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Sep 30
Education

EDU 58 - Auto-Planning in the Wild: Lessons Learned from Clinical Deployment

08:00am - 09:00am ET

MODERATOR(S)

Joseph Harms, PhD - Washington University in St. Louis

session DESCRIPTION

Automated treatment planning has long promised more consistent plan quality and faster turnaround from simulation to treatment, yet published guidance on real-world clinical deployment remains limited. This session brings "Auto-planning in the Wild" to the ASTRO community through practical lessons learned from early adopters implementing automated planning across diverse environments (i.e., single hospitals, multi-satellite health systems, and networked planning models). Speakers representing both clinicians and medical physics will share implementation stories that move beyond controlled benchmarks to day-to-day operations, including required infrastructure, workflow redesign, staffing considerations, QA and governance approaches, and strategies for maintaining clinical safety and consistency at scale. Attendees will learn common barriers and pitfalls (technical integration, change management, edge cases and acceptance criteria) alongside pragmatic solutions that have enabled sustainable deployment. Emphasis will be placed on translating operational data (plan quality uniformity, efficiency gains and reliability) into clear dialogue that communicates radiotherapy's value to clinical teams and institutional stakeholders, supporting broader adoption and advancing patient care.

learning objectives

  1. Describe the infrastructure, governance and workflow redesign required to deploy automated treatment planning safely in routine clinical practice.
  2. Assess auto-planning performance using practical plan quality and safety criteria (e.g., acceptance thresholds, QA checkpoints and monitoring metrics) to guide clinical adoption.
  3. Identify common barriers and failure modes in clinical deployment and determine mitigation strategies, including how to communicate operational results to stakeholders to support sustainable implementation.

Credits

AMA PRA Category 1 Credits: 1.00

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