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Cited by 253

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Chronic cervical cord compression: clinical significance of increased signal intensity on MR images.

Takahashi, M, Yamashita, Y, Sakamoto, Y, Kojima, R·1989·Radiology

Abstract

Magnetic resonance (MR) imaging was performed in 668 patients with chronic compressive lesions of the cervical spinal canal. High signal intensity was observed within the spinal cord on T2-weighted or proton density spin-echo images in 99 patients (14.8%). Frequency of this finding was directly proportional to severity of clinical myelopathy and degree of spinal canal compression seen on MR images. Patients with a high-signal-intensity area responded less favorably than those without to surgical or medical treatment. More than 60% of the patients had this finding when grade of myelopathy or degree of canal compression was moderate to marked. Among 10 patients who received contrast material during MR imaging, one patient had definite enhancement and another had questionable enhancement in the high-signal-intensity area. The finding disappeared after decompressive surgery and medical treatment in some cases: Three of four of the patients who underwent surgery showed good clinical improvement. High signal intensity of the spinal cord produced by compressive lesions appears to be an important indicator for predicting prognosis.

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Metadata

Authors
Takahashi, M., Yamashita, Y., Sakamoto, Y., & Kojima, R.
Venue
Radiology
Published
1989-10
Volume
173
Issue
1
Pages
219-224
ISSN
  • 0033-8419 (ISSN-L)
  • 1527-1315
OpenAlex
W2005070089
Cited by
253
References
0
FWCI
5.76
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Chronic cervical cord compression: clinical significance of increased signal intensity on MR images. https://app.cochat.ai/papers/10.1148/radiology.173.1.2781011
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Takahashi, M., Yamashita, Y., Sakamoto, Y., & Kojima, R. (1989). Chronic cervical cord compression: clinical significance of increased signal intensity on MR images. Radiology. https://doi.org/10.1148/radiology.173.1.2781011

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.