2 March 2017 New concept on an integrated interior magnetic resonance imaging and medical linear accelerator system for radiation therapy
Xun Jia, Zhen Tian, Yan Xi, Steve B. Jiang, Ge Wang
Author Affiliations +
Abstract
Image guidance plays a critical role in radiotherapy. Currently, cone-beam computed tomography (CBCT) is routinely used in clinics for this purpose. While this modality can provide an attenuation image for therapeutic planning, low soft-tissue contrast affects the delineation of anatomical and pathological features. Efforts have recently been devoted to several MRI linear accelerator (LINAC) projects that lead to the successful combination of a full diagnostic MRI scanner with a radiotherapy machine. We present a new concept for the development of the MRI-LINAC system. Instead of combining a full MRI scanner with the LINAC platform, we propose using an interior MRI (iMRI) approach to image a specific region of interest (RoI) containing the radiation treatment target. While the conventional CBCT component still delivers a global image of the patient’s anatomy, the iMRI offers local imaging of high soft-tissue contrast for tumor delineation. We describe a top-level system design for the integration of an iMRI component into an existing LINAC platform. We performed numerical analyses of the magnetic field for the iMRI to show potentially acceptable field properties in a spherical RoI with a diameter of 15 cm. This field could be shielded to a sufficiently low level around the LINAC region to avoid electromagnetic interference. Furthermore, we investigate the dosimetric impacts of this integration on the radiotherapy beam.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE) 2329-4302/2017/$25.00 © 2017 SPIE
Xun Jia, Zhen Tian, Yan Xi, Steve B. Jiang, and Ge Wang "New concept on an integrated interior magnetic resonance imaging and medical linear accelerator system for radiation therapy," Journal of Medical Imaging 4(1), 015004 (2 March 2017). https://doi.org/10.1117/1.JMI.4.1.015004
Received: 8 November 2016; Accepted: 13 February 2017; Published: 2 March 2017
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CITATIONS
Cited by 5 scholarly publications.
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KEYWORDS
Magnetic resonance imaging

Radiotherapy

Magnetism

Imaging systems

Tumors

Liver

Scanners

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