Optimizing Radiation Therapy Planning: A Hybrid Approach Integrating Physician Preferences and Automated Planning Systems.

This study evaluates the enhancement of planning automation in radiation oncology through the integration of physician-specific preferences for organ at risk (OAR) prioritization into an automated planning framework. By combining physician-defined OAR dose goals with multi-criterial driven automated treatment planning, the objective is to refine plan quality and physician satisfaction, ensuring patient-specific considerations are forefront. The study introduces an advanced automation solution that incorporates a prescription device (HRO) to input physician prescription and OAR preferences, connected to an existing planning automation engine utilizing a treatment planning software through API integration. Focusing on head and neck cancer plans, the method involves analyzing the automated planning system's efficacy in optimizing dose distribution in line with physician-set OAR priorities. The study evaluated plans in a network of 40 treatment centers, processing over 20,000 automated treatment plans annually. The system's performance was evaluated based on compliance to physician-defined OAR dose goals, planning efficiency, and the percentage of treatment plans that are approved for treatment without manual user intervention. The analysis revealed that the system successfully influenced the treatment planning system to adjust dose distribution according to physician-defined OAR priorities, with physicians able to layer organs at risk to define prioritization effectively. The system's integration with the prescription device demonstrated a notable improvement in plan quality with 62% of plans showing a reduced Parotid mean dose without compromising adjacent structures. Target coverage improved on 29% of cases while maximum dose decreased on 36% of cases while maintaining greater Parotid sparing. The approach provided physicians with the ability to influence the outcomes of complex dose optimization within a TPS without intervention, reflecting the complex interplay of clinical objectives and individual patient anatomy. The integration of physician preferences into automated planning systems represents a significant advancement in personalized radiation therapy planning. By enabling physicians to dictate OAR priorities directly, the study demonstrates improved alignment of automated plans with individual patient anatomy and clinical goals. This hybrid approach not only enhances plan quality and efficiency but also fosters greater physician satisfaction and confidence in automated systems. The findings advocate for greater provider wellness and more sustainable operating models for physicians through more patient centric automated solutions. [ABSTRACT FROM AUTHOR]