Planning Automation for Treatment Techniques Comparison and Robustness Analysis: Tangential Intensity Modulated Radiation Therapy and Volumetric Modulated Arc Therapy for Whole Breast Irradiation.

Purpose: This study evaluates the use of the mCycle automated planning system integrated into the Monaco Treatment Planning System for step-and-shoot intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) in whole breast irradiation (WBI). The aim was to assess whether automation can standardize plan quality across a diverse patient cohort and compare dosimetric outcomes and robustness of the 2 techniques against setup errors and anatomical variations.

Methods And Materials: A total of 65 patients with breast cancer who underwent postoperative WBI were selected for the study. Treatment plans were generated using mCycle, which employs multicriteria optimization with no manual intervention. Two automated planning techniques-IMRT and VMAT-were implemented and evaluated based on dosimetric outcomes, physician review, planning time, and plan robustness. The plan deliverability was verified through γ index and point dose measurements.

Results: The mCycle system produced clinically acceptable plans for both IMRT and VMAT across all patient cohorts. VMAT showed superior target coverage (V95% = 97.9%) and better sparing of ipsilateral organs at risks (OARs), whereas IMRT demonstrated enhanced sparing of contralateral OARs and greater robustness to anatomical changes such as breast swelling. Planning times were reduced with VMAT because of complete automation. Plan deliverability was confirmed with high γ passing rates and acceptable point dose deviations.

Conclusions: The use of mCycle in WBI planning successfully standardized plan quality and improved workflow efficiency. VMAT provided superior target coverage and ipsilateral OAR sparing but was more sensitive to anatomical changes. IMRT showed better contralateral OAR sparing and robustness. Both techniques are viable, with advantages depending on clinical scenarios.