MR-based Attenuation Correction for PET/MR - Correction Techniques in Emission Tomography - page 230

FIGURE 11.9: (See color insert.) Effect of ignoring cortical bone during
AC. (A) PET image reconstructed using the original CT image. (B) PET
image reconstructed using the same CT image with all bone structures set to
the HU value of soft tissue thus simulating a best case scenario of MR-AC
where bone attenuation is ignored. (C) Relative difference (%) between (A)
and (B) illustrating the largest effect inside the skeleton. Note, voxels set to
white in low uptake regions with SUV<0.2 in the original PET image.
11.4.1 The presence of bone
As bone structures are dicult to separate on MR images, a straightfor-
ward approach to MR-AC would be simply to ignore bone. This is not new
and was shown in early studies on CT-AC to be of less impact than originally
expected [1] despite the fact that the fraction of cortical bone varies in axial
images, whereby it is higher in the head than in areas below the neck.
Figure 11.9 shows an example where CT-AC is performed with and without
consideration of bone. This example illustrates the minimum bias expected
from ignoring bone attenuation and considering this tissue class as soft tissue.
In practice, an MR-AC algorithm that ignores bone tissue may also falsely
attribute air as soft tissue and thus introduce much higher errors.
Figure 11.9 shows errors of up to 60% in the reconstructed PET image if
bone structures in the attenuation map have been set to the attenuation value
of soft tissue. This magnitude bias typically occurs in regions of relatively low
activity, that are of less clinical interest.
The study by Martinez-Moller et al. [23] demonstrated no clinical dier-
ence in PET images following CT-AC and a (CT-derived) 4-tissue segmen-
tation AC. Personal communication with nuclear medicine experts confirmed
that quantitative errors of around 10%, or even 15% in lesion activity would
typically not affect their diagnosis. However, larger studies, focussing on bone