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Auto-VMAT-TBI: An Automatic Treatment Planning Software Platform for Volumetric Modulated Arc Therapy-Enabled Total Body Irradiation

J Tan*, D Parsons , P Lee , X Gu , UT Southwestern Medical Center, Dallas, TX

Presentations

(Tuesday, 7/16/2019) 1:45 PM - 3:45 PM

Room: Stars at Night Ballroom 1

Purpose: VMAT-TBI has replaced conventional extended-distance TBI in our institution thanks to its high dosimetry accuracy and patient satisfaction. VMAT-TBI planning, including CT image concatenation, contouring, isocenter placement, VMAT and field-in-field combined plan optimization, is a laborious manual process. This work aims to develop an automatic VMAT-TBI treatment planning software platform, namely auto-VMAT-TBI, to generate high-quality plans with minimal human intervention.

Methods: The auto-VMAT-TBI platform consists of two components, plan preparation and plan optimization. The plan preparation software is developed in Python to enable automatic 1) concatenating head-first supine (HFS) and feet-first supine (FFS) simulation CT images using rigid image registration; 2) segmenting VMAT-TBI body frame, patient body, and lungs using HU thresholding and creating PTVs; 3) placing beams’ isocenters using preset radio-opaque BBs and empirical beam overlapping; 4) generating one VMAT and 1-3 AP-PA plan templates, and one structure DICOM RT. Plan optimization software is developed using Eclipse Scripting API, which automatically optimizes VMAT and field-in-field plans generated in plan preparation. During optimization, the program automatically delineates gaps in target coverage, creates objectives, and assigns priorities to improve coverage and dose homogeneity.

Results: The auto-VMAT-TBI platform was evaluated on eight TBI patients using a 2Gy-single-fraction treatment regime in respect of plan quality and efficiency. The generated plan quality satisfies all dosimetric requirements. Depending on the patient height and plan complexity, it takes ~2-6 hours to complete a VMAT-TBI plan with 10 minutes of manual operation, which is far more efficient than original 2-3 days manual VMAT-TBI planning.

Conclusion: We have developed an auto-VMAT-TBI platform that can efficiently generate satisfactory 2Gy-single-fraction VMAT-TBI plans with minimal human intervention. We will further extend the platform for 12Gy-full-dose regime VMAT-TBI planning by incorporating auto-segmentation and dose optimization of critical organs, such as lungs, spinal cord, and oral cavity.

Keywords

TBI, Treatment Planning, Software

Taxonomy

TH- External beam- photons: General (most aspects)

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