Samson, RS;
Levy, S;
Schneider, T;
Smith, AK;
Smith, SA;
Cohen-Adad, J;
Wheeler-Kingshott, CAMG;
(2016)
ZOOM or Non-ZOOM? Assessing spinal cord diffusion tensor imaging protocols for multi-centre studies.
PLOS ONE
, 11
(5)
, Article e0155557. 10.1371/journal.pone.0155557.
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Abstract
The purpose of this study was to develop and evaluate two spinal cord (SC) diffusion tensor imaging (DTI) protocols, implemented at multiple sites (using scanners from two different manufacturers), one available on any clinical scanner, and one using more advanced options currently available in the research setting, and to use an automated processing method for unbiased quantification. DTI parameters are sensitive to changes in the diseased SC. However, imaging the cord can be technically challenging due to various factors including its small size, patient-related and physiological motion, and field inhomogeneities. Rapid acquisition sequences such as Echo Planar Imaging (EPI) are desirable but may suffer from image distortions. We present a multi-centre comparison of two acquisition protocols implemented on scanners from two different vendors (Siemens and Philips), one using a reduced field-of-view (rFOV) EPI sequence, and one only using options available on standard clinical scanners such as outer volume suppression (OVS). Automatic analysis was performed with the Spinal Cord Toolbox for unbiased and reproducible quantification of DTI metrics in the white matter. Images acquired using the rFOV sequence appear less distorted than those acquired using OVS alone. SC DTI parameter values obtained using both sequences at all sites were consistent with previous measurements made at 3T. For the same scanner manufacturer, DTI parameter inter-site SDs were smaller for the rFOV sequence compared to the OVS sequence. The higher inter-site reproducibility (for the same manufacturer and acquisition details, i.e. ZOOM data acquired at the two Philips sites) of rFOV compared to the OVS sequence supports the idea that making research options such as rFOV more widely available would improve accuracy of measurements obtained in multi-centre clinical trials. Future multi-centre studies should also aim to match the rFOV technique and signal-to-noise ratios in all sequences from different manufacturers/sites in order to avoid any bias in measured DTI parameters and ensure similar sensitivity to pathological changes.
Type: | Article |
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Title: | ZOOM or Non-ZOOM? Assessing spinal cord diffusion tensor imaging protocols for multi-centre studies |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1371/journal.pone.0155557 |
Publisher version: | http://dx.doi.org/10.1371/journal.pone.0155557 |
Additional information: | © 2016 Samson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
Keywords: | Science & Technology, Multidisciplinary Sciences, Science & Technology - Other Topics, HUMAN OPTIC-NERVE, OF-THE-ART, MULTIPLE-SCLEROSIS, MATTER DEMYELINATION, MRI, MOTION, FIELD, RESOLUTION, REDUCTION, ARTIFACTS |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Neuroinflammation |
URI: | https://discovery.ucl.ac.uk/id/eprint/1508438 |
Available Versions of this Item
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ZOOM and non-ZOOM spinal cord diffusion tensor imaging protocols for multi-centre studies. (deposited 02 Jun 2014 18:35)
- ZOOM or Non-ZOOM? Assessing spinal cord diffusion tensor imaging protocols for multi-centre studies. (deposited 22 Aug 2016 13:47) [Currently Displayed]
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