ArticleNeuroradiology2023
Automated signal intensity analysis of the spinal cord for detection of degenerative cervical myelopathy - a matched-pair MRI study.
Article in Neuroradiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 4 citations in OpenAlex.
- A study of examinations and surgical determinants of degenerative cervical myelopathy: the relationship between mri quantifications and motor evoked potentials.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Magnetic Resonance Imaging Preprocessing for Robust Spinal Cord Segmentation in Cervical Myelopathy.Journal of imaging · 2026Article
- Enhancing Spinal Cord and Canal Segmentation in Degenerative Cervical Myelopathy : The Role of Interactive Learning Models with manual Click.Journal of Korean Neurosurgical Society · 2026Article
- T2-weighted MRI high signal in cervical spondylotic myelopathy is associated with dynamic change.Journal of orthopaedic surgery and research · 2025Article
- Quantification of cervical spinal stenosis by automated 3D MRI segmentation of spinal cord and cerebrospinal fluid space.Spinal cord · 2024Article
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
purposeDetection of T2 hyperintensities in suspected degenerative cervical myelopathy (DCM) is done subjectively in clinical practice. To gain objective quantification for dedicated treatment, signal intensity analysis of the spinal cord is purposeful. We investigated fully automated quantification of the T2 signal intensity (T2-SI) of the spinal cord using a high-resolution MRI segmentation.
methodsMatched-pair analysis of prospective acquired cervical 3D T2-weighted sequences of 114 symptomatic patients and 88 healthy volunteers. Cervical spinal cord was segmented automatically through a trained convolutional neuronal network with subsequent T2-SI registration slice-by-slice. Received T2-SI curves were subdivided for each cervical level from C2 to C7. Additionally, all levels were subjectively classified concerning a present T2 hyperintensity. For T2-positive levels, corresponding T2-SI curves were compared to curves of age-matched volunteers at the identical level.
resultsForty-nine patients showed subjective T2 hyperintensities at any level. The corresponding T2-SI curves showed higher signal variabilities reflected by standard deviation (18.51 vs. 7.47 a.u.; p < 0.001) and range (56.09 vs. 24.34 a.u.; p < 0.001) compared to matched controls. Percentage of the range from the mean absolute T2-SI per cervical level, introduced as "T2 myelopathy index" (T2-MI), was correspondingly significantly higher in T2-positive segments (23.99% vs. 10.85%; p < 0.001). ROC analysis indicated excellent differentiation for all three parameters (AUC 0.865-0.920).
conclusionThis fully automated T2-SI quantification of the spinal cord revealed significantly increased signal variability for DCM patients compared to healthy volunteers. This innovative procedure and the applied parameters showed sufficient diagnostic accuracy, potentially diagnosing radiological DCM more objective to optimize treatment recommendation.
trial registrationDRKS00012962 (17.01.2018) and DRKS00017351 (28.05.2019).
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