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Related Experiment Videos

Spinal cord artifacts from truncation errors during MR imaging.

L M Levy1, G Di Chiro, R A Brooks

  • 1Neuroimaging Section, National Institute of Neurological and Communicative Disorders and Stroke, Bethesda, Md. 20892.

Radiology
|February 1, 1988
PubMed
Summary
This summary is machine-generated.

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Linear regions of altered signal intensity in sagittal magnetic resonance (MR) images can be misleading. Understanding these artifacts, like the Gibbs phenomenon, is crucial for accurate spinal cord diagnosis.

Area of Science:

  • Radiology
  • Medical Imaging
  • Neuroscience

Background:

  • Linear regions of altered signal intensity are observed in sagittal MR images of the spinal cord.
  • These signal variations can obscure anatomy and mimic pathological conditions, complicating diagnosis.
  • Artifacts arise from sampling effects at interfaces within the spinal canal.

Purpose of the Study:

  • To investigate the significance of linear signal intensity alterations in spinal cord MR imaging.
  • To determine the impact of sampling-related artifacts on image interpretation.
  • To explore methods for improving the clinical accuracy of MR imaging in the spinal cord.

Main Methods:

  • Examinations were conducted on ten healthy volunteers and one patient with spinal cord edema.

Related Experiment Videos

  • Magnetic resonance (MR) imaging was performed using 0.5-T and 1.5-T systems.
  • Analysis focused on signal intensity variations and their dependence on sampling parameters.

    • Main Results:

    • Sampling-related effects, specifically the Gibbs phenomenon, were identified at spinal cord edges and cerebrospinal fluid interfaces.
    • These artifacts can lead to signal patterns that obscure spinal cord anatomy.
    • The study highlighted the potential for artifacts to simulate pathological conditions like pseudosyringes.

    Conclusions:

    • Understanding Gibbs phenomenon and other sampling artifacts is essential for accurate interpretation of spinal cord MR images.
    • Analysis of intensity variations and their dependence on sampling can enhance diagnostic accuracy.
    • Improved artifact recognition is key to differentiating true pathology from imaging artifacts in the spinal cord.