Mary Kate Manhard1, Sasidhar Uppuganti2, Mathilde C Granke2, Daniel F Gochberg3, Jeffry S Nyman2, and Mark D Does1
1Biomedical Engineering, Vanderbilt University, Nashville, TN, United States, 2Department of Orthopaedics & Rehabilitation, Vanderbilt University, Nashville, TN, United States, 3Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States
Synopsis
Bound and pore water concentration measures of cortical bone
found from MRI have been shown to correlate with material properties of bone,
but the ideal way to analyze and draw information from 3D quantitative maps
remains unclear. Material properties of cadaver radii found from a 3-point bend
test were correlated with characteristics of the distribution of bound and pore
water concentrations (e.g. mean, skewness) in ROIs found from different segmentations.
Results highlighted the importance of segmentation method as well as quantitative
measures drawn from the maps. Introduction
Material properties of cortical bone such as strength and
toughness correlate with bound and pore water concentration as measured from
UTE MRI,
1–3 and bound and pore water
mapping methods have been implemented in vivo in clinically practical scans.
4,5 However, the best way to analyze and draw
information from these quantitative bound and pore water maps currently remains
unclear. For example, small ROIs of bound and pore water maps may miss changes
in porosity relevant for predicting fracture.
6 In addition, the segmentation
of the whole bone can greatly affect results, particularly the inclusion or
exclusion of the transition zone between cortical and trabecular bone near the
endosteal surface. This area of bone has been shown to be the first to
deteriorate when bone loss occurs.
7 The purpose of this work was
to investigate 1) how segmenting the whole bone affects overall measurements of
bound and pore water concentration and 2) what quantitative information from
these ROIs are important for evaluating fracture risk.
Methods
The Adiabatic Inversion Recovery (AIR) and Double Adiabatic
Full Passage (DAFP) sequences were used with 3D UTE MRI to create bound and
pore water concentration maps in 40 cadaveric forearms (mean age 80yrs, 20male/20female)
4,5. Scans were acquired at 1 mm isotropic
resolution with a 250 mm FOV. Bones were segmented by slice using a polar
transformation method described by Rad et. al.
8 through approximately 13 mm
in the axial direction at the distal third location. The segmentation was
repeated after increasing the amount of endosteal region that was classified as
cortical bone. These results were then compared with biomechanical measurements
acquired from a three-point bend test on the same bones. Spearman correlation
coefficients (ρ) were used to analyze how the
characteristics of the distribution of bound and pore water (e.g. mean,
skewness) in a given ROI relate to fracture risk and how these relationships
depend on the segmentation.
Results
Figure 1 shows bound and pore water concentration maps and
corresponding histograms from bones with high and low bending strength.
The changes in the histograms
between segmentation methods are apparent across both strong and weak bones, though
are more significant with weaker bones. Across
all 40 bones, the segmentation that excludes more of the endosteal region (without
zone 2) resulted in an increase in mean bound water concentration per voxel
(i.e. a shift to the right in
the histogram) by
an average of 8% (up to 17%) and a decrease in mean pore water per voxel
(i.e. a shift to the left) by 49%
(up to 60%). This highlights the
sensitivity of these measures to ROI placement. Figure 2 shows correlations of
bending strength with the mean bound and pore water concentrations and the
skewness of the bound and pore water distributions. Correlations were significant
with both large and small endosteal regions. The skewness of both bound and
pore water data gave high correlations to strength, especially when the larger endosteal
region (zone 1+2) was used. While the difference in correlation coefficients
for the mean values are moderate, the correlation coefficients for skewness change markedly depending on whether or not the endosteal region is included. Multivariate
analysis may give further insight into predicting fracture risk with these measurements
of bound and pore water concentrations.
Discussion
These results emphasize the importance of the segmentation method
on assessing bound and pore water maps of bone. Specifically, the same image has
the potential to give drastically different results depending on the extent to
which the segmentation method includes bone within the endosteal region. While
this may not severely affect correlations with the mean bound and pore water
concentrations, it is important that segmentation is not user dependent and is
done the same way every time to get reliable results. It is also important to
look beyond the mean concentrations, especially given the skewness of the
distribution of concentrations within an ROI. Bones with a high positive
skewness of pore water (shift towards lower concentrations) show higher
strength, as well as bones with a high negative skewness of bound water (shift
towards higher concentrations). Though including more of the endosteal region
risks over-/under-estimating the mean pore/bound water concentrations by
including voxels that may include marrow space, it also is capturing essential
information that is sensitive to the degradation of bone. Dependable analyses
of these maps are critical for future studies with bound and pore water MRI.
Acknowledgements
No acknowledgement found.References
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