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on the slice-select axis to spoil (suppress) the signal across the sample at all
locations except where iron-loaded cells act to generate local gradients to
cancel the externally imposed gradient.
The second general class of methods takes a different approach by deriv-
ing positive contrast through postprocessing of images (Posse 1992). The
local magnetic field gradients induced by magnetic susceptibilities lead to
echo shifts in k-space with GRE imaging. The effect is exploited by applying
a shifted reconstruction window in k-space (Bakker et al. 2006). A suscepti-
bility gradient mapping (SGM) technique has been proposed that generates
susceptibility vectors from a regular complex GRE dataset to develop posi-
tive contrast in 3D (Dahnke et al. 2008). A third technique is to exploit the
advantage of ultrashort echo time (UTE) imaging (Gold et al. 1995) in which
Short-T2 species, such as iron-labeled cells, will appear bright. A second
Long-TE image is acquired and subtracted from the short-TE image to yield
difference images in which the background is suppressed, including fat and
blood, while iron-labeled cells appear bright.
Some of these positive contrast methods have been compared by imag-
ing labeled glioma cells transplanted to the flanks of nude rats (Liu et al.
2008). Positive contrast was generated from the presence of labeled cells, but
it remains to be determined whether positive contrast yielded better cel-
lular detection. One disadvantage of positive contrast images is that they
lack anatomical detail and therefore are best supplemented with traditional
negative contrast images, which may in fact demonstrate higher sensitivity
to cellular detection.
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