
- The Coverage Optimized Planning (COP) framework offers a promising approach to enhance target coverage in radiotherapy by incorporating probabilistic dose assessments.
- COP's ability to leverage OAR dose variability suggests potential for improved treatment outcomes.
- Further research is needed to fully elucidate the clinical benefits of COP, particularly regarding tumor control and normal tissue complication probabilities.
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