Refining complex re-irradiation dosimetry through feasibility benchmarking and analysis for informed treatment...

Area of Science:

• Radiation Oncology
• Medical Physics
• Radiotherapy Planning

Background:

• Re-irradiation in radiotherapy presents complex challenges, particularly in managing dose overlap and ensuring treatment efficacy.
• Accurate prediction of treatment plan viability is crucial for optimizing outcomes in re-irradiation scenarios.

Purpose of the Study:

• To evaluate PlanIQ's effectiveness in predicting dosimetric planning viability for complex re-irradiation.
• To assess PlanIQ's capability in generating equivalent treatment plans via Pinnacle integration.
• To determine if PlanIQ mitigates pre-optimization uncertainties in dose overlap regions.

Main Methods:

• Retrospective analysis of 20 diverse re-irradiation cases planned with Pinnacle auto-planning and PlanIQ integration.
• Development and application of a consistent planning template across all cases.
• Direct comparison of manual plans versus PlanIQ-generated plans by physicians, recording Organ at Risk (OAR) doses and planning times.

Main Results:

• PlanIQ successfully predicted achievability for all re-irradiation cases.
• PlanIQ-generated plans were consistently equal or superior in quality to manual plans (P=0.05).
• Significant improvements in mean dose to proximal tissues (5.0%, P<0.05) and maximum point doses in cranial/spine cases (up to 10.9%) were observed.
• Planning times were reduced compared to manual planning.

Conclusions:

• PlanIQ provides reliable feasibility feedback, aiding early decision-making in re-irradiation planning.
• The integration of model-based prediction tools like PlanIQ positively impacts the quality of complex re-irradiation treatment plans.
• PlanIQ effectively eliminates trial-and-error in planning, improving efficiency and outcomes.