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Proceedings Paper

An imaging informatics-based system utilizing DICOM objects for treating pain in spinal cord injury patients utilizing proton beam radiotherapy
Author(s): Sneha K. Verma; Brent J. Liu; Sophia Chun; Daila S. Gridley
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Paper Abstract

Many US combat personnel have sustained nervous tissue trauma during service, which often causes Neuropathic pain as a side effect and is difficult to manage. However in select patients, synapse lesioning can provide significant pain control. Our goal is to determine the effectiveness of using Proton Beam radiotherapy for treating spinal cord injury (SCI) related neuropathic pain as an alternative to invasive surgical lesioning. The project is a joint collaboration of USC, Spinal Cord Institute VA Healthcare System, Long Beach, and Loma Linda University. This is first system of its kind that supports integration and standardization of imaging informatics data in DICOM format; clinical evaluation forms outcomes data and treatment planning data from the Treatment planning station (TPS) utilized to administer the proton therapy in DICOM-RT format. It also supports evaluation of SCI subjects for recruitment into the clinical study, which includes the development, and integration of digital forms and tools for automatic evaluation and classification of SCI pain. Last year, we presented the concept for the patient recruitment module based on the principle of Bayesian decision theory. This year we are presenting the fully developed patient recruitment module and its integration to other modules. In addition, the DICOM module for integrating DICOM and DICOM-RT-ION data is also developed and integrated. This allows researchers to upload animal/patient study data into the system. The patient recruitment module has been tested using 25 retrospective patient data and DICOM data module is tested using 5 sets of animal data.

Paper Details

Date Published: 19 March 2014
PDF: 9 pages
Proc. SPIE 9039, Medical Imaging 2014: PACS and Imaging Informatics: Next Generation and Innovations, 90390W (19 March 2014); doi: 10.1117/12.2044433
Show Author Affiliations
Sneha K. Verma, The Univ. of Southern California (United States)
Brent J. Liu, The Univ. of Southern California (United States)
Sophia Chun, VA Long Beach Healthcare System (United States)
Daila S. Gridley, Loma Linda Univ. (United States)

Published in SPIE Proceedings Vol. 9039:
Medical Imaging 2014: PACS and Imaging Informatics: Next Generation and Innovations
Maria Y. Law; Tessa S. Cook, Editor(s)

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