Optimization of stereotactic body radiotherapy treatment planning using a multicriteria optimization algorithm.

Area of Science:

• Radiation Oncology
• Medical Physics
• Cancer Treatment Planning

Background:

• Stereotactic body radiotherapy (SBRT) requires precise dosimetric planning for effective tumor treatment and normal tissue sparing.
• Multicriteria optimization (MCO) offers a method to balance competing objectives in treatment planning.
• Direct machine parameter optimization (DMPO) can further refine plans for improved dose conformity.

Purpose of the Study:

• To evaluate the efficacy of combining multicriteria optimization (MCO) with direct machine parameter optimization (DMPO) for SBRT planning.
• To achieve high-quality, efficient dosimetric plans for various SBRT tumor sites.
• To fine-tune MCO-generated plans using DMPO for enhanced dose gradients.

Main Methods:

• SBRT plans were generated for 18 patients (lung, liver, adrenal cancers) using VMAT technique in RayStation™ TPS.
• Initial plans utilized MCO for efficient, balanced optimization between tumor control and normal tissue sparing.
• MCO plans were further refined using DMPO to improve dose gradients around the planning target volume (PTV).

Main Results:

• The combined MCO+DMPO approach yielded clinically optimal SBRT plans within approximately one hour of computation time.
• PTV coverage and organ-at-risk sparing were comparable between MCO and MCO+DMPO plans (p>0.05).
• MCO+DMPO significantly improved conformity indexes (CI100, CI50) compared to MCO alone (p<0.05).

Conclusions:

• MCO enables efficient convergence to optimal SBRT solutions.
• The MCO+DMPO combination enhances dose gradients, especially beneficial for lung SBRT.
• This integrated approach ensures high-quality, deliverable SBRT plans meeting clinical constraints.