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Efficiency of Auto Crop and Avoidance Structure Tools in Eclipse 15.5

F Zhang2*, (2) Bayhealth Medical Center, Dover, DE

Presentations

(Sunday, 7/14/2019)  

Room: ePoster Forums

Purpose: To investigate efficiency of treatment planning using auto crop and avoidance tools in Eclipse 15.5

Methods: 10 head and neck cancer patient cases are studied. In each case, different doses are prescribed to the overlap PTVs. Previously, PTVs are cropped before optimization to avoid target overlap. One primary and two boost VMAT plans are created to implement the prescription. Now, without target cropping, one VMAT plan is generated using auto crop tool under VMAT optimization PO_15511. One lower objective with volume of 100 percentage is set for each PTV. An upper objective with volume of 0 percentage is added to PTV with highest dose prescription. System searches for target structure overlaps and 5mm internal margin structure is created around higher dose target to allow dose ramp up from lower target dose to higher one. 10 SRS cases were previously planned using avoidance sectors to avoid entrance dose to optical structures. These cases are planned with avoidance structure tool to block both entrance and exit beam under VMAT optimization PO_15511. Fluence pixel is block by moving leaves on top of the pixel.

Results: Doses to different targets and OARs are compared when the highest dose PTV has the same coverage. With auto crop tool, targets have greater minimum and mean dose with decreased dose to OARs. With avoidance tool, the dose to the optical structure is reduced by different percentages. The percentage of dose reduction is more at center of the field than that at the edge of the field.

Conclusion: Auto crop tool facilitates the SIB planning, increases the min dose to PTVs and lowers dose to the OARs. Avoidance structure tool reduces the dose by different percentage which depends on the location of avoidance structures in the fields.

Keywords

Treatment Planning

Taxonomy

TH- External beam- photons: treatment planning/virtual clinical studies

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