Clinical application of a template-guided automated planning routine.

PURPOSE: Determine the dosimetric quality and the planning time reduction when utilizing a template-based automated planning application. METHODS: A software application integrated through the treatment planning system application programing interface, QuickPlan, was developed to facilitate automated planning using configurable templates for contouring, knowledge-based planning structure matching, field design, and algorithm settings. Validations are performed at various levels of the planning procedure and assist in the evaluation of readiness of the CT image, structure set, and plan layout for automated planning. QuickPlan is evaluated dosimetrically against 22 hippocampal-avoidance whole brain radiotherapy patients. The required times to treatment plan generation are compared for the validations set as well as 10 prospective patients whose plans have been automated by QuickPlan. RESULTS: The generations of 22 automated treatment plans are compared against a manual replanning using an identical process, resulting in dosimetric differences of minor clinical significance. The target dose to 2% volume and homogeneity index result in significantly decreased values for automated plans, whereas other dose metric evaluations are nonsignificant. The time to generate the treatment plans is reduced for all automated plans with a median difference of 9' 50″ ± 4' 33″. CONCLUSIONS: Template-based automated planning allows for reduced treatment planning time with consistent optimization structure creation, treatment field creation, plan optimization, and dose calculation with similar dosimetric quality. This process has potential expansion to numerous disease sites.

Technical Report: Development and Implementation of an Open Source Template Interpretation Class Library for Automated Treatment Planning.

PURPOSE: Widespread implementation of automated treatment planning in radiation therapy remains elusive owing to variability in clinic and physician preferences, making it difficult to ensure consistent plan parameters. We have developed an open-source class library with the aim to improve efficiency and consistency for automated treatment planning in radiation therapy. METHODS AND MATERIALS: An open-source class library has been developed that interprets clinical templates within a commercial treatment planning system into a treatment plan for automated planning. This code was leveraged for the automated planning of 39 patients and retrospectively compared with the 78 clinically approved manual plans. RESULTS: From the initial 39 patients, 74 of 78 plans were successfully generated without manual intervention. The target dose was more homogeneous for automated plans, with an average homogeneity index of 3.30 for manual plans versus 3.11 for automated plans (P = .107). The generalized equivalent uniform dose (gEUD) was decreased in the femurs and rectum for automated plans, with a mean gEUD of 3746 cGy versus 3338 cGy (P ≤ 0.001) and 5761 cGy versus 5634 cGy (P ≤ 0.001) for the femurs and rectum, respectively. Dose metrics for the bladder and rectum (V6500 cGy and V4000 cGy) showed recognizable but insignificant improvements. All automated plans delivered for quality assurance passed a gamma analysis (>95%), with an average composite pass rate of 99.3% for pelvis plans and 98.8% for prostate plans. Deliverability parameters such as total monitor units and aperture complexity indicated deliverable plans. CONCLUSIONS: Prostate cancer and pelvic node radiation therapy can be automated using volumetric modulated arc therapy planning and clinical templates based on a standardized clinical workflow. The class library developed in this study conveniently interfaced between the plan template and the treatment planning system to automatically generate high-quality plans on customizable templates.