Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/40768
Title: A knowledge-based imaging informatics approach to managing patients treated with proton beam therapy
Authors: Liu, B
Huang, HK
Law, YY
Document, J
Gertych, A
Keywords: Imaging informatics
Radiotherapy
Particles
Brain
Cancer
Issue Date: 2007
Publisher: SPIE-International Society for Optical Engineering
Source: Proceedings of SPIE : the International Society for Optical Engineering, 2007, v. 6516, 651616 How to cite?
Journal: Proceedings of SPIE : the International Society for Optical Engineering 
Abstract: Last year we presented work on an imaging informatics approach towards developing quantitative knowledge and tools based on standardized DICOM-RT objects for Image-Guided Radiation Therapy. In this paper, we have extended this methodology to perform knowledge-based medical imaging informatics research on specific clinical scenarios where brain tumor patients are treated with Proton Beam Therapy (PT). PT utilizes energized charged particles, protons, to deliver dose to the target region. Protons are energized to specific velocities which determine where they will deposit maximum energy within the body to destroy cancerous cells. Treatment Planning is similar in workflow to traditional Radiation Therapy 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 Proton Therapy. 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. We have developed a methodology to perform knowledge-based medical imaging informatics research on specific clinical scenarios. This methodology can be used to extend to Proton Therapy and the development of future clinical decision-making scenarios during the course of the patient's treatment that utilize "inverse treatment planning". In this paper, we present the initial steps toward extending this 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.
Description: Medical Imaging 2007 : PACS and Imaging Informatics, San Diego, CA, 19-22 Feb 2007
URI: http://hdl.handle.net/10397/40768
ISSN: 0277-786X
EISSN: 1996-756X
DOI: 10.1117/12.710642
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