Sreenath P Kyathanahally1, Michela Azzarito1, Markus Hupp1, and Patrick Freund1
1Spinal cord injury center Balgrist, University of Zurich, Zurich, Switzerland
Synopsis
Spinal cord injury (SCI) triggers a cascade of neurodegenerative
and compensatory changes across the neuroaxis. Rehabilitative training has been
shown to improve clinical outcome following SCI. However, the
spatial and temporal patterns of neurodegenerative processes follow a
complicated trajectory over 2-years. Previous studies have already shown trauma-induced neurodegenerative processes and
highlight the relationships amongst these in the cord and brain. Here, we investigate
the trajectories of neurodegenerative changes that occur over a period of 5 years
post-SCI.
Introduction:
Traumatic spinal cord
injury (SCI) is a devastating and life changing incidence that leads
instantaneously to permanent paralysis and loss of sensory input1. Functional recovery following SCI is rather restricted
and the majority of patients will be left with severe impairments2. Rehabilitative training has been shown to improve clinical
outcome while the neuronal mechanisms underlying neurological and
functional recovery are not well understood3. Recent advances in quantitative neuroimaging of the
spinal cord (SC) and brain provide the possibility of monitoring temporal
changes of the macrostructure from the earliest onset of SCI. A longitudinal follow-up study over 2 years post-SCI
provided already important insights into progressive degenerative changes
across the neuroaxis4–6. The current study aims to extend this longitudinal
study to 5-years follow-up in order to fully characterize the temporal profiles
of the different trajectories of neurodegeneration across the neuroaxis. This
would enable us to better understand the time course of basic disease
mechanisms underpinning degeneration and neuronal damage and assess its
contribution to recovery and impairment.
We hypothesize that the cascade of
neurodegenerative changes levels off with a lesion-level and activity dependent
diaschisis over 5 years follow-up; and that the magnitude of trajectories in
cord and brain (motor and sensory) areas relate to clinical
recovery/impairment. We therefore aim to track the temporal and regional
evolution of remote and focal MRI based structural changes over 5 years.Method:
Eighteen patients with traumatic SCI and
21 healthy controls participated in a 5-year longitudinal study. All participants
underwent structural MRI (T1-weighted images) scans and multi
parameter mapping (MPM) scans of whole-brain and
cervical cord over 5 years (baseline, 2 months, 6 months, 12 months 24 months,
and 60 months). In total, 212 MRI
datasets were analyzed. However, currently we present only results from T1w
scans. Patients were also assessed with the ISNCSCI
motor and sensory scores7, SCIM scores8 and GRASSP scores9. The structural images were preprocessed using VBM10 and
smoothed with 6-mm FWHM Gaussian-kernel. They underwent 2-stage summary
statistics in SPM11. In the first stage, we used all time point scans from
each subject to estimate the individual linear trajectory models y(t) = β0 +
β1*t and generate the intercepts (β0) and rate of change (β1) maps; then in the
second stage, rate of change maps of patients and controls were used in a
2-sample t-test to test for group differences while adjusting for age and sex.
In order to investigate the
morphometric changes at the cord level, we measured crossâsectional
spinal cord area (CSA), by manually segmenting the T1w MPRAGE image, at level
C2/C3 using JIM 6.0 software12. And to measure
anterior–posterior width (APW) and left–right
width (LRW) next to CSA, an ellipse was fit to the boundary of the CSA. Then
cervical SC data was analyzed using Stata 1313Results:
At the level of the
spinal cord a
decline in CSA by 0.53 mm2 per month (p <
0.001), APW by 0.03 mm per month (p < 0.001), and LRW by 0.04 mm
per month (p < 0.001) was found in patients compared to controls
(Figure 1). The rate of change of cord area decelerated (i.e., a
positive quadratic effect) by 0.005 mm2 per month (p <
0.001), APW by 0.0003 mm per month (p < 0.001) and LRW by 0.0004
mm per month, (p< 0.001) over 5 years in patients compared to
controls.
At
the level of the brain, WM volume within the corticospinal tracts (CST) of
patients decreased more rapidly than in controls, with differences in the
medulla oblongata and cerebellar peduncle over 5 years. GM volume
decreased in the left insula, left ACC, and left thalamus (Figure 2).Discussion & Conclusion:
Trajectories of atrophy were observed
in the same areas at the level of the cord and brain as already identified over
the first 2 years
5. Crucially, we now provide evidence that the rate of change on cord
area and brain volume decelerated, indicating a halting of the
neurodegenerative changes induced by a focal injury to the spinal cord at 45
years follow-up. Quantitative
MR data (MT, R2*) will be analyzed next to understand the microstructural changes occurring in
areas of atrophy and its association with clinical outcome.
Acknowledgements
This work was supported by Wings for Life – Spinal Cord Research Foundation References
1. Zariffa J, Kramer JLK, Fawcett JW, et
al. Characterization of neurological recovery following traumatic sensorimotor
complete thoracic spinal cord injury. Spinal Cord. 2011;49(3):463-471.
doi:10.1038/sc.2010.140.
2. Curt A, Van Hedel HJA, Klaus D, Dietz
V. Recovery from a Spinal Cord Injury: Significance of Compensation, Neural
Plasticity, and Repair. J Neurotrauma. 2008;25(6):677-685.
doi:10.1089/neu.2007.0468.
3. Huber E, Curt A, Freund P. Tracking
trauma-induced structural and functional changes above the level of spinal cord
injury. Curr Opin Neurol. 2015;28(4):365-372.
doi:10.1097/WCO.0000000000000224.
4. Freund P, Weiskopf N, Ashburner J, et
al. MRI investigation of the sensorimotor cortex and the corticospinal tract
after acute spinal cord injury: a prospective longitudinal study. Lancet
Neurol. 2013;12(9):873-881. doi:10.1016/S1474-4422(13)70146-7.
5. Ziegler G, Grabher P, Thompson A, et
al. Progressive neurodegeneration following spinal cord injury. Neurology.
March 2018:10.1212/WNL.0000000000005258. doi:10.1212/WNL.0000000000005258.
6. Grabher P, Callaghan MF, Ashburner J,
et al. Tracking sensory system atrophy and outcome prediction in spinal cord
injury. Ann Neurol. 2015;78(5):751-761. doi:10.1002/ana.24508.
7. Kirshblum SC, Waring W,
Biering-Sorensen F, et al. International standards for neurological
classification of spinal cord injury (Revised 2011). J Spinal Cord Med.
2011;34(6):547-554. doi:10.1179/107902611X13186000420242.
8. Catz A, Itzkovich M, Agranov E, Ring H,
Tamir A. SCIM--spinal cord independence measure: a new disability scale for
patients with spinal cord lesions. Spinal
Cord. 1997;35(12):850-856.
9. Kalsi-Ryan S, Beaton D, Curt A, et al.
The Graded Redefined Assessment of Strength Sensibility and Prehension:
Reliability and Validity. J Neurotrauma. 2012;29(5):905-914.
doi:10.1089/neu.2010.1504.
10. Ashburner J, Friston KJ. Voxel-Based
Morphometry—The Methods. Neuroimage. 2000;11(6):805-821.
doi:10.1006/nimg.2000.0582.
11. Friston K, Holmes A, Worsley K, Poline J,
Frith C, Frackowiak R. Statistical parametric maps in functional imaging: A
general linear approach. Hum Brain Mapp. 1994;2(4):189-210.
12. JIM, Xinapse Systems – Medical Image
Analysis. http://www.xinapse.com/.
13. STATA 13. https://www.stata.com/.