Experimental evidence in animal models indicates that the brainstem plays a major role in sensory modulation. However, mapping functional activity within the human brainstem presents many methodological challenges. These constraints have deterred essential research into human sensory brainstem processing. Here, using a 3T functional Magnetic Resonance Imaging (fMRI) sequence optimised for the brainstem, combined with uni- and multivariate analysis approaches, we investigated the extent to which functional activity of neighbouring somatosensory nuclei can be delineated in the brainstem, thalamus, and primary somatosensory cortex (S1). Whilst traditional univariate approaches offered limited differentiation between adjacent hand and face activation in the brainstem, multivariate classification enabled above-chance decoding of these activity patterns across S1, the thalamus, and the brainstem. Our findings establish a robust methodological approach to explore signal processing within the brainstem and across the entire somatosensory stream. This is a fundamental step towards broadening our understanding of somatosensory processing within humans and determining what changes in sensory integration may occur in clinical populations following sensory deprivation.

Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject’s sex and age. However, corrections for body size (i.e., height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1 ± 6.6 years old, 125 females). We show that body height correlates with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44 ≤ r ≤ 0.62). Intracranial volume (ICV) correlates with body height (r = 0.46) and the brain volumes and CSA-WM (0.37 ≤ r ≤ 0.77). In comparison, age correlates with cortical GM volume, precentral GM volume, and cortical thickness (-0.21 ≥ r ≥ -0.27). Body weight correlates with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20 ≥ r ≥ -0.23). Body weight further correlates with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r = -0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlates with brain volumes (0.39 ≤ r ≤ 0.64), and with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22 ≥ r ≥ -0.25). Linear mixture of age, sex, or sex and age, explained 2 ± 2%, 24 ± 10%, or 26 ± 10%, of data variance in brain volumetry and SC CSA. The amount of explained variance increased to 33 ± 11%, 41 ± 17%, or 46 ± 17%, when body height, ICV, or body height and ICV were added into the mixture model. In females, the explained variances halved suggesting another unidentified biological factor(s) determining females’ central nervous system (CNS) morphology. In conclusion, body size and ICV are significant biological variables. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure; and body size and ICV should be considered as covariates in statistical analyses. Normalization of different brain regions with ICV diminishes their correlations with body size, but simultaneously amplifies ICV-related variance (r = 0.72 ± 0.07) and suppresses volume variance of the different brain regions (r = 0.12 ± 0.19) in the normalized measurements.

Intravoxel incoherent motion (IVIM) measurements allow to probe tissue microcirculation non-invasively. Spinal cord perfusion has been shown to be altered following different neurological pathologies. A non-invasive imaging protocol to assess perfusion in the cervical cord is, therefore, clinically relevant. This work aimed at assessing the reliability of IVIM parameters sensitive to perfusion changes in the cervical cord by determining the test-retest variability across subjects and different post-processing fitting algorithms. IVIM test-retest scans were acquired in the cervical cord (C1-C3) of 10 healthy subjects on a 3T MRI scanner, with a 15-minute break in-between. IVIM parameters, including microvascular volume fraction ( F ), pseudo-diffusion coefficient ( D * ), blood flow-related coefficient ( F · D * ), and diffusion coefficient ( D ), were derived using voxel-wise and region of interest (ROI)-wise fits. The reliability of each IVIM parameter was determined with coefficients of variation (CV), intraclass correlation coefficients (ICC), Bland-Altman analysis, and linear regression. To assess the effects of the different fitting approaches, a two-way repeated-measures analysis of variance (ANOVA) was conducted on the CVs calculated across fitting algorithms. Mean CVs of IVIM parameters calculated across subjects using the voxel-wise fit were lower in the white matter (WM) and grey matter (GM): (WM: 2.6% to 15.6%; GM: 2.2% to 16.4%) compared with those calculated using the ROI-wise fit approach (WM: 4.5% to 32.2%; GM: 3.4% to 53.4%). The voxel-wise fit in the WM yielded higher ICC values (good-to-excellent, 0.71–0.97) compared to the ROI-wise fit approach (poor-to-excellent, 0.49–0.90). IVIM parameters, derived using the voxel-wise fitting approach, demonstrated a high reliability in the cervical cord. Results highlight the high variability of IVIM parameter values depending on the fitting approach, underlining the importance of characterizing the reliability of IVIM acquisition and fitting configuration in the relevant organ of interest. Robust IVIM metrics using a voxel-wise one-step approach, observed across scans and subjects, can facilitate studies targeting perfusion impairment and pave the way to future clinical trials assessing perfusion impairment as a potential quantitative biomarker.

Diffusion MRI (dMRI) has become a crucial imaging technique in the field of neuroscience, with a growing number of clinical applications. Although most studies still focus on the brain, there is a growing interest in utilizing dMRI to investigate the healthy or injured spinal cord. The past decade has also seen the development of biophysical models that link MR-based diffusion measures to underlying microscopic tissue characteristics, which necessitates validation through ex vivo dMRI measurements. Building upon 13 years of research and development, we present an open-source, MATLAB-based academic software toolkit dubbed ACID: A C omprehensive Toolbox for I mage Processing and Modeling of Brain, Spinal Cord, and Ex Vivo D iffusion MRI Data. ACID is an extension to the Statistical Parametric Mapping (SPM) software, designed to process and model dMRI data of the brain, spinal cord, and ex vivo specimens by incorporating state-of-the-art artifact correction tools, diffusion and kurtosis tensor imaging, and biophysical models that enable the estimation of microstructural properties in white matter. Additionally, the software includes an array of linear and nonlinear fitting algorithms for accurate diffusion parameter estimation. By adhering to the Brain Imaging Data Structure (BIDS) data organization principles, ACID facilitates standardized analysis, ensures compatibility with other BIDS-compliant software, and aligns with the growing availability of large databases utilizing the BIDS format. Furthermore, being integrated into the popular SPM framework, ACID benefits from a wide range of segmentation, spatial processing, and statistical analysis tools as well as a large and growing number of SPM extensions. As such, this comprehensive toolbox covers the entire processing chain from raw DICOM data to group-level statistics, all within a single software package.

Synthetic MRI offers the advantage of reducing acquisition time and enhancing flexibility through the reconstruction of various contrast weightings from a single set of MRI scans. However, the use of synthetic T 1 -weighted (synT 1 -w) MRI can lead to potentially biased measurements of the cross-sectional area (CSA) in the spinal cord when compared to conventionally acquired T 1 -weighted MRI. This disparity can have implications for comparability and sensitivity of MRI in assessing disease progression or treatment effects in neurodegenerative spinal cord disorders. Thus, this study aimed at improving the accuracy (i.e., difference between synthetic and acquired MRI) of cervical cord CSA measurements (C1-C3 level) based on synT 1 -w MRI implementing a longitudinal data set acquired from 23 acute spinal cord injury (SCI) patients and 21 healthy controls over 2 years. Moreover, the validity of using synT 1 -w MRI for tracking cervical cord atrophy following SCI over 2 years was verified. SynT 1 -w images were reconstructed from quantitative maps of proton density, longitudinal, and effective transverse relaxation rates derived from a multi-parameter mapping protocol. The results showed a minimal bias of -0.31 mm 2 (-0.5%) in CSA measurements based on synT 1 -w compared to acquired MRI. Estimates of atrophy rates and average CSA were comparable between synthetic and acquired MRI. A sample size estimation for detecting treatment effects on CSA atrophy after 2 years following SCI revealed that the required sample size is reduced by 13.5% using synT 1 -w instead of acquired MRI. This study shows high accuracy of synT 1 -w MRI and demonstrates its applicability in clinical studies for optimizing long MRI protocols.

Blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) can be used to map neuronal function in the cervical cord, yet conclusive evidence supporting its applicability in the lumbosacral cord is still lacking. This study aimed to (i) demonstrate the feasibility of BOLD fMRI for indirectly mapping neural activity in the lumbosacral cord during a unilateral lower extremity motor task and (ii) investigate the impact of echo time (TE) on the BOLD effect size. Twelve healthy volunteers underwent BOLD fMRI using four reduced field-of-view single-shot gradient-echo echo planar imaging sequences, all with the same geometry but different TE values ranging from 20 to 42 ms. Each sequence was employed to acquire a single 6-min rest run and two 10-min task runs, which included alternating 15-s blocks of rest and unilateral ankle dorsi- and plantar flexion. We detected lateralized task-related BOLD activity at neurological levels L3-S2, centered at the ipsilateral (right) ventral spinal cord but also extending into the ipsilateral dorsal spinal cord. This pattern of activation is consistent with our current understanding of spinal cord organization, wherein lower motor neurons are located in the ventral gray matter horn, while interneurons neurons of the proprioceptive pathway, activated during the movement, are located in the dorsal horns and the intermediate gray matter. At the subject level, BOLD activity showed considerable variability but was lateralized in all participants. The highest BOLD effect size within the ipsilateral ventral spinal cord, as well as the highest split-half reliability, was observed at a TE of 42 ms. Sequences with a shorter TE (20 and 28 ms) also detected activity in the medioventral part of the spinal cord, likely representing large vein effects. In summary, our results demonstrate the feasibility of detecting task-related BOLD activity in the lumbosacral cord induced by voluntary lower limb movements. BOLD fMRI in the lumbosacral cord has significant implications for assessing motor function and its alterations in disease or after spinal cord injury.