Multiple sclerosis lesions: relationship between MR enhancement pattern and magnetization transfer effect.
PURPOSE: To investigate the relationship between the enhancement pattern of a multiple sclerosis lesion and its magnetization transfer effect. METHODS: Fifty-four lesions were chosen from 29 patients with multiple sclerosis on the basis of enhancement pattern on contrast-enhanced T1-weighted MR images. They included 14 homogeneously enhancing lesions, 26 nonenhancing lesions, and 14 ring-enhancing lesions. Magnetization transfer ratios of the homogeneously enhancing lesions, nonenhancing lesions, and central portion of the ring-enhancing lesions were measured. Means were calculated and compared. RESULTS: The magnetization transfer ratios for homogeneously enhancing lesions were higher (mean, 32.2%; SD, 3.4%) than those for nonenhancing lesions (mean 29.4%; SD, 4.3%) and for the central portion of ring-enhancing lesions (mean, 24.5%; SD, 4.0%). Significant differences were found between the ring-enhancing lesions and the homogeneously enhancing lesions and between the ring-enhancing lesions and the nonenhancing lesions. CONCLUSION: We found a relationship between decreased magnetization transfer ratios and those enhancement patterns in which myelin is known to be decreased histopathologically. Thus, use of the magnetization transfer technique may increase the specificity of MR imaging in assessing the extent of residual myelination in multiple sclerosis lesions.
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Related Subject Headings
- Pentetic Acid
- Organometallic Compounds
- Nuclear Medicine & Medical Imaging
- Nerve Fibers, Myelinated
- Multiple Sclerosis
- Meglumine
- Magnetic Resonance Imaging
- Image Processing, Computer-Assisted
- Image Enhancement
- Humans
Citation
Published In
ISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Pentetic Acid
- Organometallic Compounds
- Nuclear Medicine & Medical Imaging
- Nerve Fibers, Myelinated
- Multiple Sclerosis
- Meglumine
- Magnetic Resonance Imaging
- Image Processing, Computer-Assisted
- Image Enhancement
- Humans