Author: Jon Hansen 👨🔬
Affiliation: Washington University in St Louis 🌍
Purpose: Commercially available auto-segmentation software was utilized to generate institution-specific optimization structures for spine stereotactic body radiation therapy (SBRT). Implementation of the custom script promoted efficiency and consistency with clinical treatment planning.
Methods: Radformation AutoContour software was used in this work. Spine SBRT contours included the Clinical Target Volume (CTV), Planning Target Volume (PTV), Spinal Cord nerve bundle, and/or Cauda Equina nerve bundle as defined by the physician. Our institutional planning practice requires the creation of optimization targets with 4-7 mm offset from true nerve bundle seen on fused diagnostic imaging. For clinical cases without true nerve bundle defined, plan setup conservatively uses a 2-5 mm offset from the Spinal Canal. RegEx-based programming was used within AutoContour software to search for and use MD-defined Spinal Cord and Cauda Equina contours. For cases where nerve bundle could not be defined by the physician, the template was configured to instead automatically use nearby Spinal Canal to create optimization target volumes. The custom template also subtracted other organs at risk (OARs) with 2-5 mm offset following clinical practice.
Results: Through the custom script, our institutional planning approach for creating Spine SBRT optimization targets could be applied without relying on successive user inputs. Since implementation, the frequency of replans necessitated by incorrect contour definitions has decreased from 10/35 cases in the proceeding 6 months to 0/15 cases post-implementation. In particular, the template has proven effective at defining optimization volumes automatically for lumbar spine at the interface of Spinal Cord and Cauda Equina. Median dosimetrist planning time was found to be 10 working hours for Spine SBRT cases using the custom script.
Conclusion: This work was performed in accordance with institutional effort updating treatment planning workflows using risk-based analysis. Generating optimization structures with the custom auto-segmentation script has improved planning efficiency and consistency.