Automated Voxel Placement: A Linux-based Suite of Tools for Accurate and Reliable Single Voxel Coregistration

Eric A. Woodcock, Muzamil Arshad, Dalal Khatib and Jeffrey A. Stanley

Abstract

Background: Single-voxel proton magnetic resonance spectroscopy (¹H MRS) is a powerful technique for studying in vivo neurochemistry, but has an often-overlooked source of error variance: inconsistent voxel placement between scans. We developed and evaluated an Automated Voxel Placement (AVP) procedure for accurate and reliable 1 H MRS voxel prescription. AVP is a suite of Linux-based programs that facilitate automated template-driven single-voxel coregistration.
Methods: Three studies were conducted to evaluate AVP for prescription of one voxel: left dorsolateral prefrontal cortex. First, we evaluated how robust AVP was to ‘extreme’ subject head positions/angulations within the scanner head coil. Second, subjects (N = 13) were recruited and underwent MR scans. Manual voxel prescription (n = 5) was contrasted with AVP (n = 8). A subset of AVP subjects (n = 4) completed a second scan. Third, ongoing data collection (n = 16; recruited for a separate study) helped evaluate AVP. Voxel placement accuracy was quantified as 3D geometric voxel overlap percentage between each subject’s voxel and the template voxel. Reliability was quantified as 3D geometric voxel overlap percentage across subjects at each time point and within subjects who completed two scans.
Results: Results demonstrated that AVP was robust to ‘extreme’ head positions (97.5% – 97.9% overlap with the template voxel). AVP was significantly more accurate (baseline and follow-up: 96.2% ± 3.0% and 97.6% ± 1.4% overlap) than manual voxel placement (67.7% ± 22.8% overlap; ps<.05). AVP was reliable within- (97.9%) and between-subjects (94.2% and 97.2% overlap; baseline and follow-up; respectively). Finally, ongoing data collection indicates AVP is accurate (96.0%).

Conclusion: These pilot studies demonstrated that AVP was feasible, accurate, and reliable method for automated single voxel coregistration.

Published on: February 08, 2018
doi: 10.17756/jnpn.2018-020
Citation:  Woodcock EA, Arshad M, Khatib D, Stanley JA. 2018. Automated Voxel Placement:
A Linux-based Suite of Tools for Accurate and Reliable Single Voxel Coregistration. J Neuroimaging Psychiatry Neurol 3(1): 1-8.

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