Purpose: To develop and deploy an interface to support automatic treatment planning which predicts achievable dose levels for organs at risk (OARs) from patients with similar or more complicated anatomies queried from a database. This interface will provide an easy to use method of selecting the best known achievable dose values for a given patient, and use them to automate the planning process. Methods: An overlap volume histogram (OVH) describes the distance a target structure can be expanded with the volume of the compared overlap structure. An OVH is generated for each target/critical structure pair and stored in a database with dose‐volume histograms (DVHs) for each patient. For all patients, structures are consistently named by mapping ROI names to a set of common names. For a new patient, the patient database is queried for the lowest achievable dose for each OAR from patients in the database with the same or lower overlap distance. The plan parameters and generated objectives are then automatically loaded into treatment planning system for optimization. The final clinical plan from each patient is added to the database to improve the results of future queries. Results: The system has been accepted by the dosimetrists for clinical use. Automatically generated plans required less dosimetrist interaction to achieve similar coverage to manually generated plans while OAR doses were reduced or no worse than the manually generated plans. Conclusion: Automatic planning tools can aid dosimetrists in quickly generating plans which maintain target coverage and produce comparable or reduced dose to OARs. Our interface has simplified the process enabling the broader use of the system across our dosimetry staff. Philips stock ownership Philips Sponsored Research Elekta Sponsored Research Elekta Patent License Accuray (Tomotherapy) Patent License.
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging