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European Spine Journal
Published in: European Spine Journal 1/2024

05-11-2023 | Magnetic Resonance Imaging | Review Article

Evaluating tissue injury in cervical spondylotic myelopathy with spinal cord MRI: a systematic review

Authors: Ali Fahim Khan, Esmaeil Mohammadi, Grace Haynes, Sanaa Hameed, Michael Rohan, David B. Anderson, Kenneth A. Weber II, Fauziyya Muhammad, Zachary A. Smith

Published in: European Spine Journal | Issue 1/2024

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Abstract

Purpose

Cervical Spondylotic Myelopathy (CSM) is a degenerative condition that leads to loss of cervical spinal cord (CSC) integrity. Various spinal cord Magnetic Resonance Imaging (MRI) methods can identify and characterize the extent of this damage. This systematic review aimed to evaluate the diagnostic, biomarker, and predictive utilities of different spinal cord MRI methods in clinical research studies of CSM. The aim was to provide a comprehensive understanding of the progress in this direction for future studies and effective diagnosis and management of CSM.

Methods

A comprehensive literature search was conducted on PubMed and EMBASE from 2010 to 2022 according to PRISMA guidelines. Studies with non-human subjects, less than 3T magnetic field strength, non-clinical design, or not quantitatively focusing on the structural integrity of CSC were excluded. The extracted data from each study included demographics, disease severity, MRI machine characteristics, quantitative metrics, and key findings in terms of diagnostic, biomarker, and predictive utilities of each MRI method. The risk of bias was performed using the guide from AHRQ. The quality of evidence was assessed separately for each type of utility for different MRI methods using GRADE.

Results

Forty-seven studies met the inclusion criteria, utilizing diffusion-weighted imaging (DTI) (n = 39), magnetization transfer (MT) (n = 6), MR spectroscopy (n = 3), and myelin water imaging (n = 1), as well as a combination of MRI methods (n = 12). The metric fractional anisotropy (FA) showed the highest potential in all facets of utilities, followed by mean diffusivity. Other promising metrics included MT ratio and intracellular volume fraction, especially in multimodal studies. However, the level of evidence for these promising metrics was low due to a small number of studies. Some studies, mainly DTI, also reported the usefulness of spinal cord MRI in mild CSM.

Conclusions

Spinal cord MRI methods can potentially facilitate the diagnosis and management of CSM by quantitatively interrogating the structural integrity of CSC. DTI is the most promising MRI method, and other techniques have also shown promise, especially in multimodal configurations. However, this field is in its early stages, and more studies are needed to establish the usefulness of spinal cord MRI in CSM.
Appendix
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Literature
1.
Karadimas SK et al (2013) Pathophysiology and natural history of cervical spondylotic myelopathy. Spine (Phila Pa 1976) 38(22 Suppl 1):S21–S36PubMedCrossRef
2.
3.
Shen H et al (2007) Applications of diffusion-weighted MRI in thoracic spinal cord injury without radiographic abnormality. Int Orthop 31(3):375–383PubMedCrossRef
4.
Murphy RK et al (2018) Fractional anisotropy to quantify cervical spondylotic myelopathy severity. J Neurosurg Sci 62(4):406–412PubMedCrossRef
5.
Nischal N, Tripathi S, Singh JP (2021) Quantitative evaluation of the diffusion tensor imaging matrix parameters and the subsequent correlation with the clinical assessment of disease severity in cervical spondylotic myelopathy. Asian Spine J 15(6):808–816PubMedCrossRef
6.
7.
8.
Jones JG et al (2013) Diffusion tensor imaging correlates with the clinical assessment of disease severity in cervical spondylotic myelopathy and predicts outcome following surgery. AJNR Am J Neuroradiol 34(2):471–478PubMedPubMedCentralCrossRef
9.
Wen CY et al (2013) Is diffusion anisotropy a biomarker for disease severity and surgical prognosis of cervical spondylotic myelopathy. Radiology 270:197–204PubMedCrossRef
10.
Arima H et al (2015) Prediction of the efficacy of surgical intervention in patients with cervical myelopathy by using diffusion tensor 3T-magnetic resonance imaging parameters. J Craniovertebr Junction Spine 6(3):120–124PubMedPubMedCentralCrossRef
11.
Wang K et al (2017) Evaluation of DTI parameter ratios and diffusion tensor tractography grading in the diagnosis and prognosis prediction of cervical spondylotic myelopathy. Spine (Phila Pa 2017) 42(4):E202–E210CrossRef
12.
Paliwal M et al (2020) Magnetization transfer ratio and morphometrics of the spinal cord associates with surgical recovery in patients with degenerative cervical myelopathy. World Neurosurg 144:e939–e947PubMedPubMedCentralCrossRef
13.
Gao SJ et al (2013) Correlation study of 3T-MR-DTI measurements and clinical symptoms of cervical spondylotic myelopathy. Eur J Radiol 82(11):1940–1945PubMedCrossRef
14.
Liang S et al (2022) Changes and clinical correlation of diffusion tensor imaging parameters of compressed spinal cord and nerve root in patients with cervical spondylosis. BMC Med Imaging 22(1):107PubMedPubMedCentralCrossRef
15.
Maki S et al (2017) Reduced field-of-view diffusion tensor imaging of the spinal cord shows motor dysfunction of the lower extremities in patients with cervical compression myelopathy. Spine 43(2):89–96CrossRef
16.
17.
Hori M et al (2018) Application of quantitative microstructural MR imaging with atlas-based analysis for the spinal cord in cervical spondylotic myelopathy. Sci Rep 8(1):1–8ADSCrossRef
18.
Zhang MZ et al (2022) Utility of advanced DWI in the detection of spinal cord microstructural alterations and assessment of neurologic function in cervical spondylotic myelopathy patients. J Magn Reson Imaging 55(3):930–940MathSciNetPubMedCrossRef
19.
Ellingson BM et al (2015) Prediction of neurological impairment in cervical spondylotic myelopathy using a combination of diffusion MRI and proton MR spectroscopy. PLoS ONE 10(10):e0139451PubMedPubMedCentralCrossRef
20.
Iwama T et al (2020) Utility and validity of neurite orientation dispersion and density imaging with diffusion tensor imaging to quantify the severity of cervical spondylotic myelopathy and assess postoperative neurological recovery. Spine J 20(3):417–425MathSciNetPubMedCrossRef
21.
Jiang W et al (2018) Usefulness of conventional magnetic resonance imaging, diffusion tensor imaging and neurite orientation dispersion and density imaging in evaluating postoperative function in patients with cervical spondylotic myelopathy. J Orthop Transl 15:59–69
22.
Liberati A et al (2009) The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J Clin Epidemiol 62(10):e1–e34PubMedCrossRef
23.
Martin AR et al (2016) Translating state-of-the-art spinal cord MRI techniques to clinical use: a systematic review of clinical studies utilizing DTI, MT, MWF, MRS, and fMRI. Neuroimage Clin 10:192–238PubMedCrossRef
24.
Viswanathan M et al (2012) Assessing the risk of bias of individual studies in systematic reviews of health care interventions. Agency for healthcare research and quality methods guide for comparative effectiveness reviews. AHRQ Methods for Effective Health Care
25.
Group GW (2012) Grading of recommendations assessment, development and evaluation (GRADE)
26.
Yang HE et al (2022) Utility of diffusion and magnetization transfer MRI in cervical spondylotic myelopathy: a pilot study. Diagnostics (Basel) 12(9):2090PubMedCrossRef
27.
Ma X et al (2018) A Follow-up Study of Postoperative DCM Patients Using Diffusion MRI with DTI and NODDI. Spine (Phila Pa 1976) 43(15):E898–E904PubMedCrossRef
28.
Okita G et al (2018) Application of neurite orientation dispersion and density imaging or diffusion tensor imaging to quantify the severity of cervical spondylotic myelopathy and to assess postoperative neurologic recovery. Spine J 18(2):268–275PubMedCrossRef
29.
30.
Zhang MZ et al (2022) Predicting postoperative recovery in cervical spondylotic myelopathy: construction and interpretation of T(2)(*)-weighted radiomic-based extra trees models. Eur Radiol 32(5):3565–3575MathSciNetPubMedCrossRef
31.
32.
33.
Xiangshui M et al (2010) 3 T magnetic resonance diffusion tensor imaging and fibre tracking in cervical myelopathy. Clin Radiol 65(6):465–473PubMedCrossRef
34.
Kara B et al (2011) The role of DTI in early detection of cervical spondylotic myelopathy: a preliminary study with 3-T MRI. Neuroradiology 53(8):609–616PubMedCrossRef
35.
Uda T et al (2013) Assessment of cervical spondylotic myelopathy using diffusion tensor magnetic resonance imaging parameter at 3.0 tesla. Spine 38(5):407–414PubMedCrossRef
36.
Ellingson BM et al (2014) Diffusion tensor imaging predicts functional impairment in mild-to-moderate cervical spondylotic myelopathy. Spine J 14(11):2589–2597PubMedPubMedCentralCrossRef
37.
Li, X., et al., Potential use of diffusion tensor imaging in level diagnosis of multilevel cervical spondylotic myelopathy. Spine (Phila Pa 1976), 2014. 39(10): p. E615–22.
38.
Wen CY et al (2014) Diffusion tensor imaging of somatosensory tract in cervical spondylotic myelopathy and its link with electrophysiological evaluation. Spine J 14(8):1493–1500PubMedCrossRef
39.
Cui JL et al (2015) Quantitative assessment of column-specific degeneration in cervical spondylotic myelopathy based on diffusion tensor tractography. Eur Spine J 24(1):41–47PubMedCrossRef
40.
Suetomi Y et al (2016) Application of diffusion tensor imaging for the diagnosis of segmental level of dysfunction in cervical spondylotic myelopathy. Spinal Cord 54(5):390–395PubMedCrossRef
41.
Grabher P et al (2017) Neurodegeneration in the spinal ventral horn prior to motor impairment in cervical spondylotic myelopathy. J Neurotrauma 34(15):2329–2334PubMedCrossRef
42.
Yang YM et al (2017) The functional relevance of diffusion tensor imaging in comparison to conventional MRI in patients with cervical compressive myelopathy. Skeletal Radiol 46(11):1477–1486PubMedCrossRef
43.
Dong F et al (2018) A preliminary study of 30-T magnetic resonance diffusion tensor imaging in cervical spondylotic myelopathy. Eur Spine J 27(8):1839–1845PubMedCrossRef
44.
Zheng W et al (2018) Application of diffusion tensor imaging cutoff value to evaluate the severity and postoperative neurologic recovery of cervical spondylotic myelopathy. World Neurosurg 118:e849–e855PubMedCrossRef
45.
Iwasaki M et al (2019) Decreased value of highly accurate fractional anisotropy using 3-Tesla ZOOM diffusion tensor imaging after decompressive surgery in patients with cervical spondylotic myelopathy: aligned fibers effect. World Neurosurg X 4:100056PubMedPubMedCentralCrossRef
46.
Han X et al (2020) The evaluation and prediction of laminoplasty surgery outcome in patients with degenerative cervical myelopathy using diffusion tensor MRI. AJNR Am J Neuroradiol 41(9):1745–1753PubMedPubMedCentral
47.
He Z et al (2020) Analysis of pathological parameters of cervical spondylotic myelopathy using magnetic resonance imaging. Clin Neurol Neurosurg 189:105631PubMedCrossRef
48.
Kitamura M et al (2020) Longitudinal diffusion tensor imaging of patients with degenerative cervical myelopathy following decompression surgery. J Clin Neurosci 74:194–198PubMedCrossRef
49.
50.
Zhang H et al (2020) Multi-shot echo-planar diffusion tensor imaging in cervical spondylotic myelopathy: a longitudinal study. Bone Joint J 102(9):1210–1218PubMedCrossRef
51.
Tian X et al (2021) Correlations between preoperative diffusion tensor imaging and surgical outcome in patients with cervical spondylotic myelopathy. Am J Transl Res 13(10):11461PubMedPubMedCentral
52.
Vallotton K et al (2021) Tracking white and gray matter degeneration along the spinal cord axis in degenerative cervical myelopathy. J Neurotrauma 38(21):2978–2987PubMedCrossRef
53.
Han X et al (2022) Application of neurite orientation dispersion and density imaging to evaluate and predict the surgical outcome for degenerative cervical myelopathy. Orthop Surg 14(7):1482–1488MathSciNetPubMedPubMedCentralCrossRef
54.
Zhang JK et al (2022) Diffusion basis spectrum imaging provides insights into cervical spondylotic myelopathy pathology. Neurosurgery 10.1227
55.
Cloney MB et al (2018) Quantitative Magnetization transfer mri measurements of the anterior spinal cord region are associated with clinical outcomes in cervical spondylotic myelopathy. Spine (Phila Pa 1976) 43(10):675–680PubMedCrossRef
56.
57.
58.
Wang C et al (2022) Evolution of brain functional plasticity associated with increasing symptom severity in degenerative cervical myelopathy. EBioMedicine 84:104255PubMedPubMedCentralCrossRef
59.
Mattei TA et al (2011) Cervical spondylotic myelopathy: pathophysiology, diagnosis, and surgical techniques. In: International Scholarly Research Notices, 2011
60.
Martin AR et al (2021) Clinical outcomes of nonoperatively managed degenerative cervical myelopathy: an ambispective longitudinal cohort study in 117 patients. J Neurosurg Spine 34(6):821–829PubMedCrossRef
61.
62.
63.
Mamata H, Jolesz FA, Maier SE (2005) Apparent diffusion coefficient and fractional anisotropy in spinal cord: age and cervical spondylosis-related changes. J Magn Reson Imaging 22(1):38–43PubMedCrossRef
64.
Thurnher MM, Law M (2009) Diffusion-weighted imaging, diffusion-tensor imaging, and fiber tractography of the spinal cord. Magn Reson Imaging Clin N Am 17(2):225–244PubMedCrossRef
65.
Winklhofer S et al (2014) Spinal cord motion: influence of respiration and cardiac cycle. in RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren. 2014. © Georg Thieme Verlag KG
66.
Yin M et al (2021) A bibliometric analysis and visualization of current research trends in the treatment of cervical spondylotic myelopathy. Global Spine J 11(6):988–998PubMedCrossRef
67.
De Leener B et al (2017) SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data. Neuroimage 145(Pt A):24–43PubMedCrossRef
68.
Stephens ME et al (2022) Utility of machine learning algorithms in degenerative cervical and lumbar spine disease: a systematic review. Neurosurg Rev 45(2):965–978PubMedCrossRef
Metadata
Title
Evaluating tissue injury in cervical spondylotic myelopathy with spinal cord MRI: a systematic review
Authors
Ali Fahim Khan
Esmaeil Mohammadi
Grace Haynes
Sanaa Hameed
Michael Rohan
David B. Anderson
Kenneth A. Weber II
Fauziyya Muhammad
Zachary A. Smith
Publication date
05-11-2023
Publisher
Springer Berlin Heidelberg
Published in
European Spine Journal / Issue 1/2024
Print ISSN: 0940-6719
Electronic ISSN: 1432-0932
DOI
https://doi.org/10.1007/s00586-023-07990-0

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