A knowledge-based imaging informatics approach for managing proton beam therapy of cancer patients.
The need for a unified patient-oriented information system to handle complex proton therapy (PT) imaging and informatics data during the course of patient treatment is becoming steadily apparent due to the ever increasing demands for better diagnostic treatment planning and more accurate information. Currently, this information is scattered throughout each of the different treatment and information systems in the oncology department. Furthermore, the lack of organization with standardized methods makes it difficult and time-consuming to navigate through the maze of data, resulting in challenges during patient treatment planning. We present a methodology to develop this electronic patient record (ePR) system based on DICOM standards and perform knowledge-based medical imaging informatics research on specific clinical scenarios where patients are treated with PT. Treatment planning is similar in workflow to traditional radiation therapy (RT) methods such as intensity-modulated radiation therapy (IMRT), which utilizes a priori knowledge to drive the treatment plan in an inverse manner. In March 2006, two new RT objects were drafted in a DICOM-RT Supplement 102 specifically for ion therapy, which includes PT. The standardization of DICOM-RT-ION objects and the development of a knowledge base as well as decision-support tools that can be add-on features to the ePR DICOM-RT system were researched. This methodology can be used to extend to PT and the development of future clinical decision-making scenarios during the course of the patient's treatment that utilize "inverse treatment planning." We present the initial steps of this imaging and informatics methodology for PT and lay the foundation for development of future decision-support tools tailored to cancer patients treated with PT. By integrating decision-support knowledge and tools designed to assist in the decision-making process, a new and improved "knowledge-enhanced treatment planning" approach can be realized.
Liu
Brent J
BJ
Image Processing & Informatics Laboratory, Department of Radiology, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90292, USA. brentliu@usc.edu
D001921:Brain / Q000000981:diagnostic imaging; D019295:Computational Biology; D004601:Elementary Particles / Q000627:therapeutic use*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D019359:Knowledge; D008962:Models, Theoretical; D009369:Neoplasms / Q000532:radiotherapy*; D010347:Patient Care Planning; D019047:Phantoms, Imaging; D061766:Proton Therapy; D011877:Radionuclide Imaging; D011522:Protons
D011522:Protons