Rebecca Susan Dewey1,2,3, Deborah A Hall2,3, Hannah Guest4, Garreth Prendergast4, Christopher J Plack4,5, and Susan T Francis1
1Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom, 2National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, Nottingham, United Kingdom, 3Otology and Hearing Group, Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, United Kingdom, 4Manchester Centre for Audiology and Deafness (ManCAD), University of Manchester, Manchester, United Kingdom, 5Department of Psychology, Lancaster University, Lancaster, United Kingdom
Synopsis
We explore the effects of EPI distortion correction
and retrospective correction of cardiac and respiratory artefacts on fMRI data
quality. Further, we assess the suitability of this data to provide robust
detection of subcortical sound-evoked responses for inter-group and subgroup
analyses. We report an optimum acquisition, pre-processing and analysis
protocol for subcortical fMRI of the ascending auditory pathway.
Introduction
A
current focus of auditory neuroscience concerns the physiological mechanisms behind
“hidden” hearing loss [1]; hearing impairments that cannot be detected using
conventional diagnostic techniques such as pure tone audiometry. Permanent
noise-induced damage, apparent as a change in the ascending auditory pathway, has
been demonstrated following noise exposure in mammalian species [2]. Crucially,
this damage affects sensitivity to supra-threshold sounds, needed for interpreting
speech in noisy environments [3], but not sensitivity to quiet sounds. Subcortical fMRI of
the ascending auditory pathway requires high spatial resolution, and is
sensitive to EPI distortions and physiological (cardiac and respiratory) noise.
Here, we report optimised acquisition and analysis methods for subcortical fMRI
at 3.0 T for future assessment of the link between lifetime noise exposure and sound-evoked
responses. A secondary question concerns the group size necessary to robustly detect
subcortical activation.Methods
25 subjects with low to moderate noise exposure had
no history of audiological problems and gave informed written consent. Functional
and structural data were acquired on a Philips Ingenia 3.0 T MR scanner with a
32-channel head coil. fMRI data was collected using a gradient echo (GE) EPI
scheme (TE=35ms, FOV=34.5×34.5mm, 1.5mm isotropic resolution, SENSE=2.5, 23
slices with equidistant temporal slice spacing, TR=2 s). Slices were near-coronal
to provide coverage of the brainstem and Heschl’s gyrus (Figure 1). Each fMRI run
comprised 8 cycles of 24-s of broadband noise (1.4-4.1 kHz; 85 dB-SPL) and 42-s
rest presented using the OptoACTIVE Optical MRI Communication System
(Optoacoustics Ltd., Israel) during active noise cancellation. Four fMRI runs were
collected on each individual. In addition, 2 EPI dynamics were collected echo
shifted (37ms) and with reversed phase-encoding gradient. Structural data were
collected using a FLASH and high resolution 3D T2-weighted TSE
(turbo-spin-echo).
Image pre-processing and analysis was performed using
FSL, SPM12 and in-house Matlab scripts. fMRI data were motion corrected. To
optimise the analysis pipeline, distortion correction using FSL’s TOPUP
algorithm [4,5] and physiological noise correction using RETROICOR [6] were performed,
with the impact of these pre-processing stages assessed. All data were then spatially
smoothed (2mm Gaussian kernel). Binarised masks of white matter (WM) and CSF were
used to generate mean timecourses for use as regressors in the general linear
model (GLM). Statistical analyses were performed in SPM12 using a GLM of onset,
duration and offset of auditory stimulation as regressors of interest, with motion
parameters, WM and CSF as nuisance regressors. The FLASH image was
co-registered to a standard template [7], the resulting transformation matrix
applied to individual statistical parameter maps (SPMs), and random-effects group
analysis performed. To assess the resulting SPMs, ROI analyses were performed
using spherical 6-mm subcortical ROIs centred on co-ordinates defined by
Gutschalk et al. [8]. We evaluate the
impact of optimised pre-processing (distortion and physiological noise
correction) on beta estimates of the fMRI response. To further evaluate this
impact, a subgroup analysis was performed, reducing the number of participants
in the group [n=20, 15, 10], comparing different levels of pre-processing, to
determine the group size necessary to robustly detect subcortical activation.Results
Figure 2 shows group activation maps of the ascending
auditory pathway, highlighting strong inferior colliculus (IC) and cochlear
nucleus (CN) activity for both standard and optimised pre-processing pipelines.
Figure 3 shows subcortical ROI locations and group mean percentage difference (±
standard error) in beta values resulting from optimised, compared to standard,
pre-processing within these ROIs and the auditory cortex, highlighting a
significant improvement in beta values using the optimised analysis method for
the medial geniculate body (MGB) and nucleus of the lateral lemniscus (NLL). Subcortical
regions namely the CN, superior olivary complex (SOC); NLL and IC respond
continually to a sustained auditory stimulus, whereas the MGB and auditory
cortex respond more to the onset and offset of the stimulus, as shown in the
mean timecourses (Figure 4).
Subgroup analyses showed that sound-evoked
responses could be detected bilaterally in the CN and SOC (and other ROIs) in a
group size of n=20 provided EPI distortion correction was used (independent of
performing physiological noise correction), whilst a group size (n>=25) was
required to detect bilateral CN or SOC responses without EPI distortion
correction.Discussion
This
study has demonstrated robust subcortical sound-evoked fMRI responses at 3.0 T,
which are improved using EPI distortion and physiological noise correction.Conclusion
This
optimised fMRI protocol allows the robust study of the human auditory system. In
this ongoing study, behavioural and neuroimaging techniques will be combined to
assess changes in the auditory pathway associated with hidden hearing loss in
individuals with varying cumulative lifetime noise exposures (subgroups of n=30).Acknowledgements
This
work is supported by Medical Research Council (MRC) reference MR/L003589/1
awarded to the University of Manchester.References
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