Development and validation of retrospective spinal cord motion time-course estimates (RESPITE) for spin-echo spinal fMRI: Improved sensitivity and specificity by means of a motion-compensating general linear model analysis.

Cervical spinal cord displacements have recently been measured in relation to the cardiac cycle, substantiating that cord motion in this region reduces both the sensitivity and reproducibility of functional magnetic resonance imaging of the spinal cord (spinal fMRI). Given the ubiquitous and complex nature of this motion, cardiac gating alone is not expected to sufficiently remove these errors, whereas current modeling approaches for spin-echo methods are not specific to motion artifacts, potentially eliminating function-related data along with components of motion-related noise. As such, we have developed an alternative approach to spinal cord motion-compensation, using retrospective spinal cord motion time-course estimates (RESPITE) to forecast a small number of physiological noise regressors. These are generated from the principal components of spinal cord motion, as well as subject-specific cardiac data, and are subsequently included in a general linear model (GLM) analysis. With this approach, the components of motion-related signal fluctuation are modeled, along with functionally-relevant signal changes (i.e., those components fitting the stimulus paradigm), to account for the effects of spinal cord and cerebrospinal fluid (CSF) motion in a thorough, yet discerning, manner. By analyzing 100 previously acquired half-Fourier turbo spin-echo (HASTE) spinal fMRI data sets, along with a collection of null-task data, we show that the implementation of RESPITE reduces the occurrence of both type I (false-positive) and type II (false negative) errors, effectively increasing the specificity (5-6%) and sensitivity (15-20%) to neuronal activity.