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RapidPlan head and neck model: the objectives and possible clinical benefit
A Fogliata1, G Reggiori2, A Stravato2
1Humanitas Research Hospital and Cancer Center, Radiotherapy and Radiosurgery Department, Milan, Rozzano, Italy. Antonella.Fogliata@humanitas.it.
Radiation Oncology (London, England)
|April 29, 2017
Summary
RapidPlan (RP) significantly improved head and neck cancer treatment plans, reducing organ doses and toxicity. The knowledge-based planning model demonstrated stability across different beam geometries and fractionation schemes.
Area of Science:
- Radiation Oncology
- Medical Physics
- Cancer Treatment Planning
Background:
- Evaluating a knowledge-based planning model, RapidPlan (RP), for head and neck cancer (HNC) treatments.
- Assessing RP's potential to enhance clinical plan quality and stability.
- Investigating model performance with varied beam geometry, dose fractionation, and parotid gland management.
Purpose of the Study:
- To evaluate the efficacy of a knowledge-based planning model (RapidPlan) for head and neck cancer.
- To determine if RapidPlan can improve the quality of clinical treatment plans.
- To assess the stability of the RapidPlan model under varying treatment conditions.
Main Methods:
- Trained RapidPlan models using dosimetric and geometric data from 83 HNC patients.
- Utilized volumetric modulated arc therapy (VMAT) for target doses of 69.96 Gy and 54.45 Gy in 33 fractions.
- Validated models on 20 HNC patients, comparing RapidPlan-generated plans with clinical plans and assessing variations in beam geometry and fractionation.
Main Results:
- RapidPlan significantly improved plan quality, reducing mean parotid, oral cavity, and laryngeal doses by 2 Gy, 5 Gy, and 10 Gy, respectively.
- A simpler beam geometry slightly decreased plan quality but maintained significant improvement over clinical plans.
- Normal Tissue Complication Probability (NTCP) evaluations suggested a potential 7% reduction in toxicity profile with RapidPlan.
Conclusions:
- The RapidPlan model for HNC demonstrated enhanced plan quality and planning stability regarding beam geometry and fractionation.
- Careful selection of optimization objectives is crucial for effectively managing trade-offs in the planning model.
