Spinal Cord Toolbox Research Articles

Validation of a New Semiautomated Segmentation Pipeline Based on the Spinal Cord Toolbox DeepSeg Algorithm to Estimate the Cervical Canal Area.

As in the brain reserve concept, a larger cervical canal area may also protect against disability. In this context, a semiautomated pipeline has been developed to obtain quantitative estimations of the cervical canal area. The aim of the study was to validate the pipeline, to evaluate the consistency of the cervical canal area measurements during a 1-year period, and to compare cervical canal area estimations obtained from brain and cervical MRI acquisitions. Eight healthy controls and 18 patients with MS underwent baseline and follow-up 3T brain and cervical spine sagittal 3D MPRAGE. The cervical canal area was measured in all acquisitions, and estimations obtained with the proposed pipeline were compared with manual segmentations performed by 1 evaluator using the Dice similarity coefficient. The cervical canal area estimations obtained on baseline and follow-up T1WI were compared; brain and cervical cord acquisitions were also compared using the individual and average intraclass correlation coefficients. The agreement between the manual cervical canal area masks and the masks provided by the proposed pipeline was excellent, with a mean Dice similarity coefficient mean of 0.90 (range, 0.73-0.97). The cervical canal area estimations obtained from baseline and follow-up scans showed a good level of concordance (intraclass correlation coefficient = 0.76; 95% CI, 0.44-0.88); estimations obtained from brain and cervical MRIs also had good agreement (intraclass correlation coefficient = 0.77; 95% CI, 0.45-0.90). The proposed pipeline is a reliable tool to estimate the cervical canal area. The cervical canal area is a stable measure across time; moreover, when cervical sequences are not available, the cervical canal area could be estimated using brain T1WI.

Assessing the Equivalence of Brain-Derived Measures from Two 3D T1-Weighted Acquisitions: One Covering the Brain and One Covering the Brain and Spinal Cord.

In MS, it is common to acquire brain and spinal cord MR imaging sequences separately to assess the extent of the disease. The goal of this study was to see how replacing the traditional brain T1-weighted images (brain-T1) with an acquisition that included both the brain and the cervical spinal cord (cns-T1) affected brain- and spinal cord-derived measures. Thirty-six healthy controls (HC) and 42 patients with MS were included. Of those, 18 HC and 35 patients with MS had baseline and follow-up at 1 year acquired on a 3T magnet. Two 3D T1-weighted images (brain-T1 and cns-T1) were acquired at each time point. Regional cortical thickness and volumes were determined with FastSurfer, and the percentage brain volume change per year was obtained with SIENA. The spinal cord area was estimated with the Spinal Cord Toolbox. Intraclass correlation coefficients (ICC) were calculated to check for consistency of measures obtained from brain-T1 and cns-T1. Cortical thickness measures showed an ICC >0.75 in 94% of regions in healthy controls and 80% in patients with MS. Estimated regional volumes had an ICC >0.88, and the percentage brain volume change had an ICC >0.79 for both groups. The spinal cord area measures had an ICC of 0.68 in healthy controls and 0.92 in patients with MS. Brain measurements obtained from 3D cns-T1 are highly equivalent to those obtained from a brain-T1, suggesting that it could be feasible to replace the brain-T1 with cns-T1.

Remodeling of the brain correlates with gait instability in cervical spondylotic myelopathy.

Cervical spondylotic myelopathy (CSM) is a common form of non-traumatic spinal cord injury (SCI) and usually leads to remodeling of the brain and spinal cord. In CSM with gait instability, the remodeling of the brain and cervical spinal cord is unclear. We attempted to explore the remodeling of these patients' brains and spinal cords, as well as the relationship between the remodeling of the brain and spinal cord and gait instability. According to the CSM patients' gait, we divided patients into two groups: normal gait patients (nPT) and abnormal gait patients (aPT). Voxel-wise z-score transformation amplitude of low-frequency fluctuations (zALFF) and resting-state functional connectivity (rs-FC) were performed for estimating brain changes. Cross-sectional area (CSA) and fractional anisotropy (FA) of the spinal cord were computed by Spinal cord toolbox. Correlations of these measures and the modified Japanese Orthopedic Association (mJOA) score were analyzed. We found that the zALFF of caudate nucleus in aPT was higher than that in healthy controls (HC) and lower than that in nPT. The zALFF of the right postcentral gyrus and paracentral lobule in HC was higher than those of aPT and nPT. Compared with the nPT, the aPT showed increased functional connectivity between the caudate nucleus and left angular gyrus, bilateral precuneus and bilateral posterior cingulate cortex (PCC), which constitute a vital section of the default mode network (DMN). No significantly different FA values or CSA of spinal tracts at the C2 level were observed between the HC, nPT and aPT groups. In CSM, the right paracentral lobule's zALFF was negatively correlated with the FA value of fasciculus gracilis (FCG), and the right caudate zALFF was positively correlated with the FA value of the fasciculus cuneatus (FCC). The results showed that the functional connectivity between the right caudate nucleus and DMN was negatively correlated with the CSA of the lateral corticospinal tract (CST). The activation of the caudate nucleus and the strengthening functional connectivity between the caudate nucleus and DMN were associated with gait instability in CSM patients. Correlations between spinal cord and brain function might be related to the clinical symptoms in CSM.

Spinal cord reserve in multiple sclerosis

BackgroundThe spinal cord (SC) is a preferential target of multiple sclerosis (MS) damage highly relevant towards disability. Differential impact of such damage could be due to the initial amount of...

Contrast-agnostic deep learning–based registration pipeline: Validation in spinal cord multimodal MRI data

Medical image registration can be challenging, in that optimal solutions depend on the application domain (unimodal, multimodal, intra-subject and inter-subject), anatomical sites (e.g., brain, spinal cord (SC) and lungs), dimensionality of the data (2D, 3D and 4D), deformation constraints (rigid, affine and nonlinear) and computational time. Solutions that could accommodate a large variety of applications while producing satisfactory results are needed. SynthMorph was recently introduced as an unsupervised deep learning–based registration method. A particularly interesting feature is that training is performed on synthetic data so that registration becomes agnostic to image contrast and anatomy. However, SynthMorph is particularly sensitive to the initial closeness of the images. In this work, we extend the SynthMorph method by developing a cascaded pipeline of two models that can accommodate large and fine deformations, respectively. We also validate this pipeline for the registration of intra-subject multimodal and inter-subject uni/multimodal MRI data of the SC. This task is known to be particularly difficult due to the vicinity of multiple tissue types whose morphometrics can vary substantially across subjects and contrasts. Evaluation of the method was conducted on a publicly available dataset (spine-generic, 267 subjects) and was compared with a state-of-the-art benchmark: Spinal Cord Toolbox and Advanced Normalization Tools. Results demonstrate better registration accuracy compared with the benchmark and about 24–30 times faster on CPUs depending on the image size. This proposed pipeline provides an easy-to-use, accurate and fast solution for multimodal 3D registration. The code and trained models are freely available at https://github.com/ivadomed/multimodal-registration.

Analysis of brain and spinal MRI measures in a common domain to investigate directional neurodegeneration in motor neuron disease

BackgroundMagnetic resonance imaging (MRI) of the brain and cervical spinal cord is often performed in diagnostic evaluation of suspected motor neuron disease/amyotrophic lateral sclerosis (MND/ALS). Analysis of MRI-derived tissue damage metrics in a common domain facilitates group-level inferences on pathophysiology. This approach was applied to address competing hypotheses of directionality of neurodegeneration, whether anterograde, cranio-caudal dying-forward from precentral gyrus or retrograde, dying-back.MethodsIn this cross-sectional study, MRI was performed on 75 MND patients and 13 healthy controls. Precentral gyral thickness was estimated from volumetric T1-weighted images using FreeSurfer, corticospinal tract fractional anisotropy (FA) from diffusion tensor imaging using FSL, and cross-sectional cervical cord area between C1-C8 levels using Spinal Cord Toolbox. To analyse these multimodal data within a common domain, individual parameter estimates representing tissue damage at each corticospinal tract level were first converted to z-scores, referenced to healthy control norms. Mixed-effects linear regression models were then fitted to these z-scores, with gradients hypothesised to represent directionality of neurodegeneration.ResultsAt group-level, z-scores did not differ significantly between precentral gyral and intracranial corticospinal tract tissue damage estimates (regression coefficient − 0.24, [95% CI − 0.62, 0.14], p = 0.222), but step-changes were evident between intracranial corticospinal tract and C1 (1.14, [95% CI 0.74, 1.53], p < 0.001), and between C5 and C6 cord levels (0.98, [95% CI 0.58, 1.38], p < 0.001).DiscussionAnalysis of brain and cervical spinal MRI data in a common domain enabled investigation of pathophysiological hypotheses in vivo. A cranio-caudal step-change in MND patients was observed, and requires further investigation in larger cohorts.

Reliability of multi-parameter mapping (MPM) in the cervical cord: A multi-center multi-vendor quantitative MRI study

MRI based multicenter studies which target neurological pathologies affecting the spinal cord and brain – including spinal cord injury (SCI) – require standardized acquisition protocols and image processing methods. We have optimized and applied a multi-parameter mapping (MPM) protocol that simultaneously covers the brain and the cervical cord within a traveling heads study across six clinical centers (Leutritz et al., 2020). The MPM protocol includes quantitative maps (magnetization transfer saturation (MT), proton density (PD), longitudinal (R1), and effective transverse (R2*) relaxation rates) sensitive to myelination, water content, iron concentration, and morphometric measures, such as cross-sectional cord area. Previously, we assessed the repeatability and reproducibility of the brain MPM data acquired in the five healthy participants who underwent two scan-rescans (Leutritz et al., 2020). This study focuses on the cervical cord MPM data derived from the same acquisitions to determine its repeatability and reproducibility in the cervical cord. MPM matrices of the cervical cord were generated and processed using the hMRI and the spinal cord toolbox. To determine reliability of the cervical MPM data, the intra-site (i.e., scan-rescan) coefficient of variation (CoV), inter-site CoV, and bias within region of interests (C1, C2 and C3 levels) were determined. The range of the mean intra- and inter-site CoV of MT, R1 and PD was between 2.5% and 12%, and between 1.1% and 4.0% for the morphometric measures. In conclusion, the cervical MPM data showed a high repeatability and reproducibility for key imaging biomarkers and hence can be employed as a standardized tool in multi-center studies, including clinical trials.

Confounder-adjusted MRI-based predictors of multiple sclerosis disability.

Both aging and multiple sclerosis (MS) cause central nervous system (CNS) atrophy. Excess brain atrophy in MS has been interpreted as "accelerated aging." Current paper tests an alternative hypothesis: MS causes CNS atrophy by mechanism(s) different from physiological aging. Thus, subtracting effects of physiological confounders on CNS structures would isolate MS-specific effects. Standardized brain MRI and neurological examination were acquired prospectively in 646 participants enrolled in ClinicalTrials.gov Identifier: NCT00794352 protocol. CNS volumes were measured retrospectively, by automated Lesion-TOADS algorithm and by Spinal Cord Toolbox, in a blinded fashion. Physiological confounders identified in 80 healthy volunteers were regressed out by stepwise multiple linear regression. MS specificity of confounder-adjusted MRI features was assessed in non-MS cohort (n = 158). MS patients were randomly split into training (n = 277) and validation (n = 131) cohorts. Gradient boosting machine (GBM) models were generated in MS training cohort from unadjusted and confounder-adjusted CNS volumes against four disability scales. Confounder adjustment highlighted MS-specific progressive loss of CNS white matter. GBM model performance decreased substantially from training to cross-validation, to independent validation cohorts, but all models predicted cognitive and physical disability with low p-values and effect sizes that outperform published literature based on recent meta-analysis. Models built from confounder-adjusted MRI predictors outperformed models from unadjusted predictors in the validation cohort. GBM models from confounder-adjusted volumetric MRI features reflect MS-specific CNS injury, and due to stronger correlation with clinical outcomes compared to brain atrophy these models should be explored in future MS clinical trials.

Diffusion Kurtosis Imaging of Neonatal Spinal Cord in Clinical Routine.

Diffusion kurtosis imaging (DKI) has undisputed advantages over the more classical diffusion magnetic resonance imaging (dMRI) as witnessed by the fast-increasing number of clinical applications and software packages widely adopted in brain imaging. However, in the neonatal setting, DKI is still largely underutilized, in particular in spinal cord (SC) imaging, because of its inherently demanding technological requirements. Due to its extreme sensitivity to non-Gaussian diffusion, DKI proves particularly suitable for detecting complex, subtle, fast microstructural changes occurring in this area at this early and critical stage of development, which are not identifiable with only DTI. Given the multiplicity of congenital anomalies of the spinal canal, their crucial effect on later developmental outcome, and the close interconnection between the SC region and the brain above, managing to apply such a method to the neonatal cohort becomes of utmost importance. This study will (i) mention current methodological challenges associated with the application of advanced dMRI methods, like DKI, in early infancy, (ii) illustrate the first semi-automated pipeline built on Spinal Cord Toolbox for handling the DKI data of neonatal SC, from acquisition setting to estimation of diffusion measures, through accurate adjustment of processing algorithms customized for adult SC, and (iii) present results of its application in a pilot clinical case study. With the proposed pipeline, we preliminarily show that DKI is more sensitive than DTI-related measures to alterations caused by brain white matter injuries in the underlying cervical SC.

Mapping Pediatric Spinal Cord Development with Age.

Pediatric spinal cord morphometry has been relatively understudied because of non-optimal image quality due to the difficulty of spine imaging, rarity of post-mortem analysis, motion artifacts, and pediatric MR imaging research focus on understanding spinal injury or pathology. The pediatric brain has been comparatively well-studied with white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) differences observed with age and gender. Therefore, a greater understanding of pediatric cervical and thoracic spinal cord morphometry would be beneficial for developing clinically relevant cord growth models. We focused on retrospectively characterizing cervical and thoracic spinal cord growth and morphometry changes in a healthy pediatric population. High resolution multi-echo gradient echo (mFFE) images were acquired from pediatric spinal cord scans from 63 patients (mean: 9.24 years, range: 0.83-17.67 years). The mFFE scans were then registered to the template space for uniform viewing and analysis by using a customized semi-automatic processing pipeline involving Spinal Cord Toolbox (SCT). Jacobian control determinants were calculated, and subsequent WM, GM, dorsal column, lateral funiculi, and ventral funiculi scalar averaging was conducted. Random effects models were used to model age-related Jacobian scalar differences. Observing the growth of cord matter by patient age and vertebral level suggests that the upper cervical spinal cord, specifically C2-C3, and mid-thoracic spinal cord, T3-T8, grow faster than other cervical levels and thoracic levels, respectively. This knowledge will facilitate clinical decision making when considering spine interventions and conducting radiological analysis in children with cervical and thoracic spine abnormalities.

Semi-automated detection of cervical spinal cord compression with the Spinal Cord Toolbox

Degenerative cervical spinal cord compression is becoming increasingly prevalent, yet the MRI criteria that define compression are vague, and vary between studies. This contribution addresses the detection of compression by means of the Spinal Cord Toolbox (SCT) and assesses the variability of the morphometric parameters extracted with it. Prospective cross-sectional study. Two types of MRI examination, 3 and 1.5 T, were performed on 66 healthy controls and 118 participants with cervical spinal cord compression. Morphometric parameters from 3T MRI obtained by Spinal Cord Toolbox (cross-sectional area, solidity, compressive ratio, torsion) were combined in multivariate logistic regression models with the outcome (binary dependent variable) being the presence of compression determined by two radiologists. Inter-trial (between 3 and 1.5 T) and inter-rater (three expert raters and SCT) variability of morphometric parameters were assessed in a subset of 35 controls and 30 participants with compression. The logistic model combining compressive ratio, cross-sectional area, solidity, torsion and one binary indicator, whether or not the compression was set at level C6/7, demonstrated outstanding compression detection (area under curve =0.947). The single best cut-off for predicted probability calculated using a multiple regression equation was 0.451, with a sensitivity of 87.3% and a specificity of 90.2%. The inter-trial variability was better in Spinal Cord Toolbox (intraclass correlation coefficient was 0.858 for compressive ratio and 0.735 for cross-sectional area) compared to expert raters (mean coefficient for three expert raters was 0.722 for compressive ratio and 0.486 for cross-sectional area). The analysis of inter-rater variability demonstrated general agreement between SCT and three expert raters, as the correlations between SCT and raters were generally similar to those of the raters between one another. This study demonstrates successful semi-automated compression detection based on four parameters. The inter-trial variability of parameters established through two MRI examinations was conclusively better for Spinal Cord Toolbox compared with that of three experts' manual ratings.

White Matter Alterations in Spastic Paraplegia Type 5: A Multiparametric Structural MRI Study and Correlations with Biochemical Measurements.

In spastic paraplegia type 5, spinal cord atrophy and white matter signal abnormalities in the brain are the main MR imaging alterations. However, the specific mechanism remains unclear. We explored the microstructural changes occurring in spastic paraplegia type 5 and assessed the relation between MR imaging and clinical data. Seventeen patients with spastic paraplegia type 5 and 17 healthy controls were scanned with DTI and T1 mapping on a 3T MR imaging scanner. Fractional anisotropy, mean diffusivity, radial diffusivity, axial diffusivity, and T1 values were obtained using Tract-Based Spatial Statistics and the Spinal Cord Toolbox. Neurofilament light and myelin basic protein in the CSF were measured. The differences in MR imaging and biochemical data between patients with spastic paraplegia type 5 and healthy controls were compared using the Student t test. A widespread reduction of fractional anisotropy values and an elevation of mean diffusivity, T1, and radial diffusivity values were found in most cervical, T4, and T5 spinal cords; corona radiata; optic radiations; and internal capsules in spastic paraplegia type 5. A variation in axial diffusivity values was shown only in C2, C6, and the corona radiata but not in the gray matter. The levels of neurofilament light and myelin basic protein were higher in those with spastic paraplegia type 5 than in healthy controls (myelin basic protein, 3507 [SD, 2291] versus 127 [SD, 219] pg/mL; neurofilament light, 617 [SD, 207] versus 265 [SD, 187] pg/mL; P < .001). No correlation was found between the clinical data and MR imaging-derived measures. Multiparametric MR imaging and biochemical indicators demonstrated that demyelination (mainly) and axonal loss led to the white matter integrity loss without gray matter injury in spastic paraplegia type 5.

Design and Validation of an Expanded Disability Status Scale Model in Multiple Sclerosis

Introduction: We aimed to develop and validate an Expanded Disability Status Scale (EDSS) model through clinical, optical coherence tomography (OCT), and magnetic resonance imaging (MRI) measures. Methods: Sixty-four multiple sclerosis (MS) patients underwent peripapillary retinal nerve fiber layer and segmented macular layers evaluation through OCT (Spectralis, Heidelberg Engineering). Brain parenchymal fraction was quantified through Freesurfer, while cervical spinal cord (SC) volume was assessed manually guided by Spinal Cord Toolbox software analysis. EDSS, neuroradiological, and OCT assessment were carried out within 3 months. OCT parameters were calculated as the average of both nonoptic neuritis (ON) eyes, and in case the patient had previous ON, the value of the fellow non-ON eye was taken. Brain lesion volume, sex, age, disease duration, and history of disease-modifying treatment (1st or 2nd line disease-modifying treatments) were tested as covariables of the EDSS score. Results: EDSS values correlated with patient’s age (r = 0.543, p = 0.001), SC volume (r = −0.301, p = 0.034), and ganglion cell layer (GCL, r = −0.354, p = 0.012). Using these correlations, an ordinal regression model to express probability of diverse EDSS scores were designed, the highest of which was the most probable (Nagelkerke R2 = 43.3%). Using EDSS cutoff point of 4.0 in a dichotomous model, compared to a cutoff of 2.0, permits the inclusion of GCL as a disability predictor, in addition to age and SC. Conclusions: MS disability measured through EDSS is an age-dependent magnitude that is partly conditioned by SC and GCL. Further studies assessing paraclinical disability predictors are needed.

Tract-Specific Spinal Cord Diffusion Tensor Imaging in Friedreich's Ataxia.

Spinal cord (SC) damage is a hallmark in Friedreich's ataxia (FRDA). Neuroimaging has been able to capture some SC macroscopic changes, but no study has evaluated microstructural SC white matter (WM) damage in vivo. We designed a cross-sectional study to evaluate microstructural integrity in SC WM tracts of FRDA patients using diffusion tensor imaging (DTI) with an automated analysis pipeline. Thirty patients and 30 matched healthy controls underwent 3 Tesla (T) magnetic resonance imaging (MRI). We obtained cervical SC T2 and diffusion-weighted imaging (DWI) acquisitions. Images were processed using the Spinal Cord Toolbox v.4.3.0. For levels C2-C5, we measured cross-sectional area (CSA) and WM DTI parameters (axial diffusivity [AD], fractional anisotropy [FA], radial diffusivity [RD], and mean diffusivity [MD]). Age, duration, and FARS scores were also obtained. Mean age and disease duration of patients were 31 ± 10 and 11 ± 9 years, respectively. There was CSA reduction in FRDA amongst all levels. Between-group differences in FA, MD, and RD in total white matter (TWM), dorsal columns (DC), fasciculus gracilis (FG), fasciculus cuneatus (FC), and corticospinal tracts (CST) were present in all levels. FA and RD from TWM, DC, FC, and CST correlated with FARS scores, and in CST they also correlated with disease duration. DTI uncovered abnormalities in SC WM tracts, which correlated with clinical features in FRDA. CSA and CST FA in C2 correlated best with disease severity, whereas DC FA showed the largest effect size to differentiate patients and healthy controls. SC WM microstructure is a potential neuroimaging biomarker to be explored in the disease. © 2021 International Parkinson and Movement Disorder Society.

Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assessing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject dataset across 19 centers and a multi-subject dataset across 42 centers (for a total of 260 participants), spanning the three main MRI manufacturers: GE, Philips and Siemens. Both datasets are publicly available via git-annex. Data were analysed using the Spinal Cord Toolbox to produce normative values as well as inter/intra-site and inter/intra-manufacturer statistics. Reproducibility for the spine generic protocol was high across sites and manufacturers, with an average inter-site coefficient of variation of less than 5% for all the metrics. Full documentation and results can be found at https://spine-generic.rtfd.io/. The datasets and analysis pipeline will help pave the way towards accessible and reproducible quantitative MRI in the spinal cord.

Quantification of Cervical Cord Cross-Sectional Area: Which Acquisition, Vertebra Level, and Analysis Software? A Multicenter Repeatability Study on a Traveling Healthy Volunteer.

Background: Considerable spinal cord (SC) atrophy occurs in multiple sclerosis (MS). While MRI-based techniques for SC cross-sectional area (CSA) quantification have improved over time, there is no common agreement on whether to measure at single vertebral levels or across larger regions and whether upper SC CSA can be reliably measured from brain images.Aim: To compare in a multicenter setting three CSA measurement methods in terms of repeatability at different anatomical levels. To analyze the agreement between measurements performed on the cervical cord and on brain MRI.Method: One healthy volunteer was scanned three times on the same day in six sites (three scanner vendors) using a 3T MRI protocol including sagittal 3D T1-weighted imaging of the brain (covering the upper cervical cord) and of the SC. Images were analyzed using two semiautomated methods [NeuroQLab (NQL) and the Active Surface Model (ASM)] and the fully automated Spinal Cord Toolbox (SCT) on different vertebral levels (C1–C2; C2/3) on SC and brain images and the entire cervical cord (C1–C7) on SC images only.Results: CSA estimates were significantly smaller using SCT compared to NQL and ASM (p < 0.001), regardless of the cord level. Inter-scanner repeatability was best in C1–C7: coefficients of variation for NQL, ASM, and SCT: 0.4, 0.6, and 1.0%, respectively. CSAs estimated in brain MRI were slightly lower than in SC MRI (all p ≤ 0.006 at the C1–C2 level). Despite protocol harmonization between the centers with regard to image resolution and use of high-contrast 3D T1-weighted sequences, the variability of CSA was partly scanner dependent probably due to differences in scanner geometry, coil design, and details of the MRI parameter settings.Conclusion: For CSA quantification, dedicated isotropic SC MRI should be acquired, which yielded best repeatability in the entire cervical cord. In the upper part of the cervical cord, use of brain MRI scans entailed only a minor loss of CSA repeatability compared to SC MRI. Due to systematic differences between scanners and the CSA quantification software, both should be kept constant within a study. The MRI dataset of this study is available publicly to test new analysis approaches.

Atlas-Based Quantification of DTI Measures in a Typically Developing Pediatric Spinal Cord.

Multi-parametric MRI, provides a variety of biomarkers sensitive to white matter integrity, However, spinal cord MRI data in pediatrics is rare compared to adults. The purpose of this work was 3-fold: 1) to develop a processing pipeline for atlas-based generation of the typically developing pediatric spinal cord WM tracts, 2) to derive atlas-based normative values of the DTI indices for various WM pathways, and 3) to investigate age-related changes in the obtained normative DTI indices along the extracted tracts. DTI scans of 30 typically developing subjects (age range, 6-16 years) were acquired on a 3T MR imaging scanner. The data were registered to the PAM50 template in the Spinal Cord Toolbox. Next, the DTI indices for various WM regions were extracted at a single section centered at the C3 vertebral body in all the 30 subjects. Finally, an ANOVA test was performed to examine the effects of the following: 1) laterality, 2) functionality, and 3) age, with DTI-derived indices in 34 extracted WM regions. A postprocessing pipeline was developed and validated to delineate pediatric spinal cord WM tracts. The results of ANOVA on fractional anisotropy values showed no effect for laterality (P = .72) but an effect for functionality (P < .001) when comparing the 30 primary WM labels. There was a significant (P < .05) effect of age and maturity of the left spinothalamic tract on mean diffusivity, radial diffusivity, and axial diffusivity values. The proposed automated pipeline in this study incorporates unique postprocessing steps followed by template registration and quantification of DTI metrics using atlas-based regions. This method eliminates the need for manual ROI analysis of WM tracts and, therefore, increases the accuracy and speed of the measurements.

Quantitative Magnetic Resonance Imaging Analysis of Early Markers of Upper Cervical Cord Atrophy in Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorder.

Purpose To quantitatively analyze the C2/C3 segments of the spinal cord on magnetic resonance imaging (MRI) scans of neuromyelitis optica spectrum disorder (NMOSD) and relapsing-remitting multiple sclerosis (RRMS) patients in their first five years of the disease and to investigate the intergroup differences regarding markers of spinal cord atrophy and their correlations with expanded disability status scale (EDSS). Materials and Methods Twenty NMOSD patients and twenty RRMS patients, within their first five years of the disease, were enrolled in this cross-sectional study. All patients underwent spinal cord MR imaging using 1.5 Tesla systems, and C2/C3 portions of the spinal cord were segmented in the obtained scans. C2/C3 anteroposterior diameter (C2/C3 SC-APD), transversal diameter (C2/C3 SC-TD), and cross-sectional area (C2/C3 SC-CSA) were quantitatively measured using Spinal Cord Toolbox v.4.3. Results Three NMOSD patients were seropositive for anti-AQP4 IgG. The mean C2/C3 SC-CSA in NMOSD patients was significantly lower than in RRMS patients. NMOSD patients had significantly lower C2/C3 SC-TDs than RRMS patients. With the three anti-AQP4+ patients excluded from the analysis, C2/C3 SC-TD was negatively correlated with EDSS. Conclusion In the early stages of the disease, quantitative evaluation of C2/C3 spinal cord parameters, including cross-sectional area and transversal diameter in NMOSD patients, appears to be of potential diagnostic and prognostic value.

Spinal Cord Morphology in Degenerative Cervical Myelopathy Patients; Assessing Key Morphological Characteristics Using Machine Vision Tools.

Despite Degenerative Cervical Myelopathy (DCM) being the most common form of spinal cord injury, effective methods to evaluate patients for its presence and severity are only starting to appear. Evaluation of patient images, while fast, is often unreliable; the pathology of DCM is complex, and clinicians often have difficulty predicting patient prognosis. Automated tools, such as the Spinal Cord Toolbox (SCT), show promise, but remain in the early stages of development. To evaluate the current state of an SCT automated process, we applied it to MR imaging records from 328 DCM patients, using the modified Japanese Orthopedic Associate scale as a measure of DCM severity. We found that the metrics extracted from these automated methods are insufficient to reliably predict disease severity. Such automated processes showed potential, however, by highlighting trends and barriers which future analyses could, with time, overcome. This, paired with findings from other studies with similar processes, suggests that additional non-imaging metrics could be added to achieve diagnostically relevant predictions. Although modeling techniques such as these are still in their infancy, future models of DCM severity could greatly improve automated clinical diagnosis, communications with patients, and patient outcomes.

Spinal Cord Gray and White Matter Damage in Different Hereditary Spastic Paraplegia Subtypes.

Spinal cord damage is a hallmark of hereditary spastic paraplegias, but it is still not clear whether specific subtypes of the disease have distinctive patterns of spinal cord gray (GM) and white (WM) matter involvement. We compared cervical cross-sectional GM and WM areas in patients with distinct hereditary spastic paraplegia subtypes. We also assessed whether these metrics correlated with clinical parameters. We analyzed 37 patients (17 men; mean age, 47.3 [SD, 16.5] years) and 21 healthy controls (7 men; mean age, 42.3 [SD, 13.2] years). There were 7 patients with spastic paraplegia type 3A (SPG3A), 12 with SPG4, 10 with SPG7, and 8 with SPG11. Image acquisition was performed on a 3T MR imaging scanner, and T2*-weighted 2D images were assessed by the Spinal Cord Toolbox. Statistical analyses were performed in SPSS using nonparametric tests and false discovery rate-corrected P values < .05. The mean disease duration for the hereditary spastic paraplegia group was 22.4 [SD, 13.8] years and the mean Spastic Paraplegia Rating Scale score was 22.8 [SD, 11.0]. We failed to identify spinal cord atrophy in SPG3A and SPG7. In contrast, we found abnormalities in patients with SPG4 and SPG11. Both subtypes had spinal cord GM and WM atrophy. SPG4 showed a strong inverse correlation between GM area and disease duration (ρ = -0.903, P < .001). Cervical spinal cord atrophy is found in some but not all hereditary spastic paraplegia subtypes. Spinal cord damage in SPG4 and 11 involves both GM and WM.