Quantitative structural neuroimaging of mild traumatic brain injury in the Chronic Effects of Neurotrauma Consortium (CENC): Comparison of volumetric data within and across scanners

Abstract

Background: An important component of the multicentre Chronic Effects of Neurotrauma Consortium (CENC) project is the development of improved quantitative magnetic resonance imaging (MRI) methods, including volumetric analysis. Although many studies routinely employ quality assurance (QA) procedures including MR and human phantoms to promote accuracy and monitor site differences, few studies perform rigorous direct comparisons of these data nor report findings that enable inference regarding site-to-site comparability. These gaps in evaluating cross-site differences are concerning, especially given the well-established differences that can occur between data acquired on scanners with different manufacturer, hardware or software.

Methods: This study reports findings on (1) a series of studies utilizing two MR phantoms to interrogate machine-based variability using data collected on the same magnet, (2) a human phantom repeatedly imaged on the same scanner to investigate within-subject, within-site variability and (3) a human phantom imaged on three different scanners to examine within subject, between-site variability.

Results: Although variability is relatively minimal for the phantom scanned on the same magnet, significantly more variability is introduced in a human subject, particularly when regions are relatively small or multiple sites used.

Conclusion: Vigilance when combining data from different sites is suggested and that future efforts address these issues.

Keywords:

• Neuroimaging
• brain imaging
• magnetic resonance imaging
• veterans
• volumetrics
• phantoms

Acknowledgements

The authors wish to acknowledge all other members of the CENC Neuroimaging Core, including Aaron M. Betts, MD, Andrew Mayer, PhD, Joel L. Steinberg, MD, Randall S. Scheibel, PhD and Xiaoqi Li, PhD, as well as CENC site neuroradiologists and technologists including John L. Ritter, MD, Jorge deVillasante, MD, Michael Lennon, MD, Rajan Agarwal, MD, Robert Cadrain, Marice L. Brown and William Wolfcale. We also wish to thank CENC leadership (Drs. David X. Cifu, Ramon Diaz-Arrastia, Rick Williams and Col. Sidney R. Hinds) for their support and the CENC Government Steering Committee for their oversight.

Declaration of interest

This project was jointly supported by the Department of Defense (W81XWH-13-2-0095), and the US Department of Veterans Affairs (I01 RX 002174). The authors report no conflicts of interest. The views expressed here are those of the authors and do not necessarily reflect the official policy of position of the Department of Defense, The Department of Veterans Affairs, nor the US Government.