Gray and white matter delineation in the human spinal cord using diffusion tensor imaging and fuzzy logic

Detection of spinal long fiber tract degeneration in HSP: Improved diffusion tensor imaging

Spinal diffusion tensor imaging (sDTI) is still a challenging technique for selectively evaluating anatomical areas like the pyramidal tracts (PT), dorsal columns (DC), and anterior horns (AH) in clinical routine and for reliably quantifying white matter anisotropy and diffusivity. In neurodegenerative diseases, the value of sDTI is promising but not yet well understood. The objective of this prospective, single-center study was to evaluate the long fiber tract degeneration within the spinal cord in normal aging (n = 125) and to prove its applicability in pathologic conditions as in patients with molecular genetically confirmed hereditary spastic paraplegias (HSP; n = 40), a prototypical disease of the first motor neuron and in some genetic variants with affection of the dorsal columns. An optimized monopolar Stejskal-Tanner sequence for high-resolution, axial sDTI of the cervical spinal cord at 3.0 T with advanced standardized evaluation methods was developed for a robust DTI value estimation of PT, DC, and AH in both groups. After sDTI measurement at C2, an automatic motion correction and an advanced semi-automatic ROI-based, standardized evaluation of white matter anisotropy and diffusivity was performed to obtain regional diffusivity measures for PT, DC, and AH. Reliable and stable sDTI values were acquired in a healthy population without significant decline between age 20 and 65. Reference values for PT, DC, and AH for fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) were established. In HSP patients, the decline of the long spinal fiber tracts could be demonstrated by diffusivity abnormalities in the pyramidal tracts with significantly reduced PT_FA (p < 0.001), elevated PT_RD (p = 0.002) and reduced PT_MD (p = 0.003) compared to healthy controls. Furthermore, FA was significantly reduced in DC_FA (p < 0.001) with no differences in AH. In a genetically homogeneous subgroup of SPG4 patients (n = 12) with affection of the dorsal columns, DC_RD significantly correlated with the overall disease severity as measured by the Spastic Paraplegia Rating Scale (SPRS) (r = - 0.713, p = 0.009). With the most extensive sDTI study in vivo to date, we showed that axial sDTI combined with motion correction and advanced data post-processing strategies enables robust measurements and is ready to use, allowing recognition and quantification of disease- and age-related changes of the PT, DC, and AH. These results may also encourage the usage of sDTI in other neurodegenerative diseases with spinal cord involvement to explore its capability as selective biomarkers.

Mapping the rest of the human connectome: Atlasing the spinal cord and peripheral nervous system

The emergence of diffusion, structural, and functional neuroimaging methods has enabled major multi-site efforts to map the human connectome, which has heretofore been defined as containing all neural connections in the central nervous system (CNS). However, these efforts are not structured to examine the richness and complexity of the peripheral nervous system (PNS), which arguably forms the (neglected) rest of the connectome. Despite increasing interest in an atlas of the spinal cord (SC) and PNS which is simultaneously stereotactic, interactive, electronically dissectible, scalable, population-based and deformable, little attention has thus far been devoted to this task of critical importance. Nevertheless, the atlasing of these complete neural structures is essential for neurosurgical planning, neurological localization, and for mapping those components of the human connectome located outside of the CNS. Here we recommend a modification to the definition of the human connectome to include the SC and PNS, and argue for the creation of an inclusive atlas to complement current efforts to map the brain's human connectome, to enhance clinical education, and to assist progress in neuroscience research. In addition to providing a critical overview of existing neuroimaging techniques, image processing methodologies and algorithmic advances which can be combined for the creation of a full connectome atlas, we outline a blueprint for ultimately mapping the entire human nervous system and, thereby, for filling a critical gap in our scientific knowledge of neural connectivity.

Diffusion tensor imaging of spinal microstructure in healthy adults: improved resolution with the readout segmentation of long variable echo-trains

Diffusion tensor imaging plays an important role in the accurate diagnosis and prognosis of spinal cord diseases. However, because of technical limitations, the imaging sequences used in this technique cannot reveal the fine structure of the spinal cord with precision. We used the readout segmentation of long variable echo-trains (RESOLVE) sequence in this cross-sectional study of 45 healthy volunteers aged 20 to 63 years. We found that the RESOLVE sequence significantly increased the resolution of the diffusion images and improved the median signal-to-noise ratio of the middle (C_4-6) and lower (C₇-T₁) cervical segments to the level of the upper cervical segment. In addition, the values of fractional anisotropy and radial diffusivity were significantly higher in white matter than in gray matter. Our study verified that the RESOLVE sequence could improve resolution of diffusion tensor imaging in clinical applications and provide accurate baseline data for the diagnosis and treatment of cervical spinal cord diseases.

Fully-integrated framework for the segmentation and registration of the spinal cord white and gray matter

The spinal cord white and gray matter can be affected by various pathologies such as multiple sclerosis, amyotrophic lateral sclerosis or trauma. Being able to precisely segment the white and gray matter could help with MR image analysis and hence be useful in further understanding these pathologies, and helping with diagnosis/prognosis and drug development. Up to date, white/gray matter segmentation has mostly been done manually, which is time consuming, induces a bias related to the rater and prevents large-scale multi-center studies. Recently, few methods have been proposed to automatically segment the spinal cord white and gray matter. However, no single method exists that combines the following criteria: (i) fully automatic, (ii) works on various MRI contrasts, (iii) robust towards pathology and (iv) freely available and open source. In this study we propose a multi-atlas based method for the segmentation of the spinal cord white and gray matter that addresses the previous limitations. Moreover, to study the spinal cord morphology, atlas-based approaches are increasingly used. These approaches rely on the registration of a spinal cord template to an MR image, however the registration usually doesn't take into account the spinal cord internal structure and thus lacks accuracy. In this study, we propose a new template registration framework that integrates the white and gray matter segmentation to account for the specific gray matter shape of each individual subject. Validation of segmentation was performed in 24 healthy subjects using T₂^*-weighted images, in 8 healthy subjects using diffusion weighted images (exhibiting inverted white-to-gray matter contrast compared to T₂*-weighted), and in 5 patients with spinal cord injury. The template registration was validated in 24 subjects using T₂*-weighted data. Results of automatic segmentation on T₂*-weighted images was in close correspondence with the manual segmentation (Dice coefficient in the white/gray matter of 0.91/0.71 respectively). Similarly, good results were obtained in data with inverted contrast (diffusion-weighted image) and in patients. When compared to the classical template registration framework, the proposed framework that accounts for gray matter shape significantly improved the quality of the registration (comparing Dice coefficient in gray matter: p=9.5×10^-6). While further validation is needed to show the benefits of the new registration framework in large cohorts and in a variety of patients, this study provides a fully-integrated tool for quantitative assessment of white/gray matter morphometry and template-based analysis. All the proposed methods are implemented in the Spinal Cord Toolbox (SCT), an open-source software for processing spinal cord multi-parametric MRI data.

Segmentation of the human spinal cord

Segmenting the spinal cord contour is a necessary step for quantifying spinal cord atrophy in various diseases. Delineating gray matter (GM) and white matter (WM) is also useful for quantifying GM atrophy or for extracting multiparametric MRI metrics into specific WM tracts. Spinal cord segmentation in clinical research is not as developed as brain segmentation, however with the substantial improvement of MR sequences adapted to spinal cord MR investigations, the field of spinal cord MR segmentation has advanced greatly within the last decade. Segmentation techniques with variable accuracy and degree of complexity have been developed and reported in the literature. In this paper, we review some of the existing methods for cord and WM/GM segmentation, including intensity-based, surface-based, and image-based methods. We also provide recommendations for validating spinal cord segmentation techniques, as it is important to understand the intrinsic characteristics of the methods and to evaluate their performance and limitations. Lastly, we illustrate some applications in the healthy and pathological spinal cord. One conclusion of this review is that robust and automatic segmentation is clinically relevant, as it would allow for longitudinal and group studies free from user bias as well as reproducible multicentric studies in large populations, thereby helping to further our understanding of the spinal cord pathophysiology and to develop new criteria for early detection of subclinical evolution for prognosis prediction and for patient management. Another conclusion is that at the present time, no single method adequately segments the cord and its substructure in all the cases encountered (abnormal intensities, loss of contrast, deformation of the cord, etc.). A combination of different approaches is thus advised for future developments, along with the introduction of probabilistic shape models. Maturation of standardized frameworks, multiplatform availability, inclusion in large suite and data sharing would also ultimately benefit to the community.

A reliable spatially normalized template of the human spinal cord--Applications to automated white matter/gray matter segmentation and tensor-based morphometry (TBM) mapping of gray matter alterations occurring with age

Recently, a T2*-weighted template and probabilistic atlas of the white and gray matter (WM, GM) of the spinal cord (SC) have been reported. Such template can be used as tissue-priors for automated WM/GM segmentation but can also provide a common reference and normalized space for group studies. Here, a new template has been created (AMU40), and accuracy of automatic template-based WM/GM segmentation was quantified. The feasibility of tensor-based morphometry (TBM) for studying voxel-wise morphological differences of SC between young and elderly healthy volunteers was also investigated. Sixty-five healthy subjects were divided into young (n=40, age<40years old, mean age 28±5years old) and elderly (n=25, age>50years old, mean age 57±5years old) groups and scanned at 3T using an axial high-resolution T2*-weighted sequence. Inhomogeneity correction and affine intensity normalization of the SC and cerebrospinal fluid (CSF) signal intensities across slices were performed prior to both construction of the AMU40 template and WM/GM template-based segmentation. The segmentation was achieved using non-linear spatial normalization of T2*-w MR images to the AMU40 template. Validation of WM/GM segmentations was performed with a leave-one-out procedure by calculating DICE similarity coefficients between manual and automated WM/GM masks. SC morphological differences between young and elderly healthy volunteers were assessed using the same non-linear spatial normalization of the subjects' MRI to a common template, derivation of the Jacobian determinant maps from the warping fields, and a TBM analysis. Results demonstrated robust WM/GM automated segmentation, with mean DICE values greater than 0.8. Concerning the TBM analysis, an anterior GM atrophy was highlighted in elderly volunteers, demonstrating thereby, for the first time, the feasibility of studying local structural alterations in the SC using tensor-based morphometry. This holds great promise for studies of morphological impairment occurring in several central nervous system pathologies.

Diffusion tensor imaging predicts functional impairment in mild-to-moderate cervical spondylotic myelopathy

BACKGROUND CONTEXT

Magnetic resonance imaging (MRI) is the standard imaging modality for the assessment of cervical spinal cord; however, MRI assessment of the spinal cord in cervical spondylotic myelopathy patients has not demonstrated a consistent association with neurologic function or outcome after surgical or medical intervention. Thus, there is a need for sensitive imaging biomarkers that can predict functional impairment in patients with advanced cervical spondylosis.

PURPOSE

To implement diffusion tensor imaging (DTI) as an imaging biomarker for microstructural integrity and functional impairment in patients with cervical spondylosis.

STUDY DESIGN

Nonrandomized, single institution study.

PATIENT SAMPLE

Forty-eight cervical spondylosis patients with or without spinal cord signal change underwent DTI of the spinal cord along with functional assessment.

OUTCOME MEASURES

Functional measures of neurologic function via modified Japanese Orthopedic Association (mJOA) score.

METHODS

A zoomed-echoplanar imaging technique and two-dimensional spatially selective radiofrequency excitation pulse were used for DTI measurement. Fractional anisotropy (FA), mean diffusivity (MD), radial and axial diffusion (AD) coefficient, AD anisotropy, ψ, defined as AD-MD, and the standard deviation (SD) of primary eigenvector orientation were evaluated at the site of compression.

RESULTS

Results suggest average FA, transverse apparent diffusion coefficient, ψ, and SD of primary eigenvector orientation at the spinal level of highest compression were linearly correlated with mJOA score. Receiver-operator characteristic analysis suggested FA and ψ could identify stenosis patients with mild-to-moderate symptoms with a relatively high sensitivity and specificity.

CONCLUSIONS

The results of this study support the potential use of DTI as a biomarker for predicting functional impairment in patients with cervical spondylosis.

Framework for integrated MRI average of the spinal cord white and gray matter: the MNI-Poly-AMU template

The field of spinal cord MRI is lacking a common template, as existing for the brain, which would allow extraction of multi-parametric data (diffusion-weighted, magnetization transfer, etc.) without user bias, thereby facilitating group analysis and multi-center studies. This paper describes a framework to produce an unbiased average anatomical template of the human spinal cord. The template was created by co-registering T2-weighted images (N = 16 healthy volunteers) using a series of pre-processing steps followed by non-linear registration. A white and gray matter probabilistic template was then merged to the average anatomical template, yielding the MNI-Poly-AMU template, which currently covers vertebral levels C1 to T6. New subjects can be registered to the template using a dedicated image processing pipeline. Validation was conducted on 16 additional subjects by comparing an automatic template-based segmentation and manual segmentation, yielding a median Dice coefficient of 0.89. The registration pipeline is rapid (~15 min), automatic after one C2/C3 landmark manual identification, and robust, thereby reducing subjective variability and bias associated with manual segmentation. The template can notably be used for measurements of spinal cord cross-sectional area, voxel-based morphometry, identification of anatomical features (e.g., vertebral levels, white and gray matter location) and unbiased extraction of multi-parametric data.

Advances in MR imaging for cervical spondylotic myelopathy

PURPOSE

To outline the pathogenesis of cervical spondylotic myelopathy (CSM), the correlative abnormalities observed on standard magnetic resonance imaging (MRI), the biological implications and current status of diffusion tensor imaging (DTI), and MR spectroscopy (MRS) as clinical tools, and future directions of MR technology in the management of CSM patients.

METHODS

A systematic review of the pathogenesis and current state-of-the-art in MR imaging technology for CSM was performed.

RESULTS

CSM is caused by progressive, degenerative, vertebral column abnormalities that result in spinal cord damage related to both primary mechanical and secondary biological injuries. The T2 signal change on conventional MRI is most commonly associated with neurological deficits, but tends not to be a sensitive predictor of recovery of function. DTI and MRS show altered microstructure and biochemistry that reflect patient-specific pathogenesis.

CONCLUSION

Advanced imaging techniques, including DTI and MRS, show higher sensitivity to microstructural and biochemical changes within the cord, and may aid in management of CSM patients.

Improved in vivo diffusion tensor imaging of human cervical spinal cord

We describe a cardiac gated high in-plane resolution axial human cervical spinal cord diffusion tensor imaging (DTI) protocol. Multiple steps were taken to optimize both image acquisition and image processing. The former includes slice-by-slice cardiac triggering and individually tiltable slices. The latter includes (i) iterative 2D retrospective motion correction, (ii) image intensity outlier detection to minimize the influence of physiological noise, (iii) a non-linear DTI estimation procedure incorporating non-negative eigenvalue priors, and (iv) tract-specific region-of-interest (ROI) identification based on an objective geometry reference. Using these strategies in combination, radial diffusivity (λ(⊥)) was reproducibly measured in white matter (WM) tracts (adjusted mean [95% confidence interval]=0.25 [0.22, 0.29] μm(2)/ms), lower than previously reported λ(⊥) values in the in vivo human spinal cord DTI literature. Radial diffusivity and fractional anisotropy (FA) measured in WM varied from rostral to caudal as did mean translational motion, likely reflecting respiratory motion effect. Given the considerable sensitivity of DTI measurements to motion artifact, we believe outlier detection is indispensable in spinal cord diffusion imaging. We also recommend using a mixed-effects model to account for systematic measurement bias depending on cord segment.

Automatic segmentation of rodent spinal cord diffusion MR images

MRI, is a key tool for noninvasive spinal cord lesion analysis; however, accurate, quantitative methods for this analysis are lacking. A new, multistep, multidimensional approach, utilizing the classification expectation maximization algorithm, is proposed for MRI segmentation of spinal cord tissues. Diffusion tensor imaging is used to generate multiple images of each spinal slice, with different diffusion direction weightings. The maximum likelihood tissue classifications are then jointly estimated to produce a binary classification image, corresponding to voxels containing either spinal cord or background. Edge detection is employed to find a nonparametric curve encapsulating the entire spinal cord. The algorithm is evaluated using data from in vivo diffusion tensor imaging of control and injured mouse spinal cords. The algorithm is shown to remain accurate for whole spinal cord, white matter, and hemorrhage segmentation in the presence of significant injury. The results of the method are shown to be at least on par with expert manual segmentation.

Demyelination and degeneration in the injured human spinal cord detected with diffusion and magnetization transfer MRI

Characterizing demyelination/degeneration of spinal pathways in traumatic spinal cord injured (SCI) patients is crucial for assessing the prognosis of functional rehabilitation. Novel techniques based on diffusion-weighted (DW) magnetic resonance imaging (MRI) and magnetization transfer (MT) imaging provide sensitive and specific markers of white matter pathology. In this paper we combined for the first time high angular resolution diffusion-weighted imaging (HARDI), MT imaging and atrophy measurements to evaluate the cervical spinal cord of fourteen SCI patients and age-matched controls. We used high in-plane resolution to delineate dorsal and ventrolateral pathways. Significant differences were detected between patients and controls in the normal-appearing white matter for fractional anisotropy (FA, p<0.0001), axial diffusivity (p<0.05), radial diffusivity (p<0.05), generalized fractional anisotropy (GFA, p<0.0001), magnetization transfer ratio (MTR, p<0.0001) and cord area (p<0.05). No significant difference was detected in mean diffusivity (p=0.41), T1-weighted (p=0.76) and T2-weighted (p=0.09) signals. MRI metrics were remarkably well correlated with clinical disability (Pearson's correlations, FA: p<0.01, GFA: p<0.01, radial diffusivity: p=0.01, MTR: p=0.04 and atrophy: p<0.01). Stepwise linear regressions showed that measures of MTR in the dorsal spinal cord predicted the sensory disability whereas measures of MTR in the ventro-lateral spinal cord predicted the motor disability (ASIA score). However, diffusion metrics were not specific to the sensorimotor scores. Due to the specificity of axial and radial diffusivity and MT measurements, results suggest the detection of demyelination and degeneration in SCI patients. Combining HARDI with MT imaging is a promising approach to gain specificity in characterizing spinal cord pathways in traumatic injury.

Diffusion tensor MR imaging in chronic spinal cord injury

BACKGROUND AND PURPOSE

Diffusion tensor MR imaging is emerging as an important tool for displaying anatomic changes in the brain after injury or disease but has been less widely applied to disorders of the spinal cord. The aim of this study was to characterize the diffusion properties of the entire human spinal cord in vivo during the chronic stages of spinal cord injury (SCI). These data provide insight into the structural changes that occur as a result of long-term recovery from spinal trauma.

MATERIALS AND METHODS

Thirteen neurologically intact subjects and 10 subjects with chronic SCI (>4 years postinjury) were enrolled in this study. A single-shot twice-refocused spin-echo diffusion-weighted echo-planar imaging pulse sequence was used to obtain axial images throughout the entire spinal cord (C1-L1) in <60 minutes.

RESULTS

Despite heterogeneity in SCI lesion severity and location, diffusion characteristics of the chronic lesion were significantly elevated compared with those of uninjured controls. Fractional anisotropy was significantly lower at the chronic lesion and appeared dependent on the completeness of the injury. Conversely, mean diffusivity measurements in the upper cervical spinal cord in subjects with SCI were significantly lower than those in controls. These trends suggest that the entire neuraxis may be affected by long-term recovery from spinal trauma.

CONCLUSION

These results suggest that diffusion tensor imaging may be useful in the assessment of SCI recovery.

Diffusion tensor MR imaging of the neurologically intact human spinal cord

BACKGROUND AND PURPOSE

The aim of this study was to characterize the diffusion properties of the entire human spinal cord in vivo. These data are essential for comparisons to pathologic conditions as well as for comparisons of different pulse sequence design parameters aimed to reduce scan time and more accurately determine diffusion coefficients.

MATERIALS AND METHODS

A total of 13 neurologically intact subjects were enrolled in this study. A single-shot, twice-refocused, spin-echo, diffusion-weighted, echo-planar imaging (EPI) pulse sequence was used to obtain axial images throughout the entire spinal cord (C1-L1) in 45 minutes.

RESULTS

Diffusion images indicated slight geometric distortions; however, gray and white matter contrast was observed. All measurements varied across the length of the cord. Whole cord diffusion coefficients averaged 0.5-1.3 x 10(-3) mm(2)/s depending on orientation, mean diffusivity (MD) averaged 0.83 +/- 0.06 x 10(-3) mm(2)/s, fractional anisotropy (FA) averaged 0.49 +/- 0.05, and volume ratio (VR) averaged 0.73 +/- 0.05.

CONCLUSION

This study provided normative diffusion values for the entire spinal cord for use in comparisons with pathologic conditions as well as improvements in pulse sequence design.

Morphology and morphometry of human chronic spinal cord injury using diffusion tensor imaging and fuzzy logic

Diffusion tensor imaging (DTI) was performed on regions rostral to the injury site in four human subjects with chronic spinal cord injury (SCI) and equivalent regions in four neurologically intact subjects. Apparent diffusion coefficients were measured and compared between subjects. A fuzzy logic tissue classification algorithm was used to segment gray and white matter regions for morphometric analysis, including comparisons of cross-sectional areas of gray and white matter along with frontal and sagittal diameters. Results indicated a general decrease in both longitudinal and transverse diffusivity in the upper cervical segments of subjects with chronic SCI. Further, a decrease in the cross-sectional area of the entire spinal cord was observed in subjects with SCI, consistent with severe atrophy of the spinal cord. These observations have implications in tracking the progression of SCI from the acute to the chronic stages. We conclude that DTI with fuzzy logic tissue classification has potential for monitoring morphological changes in the spinal cord in people with SCI.