MENU

Click here to

×

Are you sure ?

Yes, do it No, cancel

Decreasing Head and Neck Treatment Planning Time Using Automation

A Ward1*, S Petro2, E Gittings3, S Hedrick4, (1) Provision CARES, Knoxville, TN, (2) Provision Center for Proton Therapy, Knoxville, TN, (3) ,,,(4) Provision Center for Proton Therapy, Knoxville, TN

Presentations

(Sunday, 7/12/2020)   [Eastern Time (GMT-4)]

Room: AAPM ePoster Library

Background: Head and Neck (H&N) disease sites are some of the most time-consuming proton treatment planning sites. The proximity of the organs at risk (OARs) increase the complexity of the plan, and the large calculation size causes each optimization to take longer to run. Multiple studies have demonstrated that timely radiotherapy initiation is important for optimal survival outcomes for H&N cancers. Automating proton treatment planning makes the H&N planning process more time efficient, allowing for the patient to start sooner, while also maintaining if not improving the plan quality.

Methods: Using RayStation v6 with Monte Carlo plan optimization and dose calculation, treatment plans were developed using automation. A script was developed to set up the H&N plans creating four beams. Avoidance structures are created in order to keep the posterior beams from treating through the shoulders, and the anterior beams from treating through the oral cavity and teeth. Equivalent Uniform Dose objectives are created for OARs with volumetric concerns by determining estimated average doses to these structures. Plan optimization and robustness settings are automatically generated. Scripting is also used to create a mock composite plan in order to let the physician visualize a rough estimate of the full treatment including the boost phases.

Results: Using the script removes multiple initial errors a dosimetrist could encounter with planning. It was found that with this script we can decrease our treatment planning time overall as well as increase the robustness of the plans. By increasing the robustness, we can make the plans more stable and less likely to need to be adapted.

Conclusion: Overall, based on patient tracking for the last year since adding the automation we can save the patient one to five days from the start of planning to first day of treatment while maintaining an optimal plan.

Download ePoster [PDF]

Keywords

Not Applicable / None Entered.

Taxonomy

Not Applicable / None Entered.

Contact Email