Eveline Huber1, Gergely David1, Alan J Thompson1, Nikolaus Weiskopf1, Siawoosh Mohammadi1, Patrick Freund2. 1. From the Spinal Cord Injury Center (E.H., G.D., P.F.), Balgrist University Hospital, Zurich, Switzerland; Department of Brain Repair and Rehabilitation (A.J.T., P.F.) and Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, University College London, UK; Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Germany. 2. From the Spinal Cord Injury Center (E.H., G.D., P.F.), Balgrist University Hospital, Zurich, Switzerland; Department of Brain Repair and Rehabilitation (A.J.T., P.F.) and Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, University College London, UK; Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Germany. patrick.freund@balgrist.ch.
Abstract
OBJECTIVE: To investigate whether gray matter pathology above the level of injury, alongside white matter changes, also contributes to sensorimotor impairments after spinal cord injury. METHODS: A 3T MRI protocol was acquired in 17 tetraplegic patients and 21 controls. A sagittal T2-weighted sequence was used to characterize lesion severity. At the C2-3 level, a high-resolution T2*-weighted sequence was used to assess cross-sectional areas of gray and white matter, including their subcompartments; a diffusion-weighted sequence was used to compute voxel-based diffusion indices. Regression models determined associations between lesion severity and tissue-specific neurodegeneration and associations between the latter with neurophysiologic and clinical outcome. RESULTS: Neurodegeneration was evident within the dorsal and ventral horns and white matter above the level of injury. Tract-specific neurodegeneration was associated with prolonged conduction of appropriate electrophysiologic recordings. Dorsal horn atrophy was associated with sensory outcome, while ventral horn atrophy was associated with motor outcome. White matter integrity of dorsal columns and corticospinal tracts was associated with daily-life independence. CONCLUSION: Our results suggest that, next to anterograde and retrograde degeneration of white matter tracts, neuronal circuits within the spinal cord far above the level of injury undergo transsynaptic neurodegeneration, resulting in specific gray matter changes. Such improved understanding of tissue-specific cord pathology offers potential biomarkers with more efficient targeting and monitoring of neuroregenerative (i.e., white matter) and neuroprotective (i.e., gray matter) agents.
OBJECTIVE: To investigate whether gray matter pathology above the level of injury, alongside white matter changes, also contributes to sensorimotor impairments after spinal cord injury. METHODS: A 3T MRI protocol was acquired in 17 tetraplegic patients and 21 controls. A sagittal T2-weighted sequence was used to characterize lesion severity. At the C2-3 level, a high-resolution T2*-weighted sequence was used to assess cross-sectional areas of gray and white matter, including their subcompartments; a diffusion-weighted sequence was used to compute voxel-based diffusion indices. Regression models determined associations between lesion severity and tissue-specific neurodegeneration and associations between the latter with neurophysiologic and clinical outcome. RESULTS: Neurodegeneration was evident within the dorsal and ventral horns and white matter above the level of injury. Tract-specific neurodegeneration was associated with prolonged conduction of appropriate electrophysiologic recordings. Dorsal horn atrophy was associated with sensory outcome, while ventral horn atrophy was associated with motor outcome. White matter integrity of dorsal columns and corticospinal tracts was associated with daily-life independence. CONCLUSION: Our results suggest that, next to anterograde and retrograde degeneration of white matter tracts, neuronal circuits within the spinal cord far above the level of injury undergo transsynaptic neurodegeneration, resulting in specific gray matter changes. Such improved understanding of tissue-specific cord pathology offers potential biomarkers with more efficient targeting and monitoring of neuroregenerative (i.e., white matter) and neuroprotective (i.e., gray matter) agents.
Spinal cord injury (SCI) usually leads to sensorimotor dysfunction resulting from damage
at the level of injury. However, a complex cascade of secondary neurodegenerative
processes occur across the spinal cord and brain.[1] In chronic SCI, cervical cord atrophy of up to 30% has been
reported above the level of injury; its magnitude relates to the degree of clinical
impairment.[2] Recent
improvements in diffusion-weighted imaging and anatomic sequences with higher in-plane
resolution,[3] combined with
advanced postprocessing techniques,[4,5] now allow the assessment of gray and
white matter changes in the cervical spinal cord occurring after SCI.Although white matter pathology within the spinal cord contributes to sensorimotor
impairments, the functional effects of gray matter pathology above the level of injury
are uncertain. Improved understanding of tissue-specific cord pathology may allow more
efficient targeting and monitoring of neuroregenerative and neuroprotective agents. This
study therefore addresses to what extent cord atrophy above the level of injury is
driven by pathophysiologic processes occurring in gray and white matter, whether lesion
severity is associated with the magnitude of neurodegeneration above the level of
injury, and whether the tissue-specific neurodegeneration is associated with
neurophysiologic and clinical outcome.Using structural and diffusion MRI data, we assessed tissue-specific cord pathology above
the level of injury in patients with chronic SCI compared to healthy controls. These
measures included the assessment of dorsal horn area (DHA) and ventral horn area
(VHA),[6] diffusivity changes
within the major spinal pathways, and associations between lesion severity,[7] tissue-specific pathology, and
neurophysiologic changes.
Methods
Standard protocol approvals, registrations, and patient consents
Our study protocol was designed in accordance with the Declaration of Helsinki
and was approved by the local ethics committee of Zurich (KEK-ZH-Nr. 2012-0343,
PB_2016-00623). All participants gave their written informed consent before
participation.
Participants
We recruited 17 patients with SCI (mean age 48.7 ± 14.1 years, 3 female
patients) between November 2014 and May 2016 who were preciously admitted to the
University Hospital Balgrist (Zurich, Switzerland). Twenty-one healthy controls
(mean age 41.7 ± 11.3 years, 7 female controls) from the local neighborhood
served as a control dataset that was acquired and used in a previous
study.[8]Inclusion criteria for patients with SCI were traumatic cervical SCI, no other
neurologic or mental disorders affecting clinical outcome, age between 18 and 70
years, MRI compatible, and no pregnancy.
Clinical assessments
All patients were examined with comprehensive clinical protocols to assess
neurologic and functional impairment. These included the International Standards
for Neurological Classification of Spinal Cord Injury protocol for motor,
light-touch, and pinprick score and completeness of injury[9]; the Spinal Cord Independence
Measure (SCIM) to measure daily life independence[10]; the Graded Redefined Assessment of Strength,
Sensibility and Prehension (GRASSP) for assessing upper limb function[11]; and the Walking Index for
Spinal Cord Injury (WISCI).[12]
All patients completed the full protocol, except GRASSP score was not available
for 1 patient.
Neurophysiologic assessments
Contact heat evoked potentials (CHEPs) and somatosensory evoked potentials
(SSEPs) were acquired bilaterally in patients at the dermatomes C4, C6, and C8
to measure the integrity of the spinothalamic tract (i.e., CHEPs) and the dorsal
column (i.e., SSEPs). For the acquisition of CHEPs[13] and SSEPs,[14] the same protocols were applied as previously
described.
Contact heat evoked potentials
A contact heat stimulator (PATHWAY Pain & Sensory Evaluation System, Medoc,
Ramat Yishay, Israel) was used to deliver contact heat stimuli from a baseline
temperature of 35°C to a peak temperature of 52°C with a heating rate
of 70°C/s and a cooling rate of 40°C/s. For each dermatome, we first
assessed heat perception and pain thresholds within 2 consecutive trials. For
the CHEPs recording, scalp recording sites were prepared with Nuprep (D.O.
Weaver & Co, Aurora, CO) and alcohol. Three 9-mm Ag/AgCl surface disk
electrodes were positioned according to the international 10-20 system with the
active electrode at the Cz position and referenced to linked earlobes
(A1–A2); impedances were kept <5 kΩ. Ten to 15 contact heat
stimuli were applied (interstimulus interval 8–12 seconds). Two seconds
after each stimulus, an audio cue appeared, and patients rated their perceived
intensity according to a numeric rating scale. All signals were sampled from 100
milliseconds before the trigger to 1,500 milliseconds after the trigger at a
sampling rate of 2,000 Hz with a preamplifier (20,000× bandpass filter
= 0.25–300 Hz; ALEA Solutions, Switzerland). Data were recorded in a
LabView-based program (V1.43 CHEP; ALEA Solutions, Zurich, Switzerland) with a
100-millisecond period before the trigger and 1-second posttrigger period. Raw
data were bandpass filtered from 0.5 to 30 Hz.
Somatosensory evoked potentials
For dermatomal SSEPs, Key Point (Medtronic, Mississauga, ON, Canada) was used to
record and deliver electric stimulation of 3 Hz. Stimuli were elicited by single
0.2-millisecond, repetitive, square-wave electric stimulation. We first assessed
electric perception and pain thresholds for each dermatome (not exceeding 40 mA)
within 2 consecutive trials. For the recording of SSEPs, surface gel electrodes
(10 mm) were used on each dermatome after the skin was prepared with Nuprep
(D.O. Weaver & Co) and alcohol. Disposable needle electrodes (Spes Medica,
Srl, Genova, Italy) were positioned according to the international 10-20 system
with the active electrode positioned at the contralateral side for the
stimulated dermatome (C3-4) referenced to Fz; impedances were kept <5
kΩ. The stimulation intensity was individually set as 3-fold electric
perception threshold. Averages of 2 traces of 300 cortical responses were
obtained for each dermatome. Raw data were bandpass filtered from 2 to 2,000
Hz.
Neurophysiologic classification
We determined amplitudes and latencies of each dermatome for each patient after
averaging all single-trial waveforms for CHEPs (i.e., N2P2, N2, P2) and SSEPs
(i.e., N1P1, N1, P1).Furthermore, CHEPs and SSEPs were classified as normal (onset latency ≤2
SDs from control dermatome recording), pathologic (onset latency >2 SDs
from control dermatome recording), or absent (not recordable).[14] The CHEPs protocol was
acquired fully in 14 patients and partially in 1 patient. For SSEPs, 12 patients
received the full protocol and 2 patients participated in part of the
protocol.
Image acquisition
All imaging was performed on a clinical 3T SkyraFit scanner (Siemens
Healthcare, Erlangen, Germany) equipped with a 16-channel radiofrequency
receive-only head and neck coil and a radiofrequency body transmit coil. A stiff
neck (Laerdal Medicals, Stavanger, Norway) was used in all participants to
minimize motion artifacts. As a result of motion artifacts, 1 patient was
excluded from macrostructural analysis, and 3 patients had to be excluded from
microstructural analysis.At the lesion epicenter, a sagittal T1-weighted (repetition time 600
milliseconds, echo time 9.9 milliseconds, flip angle 150°, in-plane
resolution 0.57 × 0.57 mm, slice thickness 3.3 mm), a sagittal T2-weighted
(repetition time 3,500 milliseconds, echo time 84 milliseconds, flip angle
160°, in-plane resolution 0.34 × 0.34 mm, slice thickness 2.75 mm),
and an axial T2-weighted image (repetition time 5,510 milliseconds, echo time 93
milliseconds, flip angle 150°, in-plane resolution 0.5 × 0.5 mm, slice
thickness 3.6 mm) were acquired to assess the lesion size.At the cervical cord above the level of injury (centered at C2-3), 5 volumes were
acquired with a T2*-weighted 3-dimensional multiecho gradient recall echo
sequence (multiple echo data image combination[15]) in the oblique axial plane (i.e.,
perpendicular to the cord) to assess gray and white matter atrophy. Each of the
5 volumes acquired consisted of 20 partitions with a resolution of 0.5 ×
0.5 mm2 (field of view 192 × 162 mm2, slice thickness
2.50 mm [10% gap], repetition time 44 milliseconds, echo time 19 milliseconds,
flip angle 11°, readout bandwidth 260 Hz/pixel). Each volume took 2.13
minutes to acquire. Application of zero-filling interpolation doubled the
nominal in-plane resolution (0.25 × 0.25 mm2).At the identical level, a high-resolution diffusion tensor imaging (DTI) dataset
was acquired with a cardiac-gated reduced-FOV single-shot spin-echo echo planar
imaging sequence with outer volume suppression[16] to assess microstructural changes of the whole
spinal cord. Four measurements of 6 b = 0 (T2-weighted) and 30 b = 500
s/mm2 volumes were acquired, resulting in 144 images per
participant and a nominal acquisition time of 6.17 minutes. The following
parameters were applied: repetition time of 350 milliseconds; echo time of 71
milliseconds; slice thickness of 5 mm (10% interslice gap); resolution of 0.76
× 0.76 mm2; FOV of 133 × 30 mm2; phase
oversampling of 50%; 5/8 partial-Fourier imaging in the phase-encoding
direction; cardiac trigger delay of 200 milliseconds; and minimal time between
triggers of 1,800 milliseconds. After acquisition, zero-filling interpolation
was used to double the in-plane resolution (0.38 × 0.38
mm2).
Image processing
Lesion segmentation
With the use of the Jim 6.0 software (Xinapse Systems, Aldwincle, UK), the
lesion was segmented on the midsagittal T2-weighted images, being visible as
a high-signal-intensity area within the spinal cord, as previously
described.[7] The
following parameters were quantified: midsagittal anterior-posterior lesion
width (equal to the maximal anterior-posterior width of the lesion),
midsagittal rostrocaudal lesion length (equal to the maximal caudocranial
extent of the lesion), total midsagittal lesion area, and midsagittal
thickness of midsagittal ventral and dorsal tissue bridges at the widest
point of the lesion, which was summed up to the total amount of midsagittal
tissue bridges.
Processing of high-resolution macrostructural data above the level of
injury
We used serial longitudinal registration[17] embedded within SPM12 to average the five
3-dimensional MEDIC volumes, accounting for intraparticipant motion. To
further increase the signal-to-noise ratio, the average volume was resampled
at a double slice thickness. We then used the Jim 6.0 software to measure
cross-sectional spinal cord area (SCA) of 3 slices. After the midpoint of
the spinal cord was marked manually in each slice, the SCA was calculated
automatically with the semiautomatic 3-dimensional active-surface
model.[18] Gray
matter area (GMA), dorsal column area (DCA), VHA (approximately lamina
VI–IX), and DHA (approximately lamina I–V) were extracted
manually.[6] White
matter area (WMA) was calculated by subtracting the GMA from the SCA. The
mean interobserver reliability and intraobserver reliability for these
measures were previously shown.[8,16]
Preprocessing and estimation of DTI data
All processing of the DTI data was carried out with a modified version of the
MatLab-based ACID toolbox optimized for the spinal cord. First, we reduced
the in-plane FOV to 24 × 24 mm2 to exclude much of the
non–spinal cord tissue in each participant. Then, DTI volumes were
slice-wise linearly registered with 3 df (translation in
the frequency- and phase-encoding direction, scaling in the phase-encoding
direction) to correct for intraparticipant motion and eddy-current
artifacts.[19] A
diffusion tensor was fitted by use of a robust tensor fitting algorithm that
accounts for outlier volumes due to motion and physiologic
artifacts.[20] The
following DTI index maps were extracted: fractional anisotropy (FA) and
mean, axial, and radial diffusivity (MD, AD, and RD).These DTI index maps were then spatially normalized to a self-constructed
mean diffusivity template residing in the spinal Montreal Neurological
Institute space.[21] To
further refine the accuracy of the registration, a manual slice-by-slice
registration (in-plane translation and scaling) was performed. Finally, all
DTI index maps were smoothed with a full width at half-maximum gaussian
kernel with 0.5 × 0.5 × 5 mm3.
Statistical analysis
Statistical analysis of all macrostructural MRI, neurophysiologic, and clinical
data was performed with Stata13 (StataCorp LP, College Station, TX). The mean
age was not statistically different between healthy controls and patients
(Mann-Whitney U test: z = −1.61,
p = 0.10). All images were visually inspected for
artifacts, and the analysis was conducted on 3 slices from each modality at the
same level.First, we assessed the morphometric differences in SCA, GMA, WMA, DCA, VHA, and
DHA between patients and healthy controls by means of analysis of covariance,
adjusted for age. For microstructural differences between patients and healthy
controls, we used SPM12 for voxel-based analysis of the different DTI indexes
(FA, MD, AD, RD) by means of analysis of covariance, adjusted for age. All
statistical parametric maps were initially thresholded with a cluster-defining
threshold of p < 0.01 (uncorrected) and clusters
surpassing a cluster threshold of p < 0.05 (family-wise
error corrected) are reported. Next, we used linear regression analysis to
investigate the relationship between changes at the lesion site (midsagittal
lesion area, length and width, and size of midsagittal tissue bridges) and
remote cord macrostructural and microstructural changes. We then determined
associations between macrostructural (SCA, GMA, WMA, DCA, VHA, and DHA) and
microstructural (DTI indexes within lateral corticospinal tract, dorsal column,
and spinal lemniscus) parameters and tract-specific clinical measures (motor,
pinprick, and light-touch score, GRASSP, SCIM) using linear regression models,
adjusted for age and lesion area. Finally, we investigated associations between
macrostructural and microstructural MRI indexes and neurophysiologic outcome
measures using linear regression models, adjusted for age and lesion area. Note
that only patients with both recordable electrophysiologic potentials and
available MRI data entered this regression analysis, resulting in a total number
of 8 patients. For all microstructural associations, we extracted mean values of
DTI indexes within anatomic regions of interest (lateral corticospinal tract,
dorsal column, and spinal lemniscus [containing spinothalamic and spinoreticular
tracts]) as embedded in the Spinal Cord Toolbox.[22] The level of significance was set to
p < 0.05.
Results
Radiologic, clinical, and neurophysiologic characteristics
Patients were scanned 6.7 ± 7.8 years after injury. An area of hyperintense
signal was visible on the T2-weighted sagittal images in 16 patients (figure 1, A and B); 13 patients showed
hyperintensities in their dorsal column, covering on average 41.4 ± 21.0%
of the whole dorsal column, and 2 patients showed hyperintensities in the
dorsolateral funiculus (e.g., corticospinal tract). The radiologic level of
injury (hyperintense T2-weighted signal) covered the vertebral level C3-5 in 1
patient, C3 in 1 patient, C4 in 2 patients, C4-5 in 1 patient, C5 in 2 patients,
C6 in 2 patients, C6-7 in 4 patients, and C7 in 2 patients. Two patients showed
no signal alteration within the cord. The average lesion area was 45.4 ±
66.6 mm2 with a lesion length of 11.3 ± 9.4 mm and a lesion
width of 4.3 ± 3.5 mm. In 2 patients, the lesion occupied the full cord
area, and no midsagittal tissue bridges could be identified. In the remaining 15
patients, the midsagittal tissue bridges had an average width of 2.9 ± 1.9
mm. No magnetic resonance abnormalities were identified in the control
group.
Figure 1
Macrostructural changes above the level of injury
Hyperintense regions most likely indicating (A) retrograde degeneration
in the corticospinal tract and (B) anterograde degeneration in the
dorsal column. Arrows indicate the corresponding locations. (C)
Differences between the cross-sectional white matter area,
cross-sectional gray matter area, cross-sectional ventral horn area, and
cross-sectional dorsal horn area in patients compared to healthy
controls.
Macrostructural changes above the level of injury
Hyperintense regions most likely indicating (A) retrograde degeneration
in the corticospinal tract and (B) anterograde degeneration in the
dorsal column. Arrows indicate the corresponding locations. (C)
Differences between the cross-sectional white matter area,
cross-sectional gray matter area, cross-sectional ventral horn area, and
cross-sectional dorsal horn area in patients compared to healthy
controls.Two patients were motor and sensory complete; 2 patients were motor complete and
sensory incomplete; and the remaining 13 patients were motor and sensory
incomplete. The motor score (maximum 100) was 68.1 ± 30.4; the light-touch
score was (mean ± SD) 66.3 ± 32.7 (maximum 112); and the pinprick
score (maximum 112) was 52.7 ± 35.0. Manual dexterity was impaired as
assessed by the GRASSP score (149.8 ± 66.3 [maximum 232]), and functional
independence was impaired as assessed by the SCIM score ([63.1 ± 31.3
[maximum. 100]). Eight patients were able to walk independently (20 of 20 points
in the WISCI score); 2 patients were dependent on walking aids (5 of 20 and 9 of
20 points in the WISCI score); and 7 patients were not able to walk (0 of 20
points). All data are summarized in table
1.
Table 1
Clinical and epidemiologic data for all patients included in the
study
Clinical and epidemiologic data for all patients included in the
studyAll patients had neurophysiologic impairment of the spinothalamic tract, and a
majority had impaired function of the dorsal column below the level of lesion as
assessed by CHEPs and SSEPs, respectively. The mean ± SD perception/pain
thresholds and the amplitudes and latencies of the recorded signals are shown in
table 2.
Table 2
Neurophysiologic data acquired in patients
Neurophysiologic data acquired in patients
Pathophysiologic changes in the cervical cord above the level of
injury
Compared to healthy controls, patients showed a decreased SCA of 20.2%
(p < 0.001, healthy controls 92.30 ± 8.49
mm2, patients 73.71 ± 20.04 mm2). In patients,
WMA was decreased by 16.9% (p = 0.001, healthy controls
75.34 ± 8.06 mm2, patients 62.64 ± 18.22 mm2),
and GMA was decreased by 30.0% (p < 0.001, healthy
controls 16.96 ± 1.25 mm2, patients 11.93 ± 2.73
mm2). In the white matter, DCA was decreased by 21.4%
(p < 0.001, healthy controls 23.73 ± 2.99
mm2, patients 18.65 ± 4.76 mm2). Within the gray
matter, the bilateral VHA showed a 34.4% decrease in patients compared to
healthy controls (left: p < 0.001, healthy controls 3.84
± 0.29 mm2, patients 2.56 ± 0.62 mm2; right:
p < 0.001, healthy controls 3.95 ± 0.40
mm2, patients 2.61 ± 0.58 mm2). In patients, the
DHA was decreased bilaterally by 33.4% (left: p < 0.001,
healthy controls 3.63 ± 0.41 mm2, patients 2.42 ± 0.66
mm2; right: p < 0.001, healthy controls
3.60 ± 0.51 mm2, patients 2.37 ± 0.66 mm2)
(figure 1C), and smaller DHA was
associated with smaller DCA (p < 0.001,
R2 = 0.74, 95% confidence interval [CI]
2.21–4.28).Voxel-based analysis of the cervical cord revealed a 16.6% decrease in FA in the
left dorsolateral funiculus (e.g., containing spinothalamic and lateral
corticospinal tracts, p = 0.003; localization [x, y, z]
−4.2, −18.5, 26; z score 4.42; cluster extent
154), 14.9% decrease in the right dorsolateral funiculus (p
= 0.025; localization [x, y, z] 6, −18.5, 37; z
score 4.34; cluster extent 85), and 17.0% decrease in the posterior funiculus
(i.e., containing dorsal columns; p = 0.004; localization
[x, y, z] 0.7, −22.3, 37; z score 3.80; cluster extent
145) in patients compared to healthy controls. AD was also decreased in patients
compared to healthy controls in the same regions, namely by 12.8% in the left
dorsolateral funiculus (p = 0.014; localization [x, y, z]
−3.1, −19.2, 26; z score 3.72; cluster extent
58), 12.8% the right dorsolateral funiculus (p = 0.002;
localization [x, y, z] 4.1, −18.8, 26; z score 4.70;
cluster extent 94), and 9.9% in the posterior funiculus (p
= 0.020; localization [x, y, z] 0.7, −19.2, 32; z
score 3.69; cluster extent 52). RD increased by 31.8% in the dorsal column
(p = 0.022; localization [x, y, z]: 0.3, −20.7,
37; z score 3.47; cluster extent 70) and by 34.0% in the left
dorsolateral funiculus (p = 0.023; localization [x, y, z]
−5, −19.2, 32; z score 3.22; cluster extent 69)
in patients compared to healthy controls. MD was not significantly different
between patients and healthy controls (figure
2).
Figure 2
Microstructural changes above the level of injury
Voxel-wise analysis of microstructural changes above the level of injury
in patients compared to healthy controls. First row shows the spinal
cord template; second row shows the white matter atlas. Note the spatial
overlap of the different diffusion tensor imaging metrics showing that
regions of decreased axonal diffusivity (AD; e.g., axonal degeneration)
but unaltered radial diffusivity (RD; e.g., no demyelination) lie mostly
adjacent to the gray matter, where unmyelinated propriospinal neurons
are located. FA = fractional anisotropy. Reprinted from De Leener
et al[22] with
permission from Elsevier.
Microstructural changes above the level of injury
Voxel-wise analysis of microstructural changes above the level of injury
in patients compared to healthy controls. First row shows the spinal
cord template; second row shows the white matter atlas. Note the spatial
overlap of the different diffusion tensor imaging metrics showing that
regions of decreased axonal diffusivity (AD; e.g., axonal degeneration)
but unaltered radial diffusivity (RD; e.g., no demyelination) lie mostly
adjacent to the gray matter, where unmyelinated propriospinal neurons
are located. FA = fractional anisotropy. Reprinted from De Leener
et al[22] with
permission from Elsevier.
Relationship between lesion severity and remote tissue-specific
neurodegeneration
Greater lesion area and length were associated with greater SCA decrease above
the level of injury (lesion area: p = 0.048,
R2 = 0.25, 95% CI −3.64 to
−0.23 1/mm3; lesion length: p = 0.006,
R2 = 0.42, 95% CI −0.55 to
−0.11 1/mm2) independently of age. The width of total
midsagittal tissue bridges was associated with less SCA decrease
(p = 0.007, R2 =
0.39, 95% CI 0.02–0.11 1/mm2). Greater lesion length was
associated with smaller GMA (p = 0.012,
R2 = 0.40, 95% CI −3.74 to
−0.57 1/mm2), VHA (p = 0.039,
R2 = 0.29, 95% CI −8.33 to
−0.25 1/mm2), and DHA (p = 0.004,
R2 = 0.49, 95% CI −8.36 to
−2.03 1/mm2), while midsagittal tissue bridges were positively
associated with GMA (p = 0.035,
R2 = 0.28, 95% CI
0.33–0.781/mm2) and DHA (p = 0.011,
R2 = 0.38, 95% CI 0.26–1.74
1/mm2) (figure 3A). Greater
lesion length and preserved midsagittal tissue bridges were associated with WMA
(lesion length: p = 0.014, R2
= 0.38, 95% CI −0.61 to −0.08 1/mm2; tissue
bridges: p = 0.011, R2 =
0.38, 95% CI 0.02–0.12 1/mm2) above the level of injury (figure 3B).
Figure 3
Relationship between lesion severity and neurodegeneration above the
level of injury
The magnitude of tissue damage at the lesion site is associated with the
amount of neurodegeneration above the level of injury. Lesion length and
midsagittal tissue bridges are associated with (A) remote gray matter
and (B) white matter atrophy.
Relationship between lesion severity and neurodegeneration above the
level of injury
The magnitude of tissue damage at the lesion site is associated with the
amount of neurodegeneration above the level of injury. Lesion length and
midsagittal tissue bridges are associated with (A) remote gray matter
and (B) white matter atrophy.The width of total midsagittal tissue bridges was associated with DCA above the
level of lesion (p = 0.019, R2
= 0.29, 95% CI 0.25–2.39 1/mm2). Neither lesion size nor
midsagittal tissue bridges were associated with microstructural changes above
the level of lesion.
Relationship between remote neurodegeneration and neurophysiologic
outcome
The size of the cross-sectional area of the dorsal columns identified those
patients with bilateral recordable SSEPs of the dermatomes C6 and C8 (figure 4). This relationship was not evident
for the WMA and CHEPs. Higher AD values within the dorsal column were associated
with shorter SSEP N1P1 latency at the C4 dermatome (p =
0.0024, R2 = 0.83, 95% CI: −0.00007 to
−0.00001 10−3 × s2/mm2),
corrected for age and lesion area. DTI metrics within the spinothalamic tracts
were not associated with CHEPs recordings.
Figure 4
Relationship between neurodegeneration above the level of injury and
electrophysiologic outcome
Patients were grouped into 3 cohorts: without or with unilateral (u) or
bilateral (b) recordable dermatomal somatosensory-evoked potentials
(SSEPs) at the C4, C6, and C8 level. Patients with recordable dermatomal
SSEPs showed a tendency toward larger dorsal column area above the level
of injury.
Relationship between neurodegeneration above the level of injury and
electrophysiologic outcome
Patients were grouped into 3 cohorts: without or with unilateral (u) or
bilateral (b) recordable dermatomal somatosensory-evoked potentials
(SSEPs) at the C4, C6, and C8 level. Patients with recordable dermatomal
SSEPs showed a tendency toward larger dorsal column area above the level
of injury.
Relationship between remote neurodegeneration and clinical outcome
GMA was associated with motor score (p = 0.007,
R2 = 0.72, 95% CI 1.77–9.26) and
pinprick score (p = 0.003, R2
= 0.58, 95% CI 3.48–13.90); VHA area was associated with motor score
(p = 0.001, R2 =
0.78, 95% CI 6.74–21.93); and DHA was associated with pinprick score
(p = 0.004, R2 =
0.57, 95% CI 7.43–31.52) when corrected for lesion area and age (figure 5A).
Figure 5
Relationship between neurodegeneration above the level of injury and
clinical outcome
Associations between (A) remote tract-specific macrostructural MRI
parameters above the level of injury and clinical impairment and (B)
remote tract-specific microstructural MRI indexes above the level of
injury and clinical impairment. FA = fractional anisotropy; SCIM
= Spinal Cord Independence Measure.
Relationship between neurodegeneration above the level of injury and
clinical outcome
Associations between (A) remote tract-specific macrostructural MRI
parameters above the level of injury and clinical impairment and (B)
remote tract-specific microstructural MRI indexes above the level of
injury and clinical impairment. FA = fractional anisotropy; SCIM
= Spinal Cord Independence Measure.To quantify tract-specific associations with appropriate clinical outcome, we
used the extracted mean values of DTI indexes within the regions of interest
(i.e., corticospinal tract, dorsal column, and spinothalamic tract). FA and RD
within corticospinal tract and the dorsal columns were associated with SCIM
score (corticospinal tract: FA: p = 0.002,
R2 = 0.80, 95% CI 105.82–361.55; RD:
p = 0.001, R2 = 0.83,
95% CI −169829.70 to −60547.48; dorsal columns: FA:
p = 0.002, R2 = 0.80,
95% CI 106.07–341.42; RD: p = 0.003,
R2 = 0.79, 95% CI −216944.1 to
−60854.36) independently of lesion extent and age (figure 5B). AD within the dorsal columns was associated with
GRASSP score independently of lesion extent and age (p =
0.30, R2 = 0.60, 95% CI
40298.4–646999.7).
Discussion
This study shows the in vivo structure-function relationship between the extent of
tissue-specific cord pathology and neurophysiologic and clinical impairment after
traumatic SCI. Crucially, we show that the magnitude of tissue damage at the lesion
epicenter is associated with the extent of neurodegeneration above the level of
lesion, which, in turn, is associated with clinically relevant impairment and
neurophysiologic abnormalities. These findings allow us to investigate the extent of
tissue-specific neurodegeneration above the level of injury, its relationship to
neuronal tissue loss at the site of the lesion, and its effect on neurophysiologic
and clinical outcome.Tissue damage at the epicenter of a traumatic SCI results both from the direct effect
of the traumatic insult and from damage to the vascular architecture and the ensuing
ischemic effects on the neuronal and glial cell populations within the acute phase
of injury.[23] Remote from the
epicenter of the lesion, secondary neurodegeneration within white[24,25] and gray matter[26] follows with a time lag and is driven by a multiphasic
response to cellular inflammation.[27] While the extent of secondary remote atrophy has been
quantified in vivo after injury,[2,28-30] we provide
evidence that changes within both gray and white matter contribute to cord atrophy
above the level of injury. This is in agreement with spinal gray matter degeneration
distant to the initial site of damage in patients with multiple sclerosis[31] and experimental SCI.[32] Although the relative decrease is
larger within ventral and dorsal horns (i.e., gray matter), the absolute magnitude
of change is larger within white matter, contributing more to the overall loss of
SCA by 20.2%.We uncovered an in vivo relationship between neuronal tissue loss (i.e., lesion
severity) and remote tissue-specific cord pathology above the level of injury.
Moreover, we show an interdependence of remote white and gray matter atrophy (i.e.,
DHA and DCA). Neurodegenerative changes within gray matter above the level of injury
are not likely to be specific for any single pathologic process but rather are
likely to represent a combination of different pathologic mechanisms taking place
after SCI. Possible mechanisms involve transsynaptic/transneuronal degeneration
affecting the propriospinal systems[33,34] and motor neurons
located in the proximity of the spinal injury.[35] Next to direct effects of neurodegenerative processes, a
reduction in muscle activity of the upper extremity could lead to a reduction of
neuronal activity above the level of injury, which may translate into shrinkage of
the neuron soma size.Furthermore, demyelination of corticospinal projections to the dorsal
horns,[36] the expression of
neurotrophic factors from nonneuronal cells around neighboring degenerating
axons,[36] growth factor
dysregulation,[37] and
vascular remodeling[38] could
contribute to gray matter pathology. As white matter damage is known to induce
microglial activation altering glutamate signaling, this process is thought to be
responsible for the dying back of axons and their parternal neurons,[39] which might be a shared underlying
disease mechanism. Thus, next to anterograde and retrograde degeneration of white
matter tracts[30,40,41] the
neuronal circuits within the spinal cord far above the level of injury undergo a
temporary structured neurodegeneration.[25]Within the microstructure of the atrophied white matter, we found indications of both
axonal degeneration and demyelination,[42] represented by decreased FA and AD and increased RD in the
dorsolateral funiculus (e.g., containing the lateral corticospinal and spinothalamic
tracts) and posterior funiculus (e.g., containing the dorsal columns). Within the
corticospinal tract and the dorsal column, leg function is represented most
laterally, whereas arm function is located either medially (i.e., corticospinal
tract) or centrally (i.e., dorsal column). Our observed changes cover the entire
lateral corticospinal tract and the dorsal columns, indicating neurodegenerative
processes affecting axons that convey information relating to leg and arm function.
Spatially overlaying the different DTI metrics changes revealed that regions showing
decreased AD (e.g., axonal degeneration) but unaltered RD (e.g., no demyelination)
lie mostly adjacent to the gray matter border. This region contains the fasciculi
proprii and contains mostly short, mainly unmyelinated propriospinal
neurons.[43] This underlies
our hypothesis that SCI might lead to degeneration affecting interneurons within the
spinal cord.Our findings complement previous studies in patients with SCI [20,44-46] in that they now locate these
changes to gray and white matter rather than being nonspecific in terms of location
and tissue. Thus, our in vivo cord MRI measurements demonstrate a combination of
structural and functional processes occurring over several segments above the level
of injury affecting both gray and white matter that is driven by lesion
severity.We show that tract-specific microstructural and macrostructural changes are
associated with prolonged conduction of appropriate electrophysiologic recordings.
This association suggests a structure-function relationship because the amount of
neurodegeneration was directly associated with impairment of neurophysiologic
information flow. Because the DTI signal is sensitive to altered diffusion
properties occurring as a response to CNS damage (i.e., demyelination/degeneration)
and because neuronal excitability is affected by morphometry of the axon and its
myelin, it seems plausible that neurophysiologic changes might be reflected in
remote macrostructural and microstructural changes above the level of injury. Our
findings complement previous findings showing that the topography and the
excitability of corticomotor projections were associated with cervical cord
atrophy.[2,47]Current assessments in patients with SCI lack sensitivity to minimal changes in motor
and sensory function[48] in that
they cannot detect subtle changes due to remyelination and axonal regeneration.
Neuroimaging biomarkers have the potential to track these subtle abnormalities
because they are sensitive to microstructural changes.[1] In this study, the magnitude of both remote
macrostructural and microstructural changes within gray and white matter was
significantly associated with clinical impairment, independently of lesion extent.
In particular, the extent of remote ventral horn atrophy was associated with motor
impairment, whereas dorsal horn atrophy was associated with sensory disturbance.
Microstructural tract-specific changes above the level of injury were related to
measures of functional independence (i.e., SCIM) and strength, sensibility, and
prehension of the upper limbs (i.e., GRASSP). This suggests that high-resolution MRI
sequences applied above the level of injury provide superior information on the
patient's clinical status compared to standard clinical sequences at the lesion
site. In addition, the latter findings are striking in that they suggest that remote
neurodegeneration within gray matter above the level of injury contributes, in
addition to white matter pathology, to motor and sensory impairment. This multilevel
interaction supports the view that SCI leads to a cascade of neurodegenerative
changes affecting the entire spinal cord and brain.[49] Characterizing these secondary neurodegenerative
events has the potential to provide insights into new therapeutic interventions, in
addition to providing opportunities for monitoring treatment effects in trials
conducted in patients with acute and chronic SCI.This study had several limitations. Although our cohorts did not show a significant
age difference, the mean age was on average higher in the patient group, which could
potentially affect the analysis. We therefore adjusted for age as a potential
confounder of no interest in all analyses. Furthermore, unbiased voxel-based
morphometry of DTI indexes in the spinal cord has just started emerging,[3] and the automated postprocessing
methods for spatial normalization of the spinal cord into common space are in their
infancy. To increase the reliability of our analysis, we therefore manually
corrected the spatial normalization to the template.This study shows that the magnitude of dorsal and ventral horn and white matter
structural changes above the level of injury is associated with appropriate clinical
and neurophysiologic impairment and is driven by lesion severity. These findings
suggest a combination of different pathologic processes affecting both gray and
white matter several segments above the level of injury that are clinically
eloquent. Therefore, these neuroimaging biomarkers might serve as promising
surrogate markers for future clinical trials supplementing (or complementing)
clinical outcome measures.
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