Challenges in lung and heart avoidance for postmastectomy breast cancer radiotherapy: Is automated planning the...

Postmastectomy radiotherapy (PMRT) has been shown to improve the overall survival for invasive breast cancer patients. However, it represents a challenging treatment geometry and individualized planning strategies with complex field arrangements are usually adopted to decrease radiotoxicity to heart and lungs. Automated treatment planning has the potential to improve plan quality consistency and planning efficiency. Herein, we describe the application of the Pinnacle³ Autoplanning engine as a valuable technological resource able to allow the treatment of challenging patients theoretically unfit for radiotherapy for major cardiac and pulmonary comorbidities. Treatment was planned for three left-sided chest wall and regional lymph-nodes postmastectomy breast cancer patients. A deep inspiration breath-hold (DIBH) technique was used aiming to reduce the OARs irradiation. Three manually generated plans (hybrid-IMRT (HMRT), hybrid-VMAT (HVMAT) and full VMAT (MP-VMAT) and a fully automated plan created by the Autoplanning engine (AP-VMAT) were optimized in order to ensure a safe radiation therapy to the patients. The plans were evaluated based on planning target volumes (PTVs) coverage, dose homogeneity index (HI), conformity index (CN), dose to organs at risk (OARs) and normal tissue complication probabilities (NTCPs) of pericarditis, long term mortality and pneumonitis. Despite the use of deep moderated breath-hold, all human-driven plans failed to reach the stringent dose objectives for OARs. All plans provided an optimal coverage for chest wall and lymph-nodal area. AP-VMAT delivered the lowest mean dose to the heart (3.4 to 4.9 Gy) and ipsilateral lung (7.5 to 12.5 Gy) reporting the lowest NTCP for pneumonitis (<1%), confirming the only chance to comply the dose objectives. Moreover, AP-VMAT reported a decrease of the integral dose, which was lower by about 4-8% with respect to manual plans. AP-VMAT plan resulted in up to 58% increase of MUs with respect to manual plans, suggesting a more pronounced fluence modulation and plan complexity. A major difference was found for the planning time which was reduced to less than 30 minutes by using the Auto-Planning module. With improved planning quality and efficiency, Auto-planning is an effective tool to enable high-quality plans in challenging postmastectomy breast cancer radiotherapy.