Imaging iron stores in the brain
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Date: 03/01/05
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Date: 1 Mar 2005 08:01:54 -0800
Magn Reson Imaging. 2005 Jan;23(1):1-25. Related Articles, Links
Imaging iron stores in the brain using magnetic resonance imaging.
Haacke EM, Cheng NY, House MJ, Liu Q, Neelavalli J, Ogg RJ, Khan A,
Ayaz M, Kirsch W, Obenaus A.
The MRI Institute for Biomedical Research, 440 East Ferry Street,
Detroit, MI 48202, USA; Department of Radiology, Wayne State
University, 3990 John R Road, Detroit, MI 48202, USA.
For the last century, there has been great physiological interest in
brain iron and its role in brain function and disease. It is well known
that iron accumulates in the brain for people with Huntington's
disease, Parkinson's disease, Alzheimer's disease, multiple sclerosis,
chronic hemorrhage, cerebral infarction, anemia, thalassemia,
hemochromatosis, Hallervorden-Spatz, Down syndrome, AIDS and in the eye
for people with macular degeneration. Measuring the amount of nonheme
iron in the body may well lead to not only a better understanding of
the disease progression but an ability to predict outcome. As there are
many forms of iron in the brain, separating them and quantifying each
type have been a major challenge. In this review, we present our
understanding of attempts to measure brain iron and the potential of
doing so with magnetic resonance imaging. Specifically, we examine the
response of the magnetic resonance visible iron in tissue that produces
signal changes in both magnitude and phase images. These images seem to
correlate with brain iron content, perhaps ferritin specifically, but
still have not been successfully exploited to accurately and precisely
quantify brain iron. For future quantitative studies of iron content we
propose four methods: correlating R2' and phase to iron content;
applying a special filter to the phase to obtain a susceptibility map;
using complex analysis to extract the product of susceptibility and
volume content of the susceptibility source; and using early and late
echo information to separately predict susceptibility and volume
content.
PMID: 15733784 [PubMed - in process]
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