Leonardo A Rivera-Rivera1, Ante Zhu1, Timothy Colgan 2, Diego Hernando1,2, Tilman Schubert3, Patrick A Turski1,2, and Kevin M Johnson1,2
1Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, 2Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States, 3Department of Radiology, Basel University Hospital, Basel, Switzerland
Synopsis
Intracranial
vascularity is modified in a wide array of diseases, including various forms of
dementia, cancer, and stroke. When assessment of the vascular architecture is
needed, one potential approach is steady state imaging with ferumoxytol to estimate
cerebral blood volume (CBV). Building upon recent work, in this study we
investigate the correlation between QSM and R2* based CBV estimates. Results
from 19 healthy volunteers show that the QSM based CBV estimates demonstrated a
high degree of correlation in gray and white matter, but larger variance than
R2* based measures.
INTRODUCTION:
Increasing evidence
exists indicating pathologic alterations of the cerebral vasculature in
Alzheimer’s disease (AD).1 In chronic neurodegenerative diseases
such as AD, characterized by the loss of neurons in the cerebral cortex,
disease may be diffuse such that drawing reference regions of interest to
estimate relative cerebral blood volume (CBV) is not practical. Absolute CBV
quantification may enable the identification of global and regional pathologic
CBV with higher reproducibility. However, blood volume concentration is highly
challenging to relate to MRI signal characteristics such as the observed R1 or
R2*, which are sensitive to factors such as water exchange,
compartmentalization, flow, and vascular architecture. Quantitative Susceptibility Mapping is an independent technique
which, in principle, can be used to obtain
images of local tissue magnetic susceptibility, and hence estimate changes
after administration of a contrast agent. While QSM has been demonstrated for
DSC-MRI2, it is based on an ill-posed deconvolution procedure, and
thus may be sensitive to the image quality achievable with dynamic imaging. In
this work, we explore the use of QSM for CBV estimation using ferumoxytol
enhanced MRI and compare to R2* based results.METHODS:
This is a retrospective re-analysis of data previously
acquired for comparison of R2* and T1 based measures.3 Subjects: 19
healthy subjects (age range 20-61y, mean=32y, 10F). MRI: 3.0T scanner (MR750, GE Healthcare Waukesha, WI, USA) with a 32ch brain
coil (Nova Medical, Wilmington, MA, USA). For all patients, scanning was
performed before and after the administration of two doses of ferumoxytol (AMAG
Pharmaceuticals, Inc., Cambridge, MA). Ferumoxytol was diluted to 60 ml and
injected as a slow infusion. Images were acquired at 3 time points:
pre-contrast, after a first injection (1mg/kg) and a second injection (4mg/kg),
for a total ferumoxytol dose of 5mg/kg. 3D multi-echo,
gradient echo images were acquired with: TR= 32.5 ms, 8 echo times ranging from
2.2ms to 29.8ms, flip angle = 15 degrees, 1mm isotropic resolution, and
FOV=256x180x240 mm3.
R2* images were generated from complex fitting the multi-echo images.
For each subject, partial volume masks (PVMs) of gray matter (GM) and white
matter (WM) were generated as previously described.3 QSM
images were generated after exploring different approaches (figure 1). Background
field removal was performed using a projection onto dipole fields approach4, and the
magnetic susceptibility of tissue was determined using
morphology enable dipole inversion (MEDI)5. QSM images
pre- and post-contrast were co-registered using a rigid body registration
utilizing the source images, and then subtracted to obtain ΔQSM. Pixel
wise changes were cumulated from the registered images into a 2D histogram of
measures. This data was projected for along the Δχ and ΔR2* values at the 5mg
FE/kg dose. The change in magnetic susceptibility (Δχ) in blood estimated
in
previous work3 using Nadler equation and
R1 measurements were used. In addition, Δχ in blood was estimated
from QSM images from observations in ROI’s in the superior sagittal sinus.
RESULTS:
Figure 2 shows representative χ,
R2*, Δχ, and ΔR2* images from a single slice of the volume from one subject. QSM
images show GM and WM demarcation; however, some variation can be seen in the
post contrast images, especially in white matter. R2* images show higher SNR.
Figure 3 shows the comparison between the
Δχ in blood from QSM, Nadler equation and R1 approaches. QSM and R1 Δχ measures
are similar, but QSM shows a larger variance. As shown in
Figure 4, QSM based CBV estimates are lower that R2* measures, the variance in
WM suggest inherent challenges to remove the background field and to solve the
ill posed problem in QSM. Figure 5 shows pixel wise
relationship between χ and R2* measures for all subjects. The pixel wise
correlation shows a slow increase when projected onto R2*. As projected onto Δχ,
the ΔR2* tends to exhibit changes where the QSM does not, potentially
indicating background field effects. DISCUSSION AND CONCLUSION:
In this work, we compare QSM and R2* based CBV
measurements after the administration of ferumoxytol. The average QSM based
measurements correlate well with R2* results, although inherent challenges
persist to disentangle the background field effects from contrast enhancement.
Ferumoxytol is delivered widely throughout the brain and may result in non-local
susceptibility effects. The ideal approach of subtracting phase image prior to
QSM processing (Fig1a) failed in our study. This technique potentially is
challenged by the considerable time between pre and post contrast images
(~40min). Further investigation is required of the solver and potential
challenges relating to the complex distribution of contrast.Acknowledgements
We gratefully acknowledge R01NS066982, and GE
Healthcare for assistance and support.References
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