Image and isocentre management in the paperless age: an automated decision making model

Purpose: The introduction of sophisticated imaging and image analysis tools into daily radiotherapy has made it feasible to undertake image guided radiation therapy (IGRT) on a daily basis. The aim of this paper is to outline that the introduction of a paperless automated decision making model to assess systematic trends in field placement can enhance the efficiency of a treating radiotherapy team. Methods: Automated custom reports were written using Infomaker (Sybase, Dublin, California, USA) to integrate with the ARIA (Varian, Palo Alto, California, USA) patient information system. This allowed automated systematic trend identification in treatment field set-up. The efficiency and accuracy of an automated approach was then compared to manual field placement analysis and a statistical model (Newcastle model). Results: The automated decision making model has been shown to reduce the amount of time taken to analyse images and systematic trend analysis, when compared to manual methods, significantly (P less than 0.001). In addition to the enhanced efficiency there is no trade off in accuracy with the automated decision making model. Discussion: An automated approach to trend analysis allows the treating radiotherapy team to manage field placement in a highly efficient manner, which is paramount in the era of increased image data. A paperless approach to image analysis and field placement trend analysis places the responsibility of accurate field placement on the radiation therapist and represents a vital link in the management of an IGRT protocol. Conclusion: In the era of IGRT with increased imaging data, efficient methods must be found to analyse and manage systematic trends. An automated decision making model represents an increase in efficiency with no trade off in accuracy.