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Ann Neurol. 2008 Dec;64(6):707-13. doi: 10.1002/ana.21582.

Quantitative in vivo magnetic resonance imaging of multiple sclerosis at 7 Tesla with sensitivity to iron.

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  • 1University of California San Francisco/Berkeley Joint Graduate Group in Bioengineering, University of California San Francisco, San Francisco, CA, USA.

Abstract

OBJECTIVE:

Magnetic resonance imaging at 7 Tesla produces high-resolution gradient-echo phase images of patients with multiple sclerosis (MS) that quantify the local field shifts from iron in the basal ganglia and lesions. Phase imaging is easily integrated into clinical examinations because it is a postprocessing technique and does not require additional scanning. The purpose of this study was to quantify local field shifts in MS and to investigate their relation to disease duration and disability status.

METHODS:

Thirty-two subjects including 19 patients with MS and 13 age- and sex-matched control subjects were scanned at a spatial resolution of up to 195 x 260 microm. Data were postprocessed to produce anatomical quantitative phase images of local field shifts, as well as conventional magnitude images.

RESULTS:

The phase images showed an increased local field in the caudate, putamen, and globus pallidus of patients relative to control subjects (p < 0.01). The local field in the caudate was strongly correlated with disease duration (r(2) = 0.77; p < 0.001). Phase images showed contrast in 74% of the 403 lesions, increasing the total lesion count by more than 30% and showing distinct peripheral rings and a close association with vasculature.

INTERPRETATION:

The increased field in the basal ganglia and correlation with disease duration suggest pathological iron content increases in MS. The peripheral phase rings are consistent with histological data demonstrating iron-rich macrophages at the periphery of a subset of lesions. The clearly defined vessels penetrating MS lesions should increase our ability to detect focal vascular abnormalities specifically related to demyelinating processes.

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PMID:
19107998
[PubMed - indexed for MEDLINE]
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