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Proceedings Paper

Physiologically gated micro-beam radiation therapy using electronically controlled field emission x-ray source array
Author(s): Pavel Chtcheprov; Michael Hadsell; Laurel Burk; Rachel Ger; Lei Zhang; Hong Yuan; Yueh Z. Lee; Sha Chang; Jianping Lu; Otto Zhou
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Paper Abstract

Micro-beam radiation therapy (MRT) uses parallel planes of high dose narrow (10-100 um in width) radiation beams separated by a fraction of a millimeter to treat cancerous tumors. This experimental therapy method based on synchrotron radiation has been shown to spare normal tissue at up to 1000Gy of entrance dose while still being effective in tumor eradication and extending the lifetime of tumor-bearing small animal models. Motion during the treatment can result in significant movement of micro beam positions resulting in broader beam width and lower peak to valley dose ratio (PVDR), and thus can reduce the effectiveness of the MRT. Recently we have developed the first bench-top image guided MRT system for small animal treatment using a high powered carbon nanotube (CNT) x-ray source array. The CNT field emission x-ray source can be electronically synchronized to an external triggering signal to enable physiologically gated firing of x-ray radiation to minimize motion blurring. Here we report the results of phantom study of respiratory gated MRT. A simulation of mouse breathing was performed using a servo motor. Preliminary results show that without gating the micro beam full width at tenth maximum (FWTM) can increase by 70% and PVDR can decrease up to 50%. But with proper gating, both the beam width and PVDR changes can be negligible. Future experiments will involve irradiation of mouse models and comparing histology stains between the controls and the gated irradiation.

Paper Details

Date Published: 15 March 2013
PDF: 8 pages
Proc. SPIE 8671, Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling, 86711Z (15 March 2013); doi: 10.1117/12.2007998
Show Author Affiliations
Pavel Chtcheprov, The Univ. of North Carolina at Chapel Hill (United States)
Michael Hadsell, The Univ. of North Carolina at Chapel Hill (United States)
Laurel Burk, The Univ. of North Carolina at Chapel Hill (United States)
Rachel Ger, The Univ. of North Carolina at Chapel Hill (United States)
Lei Zhang, The Univ. of North Carolina at Chapel Hill (United States)
Hong Yuan, The Univ. of North Carolina at Chapel Hill (United States)
Yueh Z. Lee, The Univ. of North Carolina at Chapel Hill (United States)
Sha Chang, The Univ. of North Carolina at Chapel Hill (United States)
Jianping Lu, The Univ. of North Carolina at Chapel Hill (United States)
Otto Zhou, The Univ. of North Carolina at Chapel Hill (United States)


Published in SPIE Proceedings Vol. 8671:
Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling
David R. Holmes; Ziv R. Yaniv, Editor(s)

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