A treatment plan captures a single moment in time and fails to account for changes in anatomy over the course of treatment. Changes in weight or variations in internal anatomy, for example, can result in displacement of the target volume and OAR’s relative to the planned dose cloud. The process of adapting a plan can be labor intensive and time consuming for both physicians and staff. Artificial intelligence (AI) has the potential to improve the accuracy, precision, efficiency, and overall quality of radiation therapy for patients by automating adaptive radiotherapy workflows such as target segmentation, treatment planning and, in some cases, radiotherapy delivery. Vendors will present their AI adaptive solutions and describe how their products can improve the workflow and empower the clinician and staff to make informed decisions related to patient cancer treatments.
Learning Objectives:
1. Review the rationale behind adaptive planning.
2. Explore the different means of adapting a plan including off-line, on-line, and real-time adaptive planning.
3. Explain how AI can help streamline the adaptive treatment process.
Treatment Planning, Image-guided Therapy, Targeted Radiotherapy