Michael Carl1, Graeme McKinnon2, and Gaspar Delso3
1GE Healthcare, San Diego, CA, United States, 2GE Healthcare, WI, United States, 3GE Healthcare, United Kingdom
Synopsis
Many musculoskeletal tissues such as cortical bone
have very short transverse relaxation times and require specialized pulse
sequences such as UTE or ZTE for optimal signal acquisition. Recently, these
sequences have been used to directly visualize cortical bone by suppressing
surrounding long T2 tissues such as fat or muscle by either magnetization
preparation using inversion recovery, or logarithmic tissue segmentation. In
this work, we compare these techniques on a cadaveric bovine knee specimen. Both inversion recovery UTE as well as tissue
segmented ZTE imaging proved promising method for direct bone imaging with
CT-like image appearance.
Introduction
Many
musculoskeletal (MSK) tissues such as cortical bone have very short transverse
relaxation times and require specialized pulse sequences such as UTE or ZTE for
signal acquisition. Recently, these sequences have been used to directly
visualize cortical bone by suppressing surrounding signals from long T2
tissues such as fat or muscle by either using inversion recovery [1], or
logarithmic tissue segmentation [2]. In this work, we compare these techniques
on a cadaveric bovine knee specimen.Theory
Due
to the short TE and resulting lack of T2 weighting, simple single
echo UTE or ZTE images show little tissue contrast. The spin density of
cortical bone is lower than that of the surrounding soft tissues, and it appears
as low signal intensity on UTE/ZTE images. Inversion recovery prepared UTE on
the other hand results in images that have most soft tissue signals suppressed
and shows cortical bone as relatively high signal [3]. This is accomplished by
using adiabatic inversion pulses that are insensitive to B1/B0
inhomogeneity and choosing the inversion time TI to coincide with the
null-point of fat. Since muscle has a comparatively longer T1, these
signals are suppressed by their resulting low steady state magnetization.
Therefore, only the very short T2 signals from bone or tendon
tissues, which do not get inverted by the IR pulse [4], contribute to the final
image. ZTE is another promising approach that has been developed recently. With
this technique the MR signal coming from all tissues can be segmented on a
logarithmic scale to distinguish air, bone, and soft tissues. Selectively
filtering out of soft tissues results in a CT-like image of cortical bone.Methods
A
fresh bovine knee specimen was obtained from a local butcher and scanned on a
3T MRI scanner (GE DV750). Images were obtained in the sagittal plane using an
eight channel head coil that was able to contain the whole knee joint. The UTE
sequence used a 3DCones k-space acquisition. Other relevant scan parameters for
both UTE and ZTE acquisitions were: FOV=26cm, matrix=256x256, #slices=150,
slice-thick=1.1mm. For the IR Cones sequence the repetition and inversion times
were TR=60ms, TI=28ms, respectively.Results
A
sagittal slice of a native ZTE image and the corresponding bone segmentation
are shown Fig.1. The corresponding IR UTE image is shown in Fig.2 (left). For
comparison, Fig.2 also shows a dual echo subtraction image (TE2=2.2ms).
Although the patella tendon is well depicted here, the cortical bone contrast
is less prominent compared to the IR UTE or the segmented ZTE images. Finally,
Fig.3 shows 3D rendered IR UTE (bottom row) and bone segmented ZTE (top row) images.
The ZTE images include a processing step that removes out-of-volume signals
such as coil elements, which can be visible in the IR UTE images (arrow).Discussion
Both
inversion recovery UTE as well as tissue segmented ZTE imaging proved promising
methods for direct bone imaging with CT-like image appearances. We found that
ZTE has the advantage of being more SNR efficient, while IR UTE represents a more
direct way without the need for additional processing steps to selectively image
bone.Acknowledgements
No acknowledgement found.References
[1] Li S et al, NMR Biomed. 2015 Jan;28(1): 70–78
[2] Wiesinger Fet al, Magn Reson
Med 2016 Jan;75(1):107-14
[3] Carl M et al, Magn Reson Med 2016
Aug;76(2):577-82
[4] Larson P et al, Magn Reson Med,
2007. 58(5): p. 952-61.