8 January 2018 7T MRI subthalamic nucleus atlas for use with 3T MRI
Mikhail Milchenko, Scott A. Norris, Kathleen L. Poston, Meghan C. Campbell, Mwiza Ushe, Joel S. Perlmutter, Abraham Z. Snyder
Author Affiliations +
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) reduces motor symptoms in most patients with Parkinson disease (PD), yet may produce untoward effects. Investigation of DBS effects requires accurate localization of the STN, which can be difficult to identify on magnetic resonance images collected with clinically available 3T scanners. The goal of this study is to develop a high-quality STN atlas that can be applied to standard 3T images. We created a high-definition STN atlas derived from seven older participants imaged at 7T. This atlas was nonlinearly registered to a standard template representing 56 patients with PD imaged at 3T. This process required development of methodology for nonlinear multimodal image registration. We demonstrate mm-scale STN localization accuracy by comparison of our 3T atlas with a publicly available 7T atlas. We also demonstrate less agreement with an earlier histological atlas. STN localization error in the 56 patients imaged at 3T was less than 1 mm on average. Our methodology enables accurate STN localization in individuals imaged at 3T. The STN atlas and underlying 3T average template in MNI space are freely available to the research community. The image registration methodology developed in the course of this work may be generally applicable to other datasets.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE) 2329-4302/2018/$25.00 © 2018 SPIE
Mikhail Milchenko, Scott A. Norris, Kathleen L. Poston, Meghan C. Campbell, Mwiza Ushe, Joel S. Perlmutter, and Abraham Z. Snyder "7T MRI subthalamic nucleus atlas for use with 3T MRI," Journal of Medical Imaging 5(1), 015002 (8 January 2018). https://doi.org/10.1117/1.JMI.5.1.015002
Received: 17 May 2017; Accepted: 12 December 2017; Published: 8 January 2018
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CITATIONS
Cited by 14 scholarly publications.
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KEYWORDS
Magnetic resonance imaging

Transform theory

Image registration

Scanners

Binary data

Radon

Brain

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