Predicting functional outcomes from spinal cord injury (SCI) at the acute setting is important for patient management. This work investigated the relationship of early magnetic resonance imaging (MRI) biomarkers in a rat model of cervical contusion SCI with long-term functional outcome and tissue sparing. Forty rats with contusion injury at C5 at either the spinal cord midline (bilateral) or over the lateral cord (unilateral) were examined using in vivo multi-modal quantitative MRI at 1 day post-injury. The extent of T2-weighted hyperintensity reflecting edema was greater in the bilateral model compared with the unilateral injury. Diffusion tensor imaging (DTI) exhibited microscopic damage in similar regions of the cord as reductions in fractional anisotropy (FA) and mean diffusivity (MD), but DTI parameter maps were also confounded by the presence of vasogenic edema that locally increased FA and MD. In comparison, filtered diffusion-weighted imaging (fDWI) more clearly delineated the location of acute axonal damage without effects of vasogenic edema. Pairwise correlation analysis revealed that 28-day motor functional outcomes were most strongly associated with the extent of edema (R = −0.69). Principal component analysis identified close associations of motor functional score with tissue sparing, the extent of edema, lesion area, and injury type (unilateral or bilateral). Among the diffusion MRI parameters, lesion areas measured with fDWI had the strongest association with functional outcome (R = −0.41). Voxelwise correlation analysis identified a locus of white matter damage associated with function in the dorsal white matter, although this was likely driven by variance across the two injury patterns (unilateral and bilateral injury). Nonetheless, correlation with motor function within the damaged region found in the voxelwise analysis outperformed morphological lesion area measurement as a predictor of chronic function. Collectively, this study characterized anatomical and diffusion MRI signatures of acute SCI at cervical spine and their association with chronic functional outcomes and histological results.
Get full access to this article
View all access options for this article.
References
1.
BozzoA, MarcouxJ, RadhakrishnaM, et al.The role of magnetic resonance imaging in the management of acute spinal cord injury. J Neurotrauma, 2011; 28(8):1401–1411; doi: 10.1089/neu.2009.1236.
2.
GartonTP, HeY, GartonHJL, et al.Hemoglobin-induced neuronal degeneration in the hippocampus after neonatal intraventricular hemorrhage. Brain Res, 2016; 1635:86–94; doi: 10.1016/j.brainres.2015.12.060.
ZilleM, KaruppagounderSS, ChenY, et al.Neuronal death after hemorrhagic stroke in vitro and in vivo shares features of ferroptosis and necroptosis. Stroke, 2017; 48(4):1033–1043; doi: 10.1161/STROKEAHA.116.015609.
5.
LoseyP, AnthonyDC. Impact of vasculature damage on the outcome of spinal cord injury: a novel collagenase-induced model may give new insights into the mechanisms involved. Neural Regen Res, 2014; 9(20):1783–1786; doi: 10.4103/1673-5374.143422.
6.
LoseyP, YoungC, KrimholtzE, et al.The role of hemorrhage following spinal-cord injury. Brain Res, 2014; 1569:9–18; doi: 10.1016/j.brainres.2014.04.033.
7.
GuoT, RenP, LiX, et al.Neural injuries induced by hydrostatic pressure associated with mass effect after intracerebral hemorrhage. Sci Rep, 2018; 8(1):1–12; doi: 10.1038/s41598-018-27275-7.
8.
KumarY, HayashiD. Role of magnetic resonance imaging in acute spinal trauma: a pictorial review. BMC Musculoskelet Disord, 2016; 17:310; doi: 10.1186/s12891-016-1169-6.
9.
MiyanjiF, FurlanJC, AarabiB, et al.Acute cervical traumatic spinal cord injury: MR imaging findings correlated with neurologic outcome–prospective study with 100 consecutive patients. Radiology, 2007; 243(3):820–827; doi: 10.1148/radiol.2433060583.
10.
AarabiB, SansurCA, IbrahimiDM, et al.Intramedullary lesion length on postoperative magnetic resonance imaging is a strong predictor of ASIA Impairment Scale grade conversion following decompressive surgery in cervical spinal cord injury. Neurosurgery, 2017; 80(4):610–620; doi: 10.1093/neuros/nyw053.
11.
SinghR, KumarRR, SetiaN, et al.A prospective study of neurological outcome in relation to findings of imaging modalities in acute spinal cord injury. Asian J Neurosurg, 2015; 10(3):181–189; doi: 10.4103/1793-5482.161166.
12.
ShanmuganathanK, ZhuoJ, ChenHH, et al.Diffusion tensor imaging parameter obtained during acute blunt cervical spinal cord injury in predicting long-term outcome. J Neurotrauma, 2017; 34(21):2964–2971; doi: 10.1089/neu.2016.4901.
13.
DeoAA, GrillRJ, HasanKM, et al.In vivo serial diffusion tensor imaging of experimental spinal cord injury. J Neurosci Res, 2006; 83(5):801–810; doi: 10.1002/jnr.20783.
14.
LiuY, KongC, CuiL, et al.Correlation between diffusion tensor imaging parameters and clinical assessments in patients with cervical spondylotic myelopathy with and without high signal intensity. Spinal Cord, 2017; 55(12):1079–1083; doi: 10.1038/sc.2017.75.
15.
RutmanAM, PetersonDJ, CohenWA, et al.Diffusion tensor imaging of the spinal cord: clinical value, investigational applications, and technical limitations. Curr Probl Diagn Radiol, 2018; 47(4):257–269; doi: 10.1067/j.cpradiol.2017.07.005.
16.
SkinnerNP, KurpadSN, SchmitBD, et al.Rapid in vivo detection of rat spinal cord injury with double-diffusion-encoded magnetic resonance spectroscopy. Magn Reson Med, 2017; 77(4):1639–1649; doi: 10.1002/mrm.26243.
17.
SkinnerNP, LeeS-Y, KurpadSN, et al. Filter-probe diffusion imaging improves spinal cord injury outcome prediction. Ann Neurol 2018; doi: 10.1002/ana.25260.
18.
BuddeMD, SkinnerNP, MuftulerLT, et al. Optimizing filter-probe diffusion weighting in the rat spinal cord for human translation. Front Neurosci 2017;11; doi: 10.3389/fnins.2017.00706.
19.
AhujaCS, MartinAR, FehlingsMG. Recent Advances in Managing a Spinal Cord Injury Secondary to Trauma. F1000Res, 2016; 5:1017; doi: 10.1268/8/f1000research.7586.1.
20.
WilkinsNL, SkinnerNP, MotovylyakA, et al.Evolution of magnetic resonance imaging as predictors and correlates of functional outcome after spinal cord contusion injury in the rat. J Neurotrauma, 2020; 37(6):889–898; doi: 10.1089/neu.2019.6731.
21.
RamseyJBG, RamerLM, InskipJA, et al.Care of rats with complete high-thoracic spinal cord injury. J Neurotrauma, 2010; 27(9):1709–1722; doi: 10.1089/neu.2010.1382.
22.
AndersonKD, SharpKG, HofstadterM, et al.Forelimb Locomotor Assessment Scale (FLAS): novel assessment of forelimb dysfunction after cervical spinal cord injury. Exp Neurol, 2009; 220(1):23–33; doi: 10.1016/j.expneurol.2009.08.020.
23.
SimardJM, PopovichPG, TsymbalyukO, et al.Spinal cord injury with unilateral versus bilateral primary hemorrhage—effects of glibenclamide. Exp Neurol, 2012; 233(2):829–835; doi: 10.1016/j.expneurol.2011.11.048.
24.
LeeS-Y, MeyerBP, KurpadSN, et al.Diffusion-prepared fast spin echo for artifact-free spinal cord imaging. Magn Reson Med, 2021; 86(2):984–994; doi: 10.1002/mrm.28751.
25.
BuddeM. Variable flip angle RARE for high-resolution preclinical brain and spinal cord imaging. Proc. Intl. Soc. Mag. Reson. Med.; 2018. doi: http://indexsmart.mirasmart.com/ISMRM2018/PDFfiles/2039.html.
26.
WatsonC, PaxinosG, KayaliogluG, et al. Chapter 15—Atlas of the Rat Spinal Cord. In: The Spinal Cord. (Watson C, Paxinos G, Kayalioglu G. eds.) Academic Press: San Diego; 2009; pp. 238–306; doi: 10.1016/B978-0-12-374247-6.50019-5.
27.
De LeenerB, LévyS, DupontSM, et al.SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data. Neuroimage, 2017; 145(Pt A):24–43; doi: 10.1016/j.neuroimage.2016.10.009.
28.
GorgolewskiK, BurnsC, MadisonC, et al. Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. Front Neuroinform 2011;5(13); doi: https://doi.org/10.3389/fninf.2011.00013.
29.
BuddeMD. Processing template for rat spinal cord MRI inNipype. 2022. https://github.com/mdbudde/RatSpinalCordMRIpipeline (Last accessed July15, 2022).
30.
SnedecorGW, CochranWG. Statistical Methods. 8th edition. Iowa State University Press: Ames, Iowa; 1989.
31.
SmithSM, JenkinsonM, WoolrichMW, et al.Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage, 2004; 23(Suppl 1):S208–S219; doi: 10.1016/j.neuroimage.2004.07.051.
32.
JenkinsonM, BeckmannCF, BehrensTEJ, et al.FSL. Neuroimage, 2012; 62(2):782–790; doi: 10.1016/j.neuroimage.2011.09.015.
33.
AlizadehA, DyckSM, Karimi-AbdolrezaeeS. Traumatic spinal cord injury: an overview of pathophysiology, models and acute injury mechanisms. Front Neurol, 2019; 10:282; doi: 10.3389/fneur.2019.00282.
34.
SinghA, KrisaL, FrederickKL, et al.Forelimb locomotor rating scale for behavioral assessment of recovery after unilateral cervical spinal cord injury in rats. J Neurosci Methods, 2014; 226:124–131; doi: 10.1016/j.jneumeth.2014.01.001.
35.
CaoY, ShumskyJS, SabolMA, et al.Nogo-66 receptor antagonist peptide (NEP1-40) administration promotes functional recovery and axonal growth after lateral funiculus injury in the adult rat. Neurorehabil Neural Repair, 2008; 22(3):262–278; doi: 10.1177/1545968307308550.
36.
IrvineK-A, FergusonAR, MitchellKD, et al. The Irvine, Beatties, and Bresnahan (IBB) Forelimb Recovery Scale: an assessment of reliability and validity. Front Neurol 2014;5; doi: 10.3389/fneur.2014.00116.
37.
FreehaferAA. Care of the hand in cervical spinal cord injuries. Spinal Cord, 1969; 7(2):118–130; doi: 10.1038/sc.1969.22.
38.
LeypoldBG, FlandersAE, BurnsAS. The early evolution of spinal cord lesions on MR imaging following traumatic spinal cord injury. Am J Neuroradiol, 2008; 29(5):1012–1016; doi: 10.3174/ajnr.A0962.
39.
FlandersAE, SpettellCM, TartaglinoLM, et al.Forecasting motor recovery after cervical spinal cord injury: value of MR imaging. Radiology, 1996; 201(3):649–655; doi: 10.1148/radiology.201.3.8939210.
40.
DalkilicT, FallahN, NoonanVK, et al.Predicting injury severity and neurological recovery after acute cervical spinal cord injury: a comparison of cerebrospinal fluid and magnetic resonance imaging biomarkers. J Neurotrauma, 2017; 35(3):435–445; doi: 10.1089/neu.2017.5357.
41.
RutgesJPHJ, KwonBK, HeranM, et al.A prospective serial MRI study following acute traumatic cervical spinal cord injury. Eur Spine J, 2017; 26(9):2324–2332; doi: 10.1007/s00586-017-5097-4.
42.
ChandraJ, SheerinF, Lopez de HerediaL, et al.MRI in acute and subacute post-traumatic spinal cord injury: pictorial review. Spinal Cord, 2012; 50(1):2–7; doi: 10.1038/sc.2011.107.
43.
SparaciaG, SpecialeC, BancoA, et al.Accuracy of SWI sequences compared to T2*-weighted gradient echo sequences in the detection of cerebral cavernous malformations in the familial form. Neuroradiol J, 2016; 29(5):326–335; doi: 10.1177/1971400916665376.
44.
BeattieMS, ManleyGT. Tight squeeze, slow burn: inflammation and the aetiology of cervical myelopathy. Brain, 2011; 134(5):1259–1261; doi: 10.1093/brain/awr088.
45.
BuddeMD, SkinnerNP. Diffusion MRI in acute nervous system injury. J Magn Reson, 2018; 292:137–148; doi: 10.1016/j.jmr.2018.04.016.
46.
KimJH, LoyDN, WangQ, et al.Diffusion tensor imaging at 3 hours after traumatic spinal cord injury predicts long-term locomotor recovery. J Neurotrauma, 2010; 27(3):587–598; doi: 10.1089/neu.2009.1063.
47.
PisharadyPK, EberlyLE, CheongI, et al.Tract-specific analysis improves sensitivity of spinal cord diffusion MRI to cross-sectional and longitudinal changes in amyotrophic lateral sclerosis. Commun Biol, 2020; 3(1):1–13; doi: 10.1038/s42003-020-1093-z.
48.
FouadK, PopovichPG, KoppMA, et al.The neuroanatomical–functional paradox in spinal cord injury. Nat Rev Neurol, 2021; 17(1):53–62; doi: 10.1038/s41582-020-00436-x.
49.
FergusonAR, IrvineK-A, GenselJC, et al. Derivation of multivariate syndromic outcome metrics for consistent testing across multiple models of cervical spinal cord injury in rats. PLoS One 2013;8(3); doi: 10.1371/journal.pone.0059712.
50.
NobleLJ, WrathallJR. Correlative analyses of lesion development and functional status after graded spinal cord contusive injuries in the rat. Exp Neurol, 1989; 103(1):34–40; doi: 10.1016/0014-4886(89)90182-9.
51.
SchuchtP, RaineteauO, SchwabME, et al.Anatomical correlates of locomotor recovery following dorsal and ventral lesions of the rat spinal cord. Exp Neurol, 2002; 176(1):143–153; doi: 10.1006/exnr.2002.7909.
52.
HackneyDB, FinkelsteinSD, HandCM, et al.Postmortem magnetic resonance imaging of experimental spinal cord injury: magnetic resonance findings versus in vivo functional deficit. Neurosurgery, 1994; 35(6):1104–1111; doi: 10.1227/00006123-199412000-00013.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
