Ruaridh M Gollifer1,2, Tim JP Bray1,3, Margaret Hall-Craggs1,3, and Alan Bainbridge2
1Centre for Medical Imaging (CMI), University College London, London, United Kingdom, 2Department of Medical Physics and Bioengineering, University College London Hospital, London, United Kingdom, 3Department of Imaging, University College London Hospital, London, United Kingdom
Synopsis
Short
tau inversion recovery (STIR) imaging is the mainstay of clinical imaging in
inflammatory musculoskeletal (MSK) diseases, and generates hyperintense signal
in areas of inflammation in bone marrow (bone marrow oedema). However, the assessment
of STIR images of bone marrow is based on qualitative judgement of signal intensity
and can be confounded by variations in fat content resulting from the healing
response in bone to inflammation. We aimed to develop a method which would (1)
separate fat and water and (2) provide a water-specific T2
measurement, enabling separation and individual quantification of oedema and
fat in the bone marrow.
Introduction
MRI
has become a key component of pathways for diagnosing, phenotyping and
monitoring inflammation in inflammatory musculoskeletal
(MSK) diseases1-3. T2-weighted short inversion time inversion recovery (STIR)
imaging is the mainstay of imaging these disorders, and areas of hyperintensity
within bone marrow indicate active inflammation. The key mechanisms for this
hyperintensity are thought to be elongated T2 of the water component
(T2water) and reduced fat fraction3,4. However, radiological assessment of STIR images for diagnostic and
disease management purposes is subjective. Furthermore, variations in fat
content due to chronic inflammation (e.g. fat metaplasia in the bone
marrow) make interpretation difficult because the tissue becomes heterogenous
and areas of ‘spared’ normal tissue are difficult to differentiate from
oedema/inflammation1,2. Therefore, quantitative measurements of tissue characteristics are
needed to improve specificity and to offer more detailed tissue
characterisation.
To
address this problem, we aim to develop a single integrated acquisition that
can (1) separate water and fat signals and (2) perform T2
relaxometry on the water component in the marrow. Here, as a proof of concept, we
used a series of discrete Dixon turbo spin echo (TSE) acquisitions with
incrementally increasing effective echo times in order to achieve water T2water
quantification. This approach represents a simplification of methodology by Janiczek
et al., who used a Carr-Purcell-Meiboom-Gill (CPMG) echo train with asymmetric
echoes for Dixon encoding5. We assess the accuracy of this method in a phantom constructed to
provide a range of fat fraction and T2 values, with T2water and T2fat values obtained using MR spectroscopy as a gold standard6,7. Methods
Imaging
was performed in the phantom and in the bone marrow of a healthy volunteer. The
phantom consisted of containers with varying agar concentration (2%, 3% and 4%
to modify T2)8 and with varying fat fraction (0%, 30% and 40% by volume).
Emulsification was achieved using sodium dodecyl sulphate (SDS) surfactant, and
all the phantoms were solid (Figure 1).
Imaging
was performed using a 3.0T Philips Ingenia scanner. T2water
quantification was achieved using a series of optimised Philips Dixon TSE
acquisitions with incrementally increasing effective echo time (TEeff
20ms, 30ms,40ms, 60ms, 80ms and 100ms) (see schematic, Figure 2). The echo
spacing increased with increasing TEeff (corresponding values were
9.2ms, 13.8ms, 18.4ms, 27.6ms, 36.8ms and 46ms). Other parameters included:
pixel spacing 0.6x0.6mm; slice thickness 5mm, TR 3000ms, linear k-space
ordering; flip angle/refocusing angle 90o/180o; image
matrix 400x392 (448x422 for healthy volunteer); echo train length 8; SENSE
factor 2; acquisition duration 69 seconds. The total scan duration for six
Dixon TSE acquisitions was approximately seven minutes. T2water
measurements were obtained using a monoexponential fit, implemented in MATLAB
using a nonlinear least squares solver (Levenberg-Marquardt). We implemented an
extended phase graph (EPG) based correction method to account for the effect of
non-180°
refocusing pulses and to measure T2 over the TEeff
increments9,10; however, this was not used in the present work as all TSE acquisitions
used 180°
refocusing pulses.
Multi-echo
Point RESolved Spectroscopy (PRESS) was performed with a 15x15x15 voxel placed
in the centre of each container with echo times of 40, 60, 80, 100 and 140ms
and TR of 5000ms. The spectra were analysed in jMRUI11,12 using the AMARES package13 (Figure 1). T2water estimates from Dixon TSE data were
compared against MRS (as a reference standard) using linear regression, with
two tailed t-tests to determine if regression slopes and intercepts were
significant.Results
T2
estimates derived from water-only images from the Dixon TSE acquisition are
compared against spectroscopy in Figure 3. Images from the volunteer are shown
in Figures 4 and 5.
T2water
estimates from Dixon TSE were accurate and linearly related to reference
T2water estimates from spectroscopy over the range of FF values investigated (regression
slope = 0.77, P < 0.001, regression intercept = 10.5, P = 0.004. There was a
decrease in T2water with increasing FF of the phantom observed in both the Dixon
TSE data and in the MRS data.
In
vivo imaging produced good quality images which were artifact free and produced
plausible T2 values in relevant structures (with lower values in bone marrow (47.6ms)
and fat (41.1ms) and higher values in intervertebral disc (388.8ms)) (Figure 4). Discussion and Conclusions
T2water
measurements using multiple Dixon TSE acquisitions with echo time increments
provide T2 measurements over a range of fat fraction values that
shown similar behaviour with respect to agar concentration and fat fraction as
the reference MRS method. Separating out the water and fat signals before
performing relaxometry may be particularly advantageous in bone marrow because
it normally contains a substantial proportion of fat. Our results suggest that
the proposed methodology is promising and offers sufficient accuracy and
linearity14 to warrant further development.
The
proposed fat-insensitive T2water measurement offers a quantitative
alternative to the widely-used STIR sequence and could enable more accurate and
precise diagnosis, monitoring and phenotyping of inflammatory diseases
affecting the bone marrow. This multiparametric approach has the advantage that
a number of images with different contrasts can be generated in one
acquisition, potentially increasing value and reducing scan time. Our next step
will be to measure T2water in cohorts of healthy volunteers and in
patients with bone marrow inflammation. Acknowledgements
RMG
is supported by the UCL Biomedical Research Centre (BRC). TJPB is supported by
an NIHR Clinical Lectureship (CL-2019-18-001). MHC is supported by UCLH BRC. This
work was undertaken at UCLH/UCL, which receives funding from the UK Department
of Health’s the National Institute for Health Research (NIHR) Biomedical
Research Centre (BRC) funding scheme.References
- Sieper, J. et al. The Assessment
of SpondyloArthritis international Society (ASAS) handbook: A guide to assess
spondyloarthritis. Ann. Rheum. Dis. 68, ii1–ii44 (2009).
- Bray, T. J. P. et al.
Recommendations for acquisition and interpretation of MRI of the spine and
sacroiliac joints in the diagnosis of axial spondyloarthritis in the UK. Rheumatology
58, 1831–1838 (2019).
- Bray, T. J. P., Bainbridge, A.,
Punwani, S., Ioannou, Y. & Hall-Craggs, M. A. Simultaneous Quantification
of Bone Edema/Adiposity and Structure in Inflamed Bone Using Chemical
Shift-Encoded MRI in Spondyloarthritis. Magn. Reson. Med. 79,
1031–1042 (2018).
- Bray, T. J. P., Chouhan, M. D.,
Punwani, S., Bridge, A. & Hall-Craggs, M. A. Fat fraction mapping using
magnetic resonance imaging: Insight into pathophysiology. British Journal of
Radiology vol. 91 (2018).
- Janiczek, R. L. et al.
Simultaneous T 2 and lipid quantitation using IDEAL-CPMG. Magn.
Reson. Med. 66, 1293–1302 (2011).
- Klose, U. Measurement sequences for
single voxel proton MR spectroscopy. Eur. J. Radiol. 67, 194–201
(2008).
- Bley, T. A., Wieben, O., François, C.
J., Brittain, J. H. & Reeder, S. B. Fat and water magnetic resonance
imaging. Journal of Magnetic Resonance Imaging vol. 31 4–18 (2010).
- Christoffersson, J. O., Olsson, L. E.
& Sjöberg, S. Nickel-doped agarose gel phantoms in MR imaging. Acta
radiol. 32, 426–431 (1991).
- Weigel, M. Extended phase graphs:
Dephasing, RF pulses, and echoes - Pure and simple. Journal of Magnetic
Resonance Imaging vol. 41 266–295 (2015).
- Nöth, U., Shrestha, M., Schüre, J. R.
& Deichmann, R. Quantitative in vivo T2 mapping using fast spin echo
techniques – A linear correction procedure. Neuroimage 157, 476–485
(2017).
- Naressi, A., Couturier, C., Castang, I.,
De Beer, R. & Graveron-Demilly, D. Java-based graphical user interface for
MRUI, a software package for quantitation of in vivo/medical magnetic resonance
spectroscopy signals. Comput. Biol. Med. 31, 269–286 (2001).
- Stefan, D. et al. Quantitation of
magnetic resonance spectroscopy signals: The jMRUI software package. Meas.
Sci. Technol. 20, 104035 (2009).
- Vanhamme, L., Van Den Boogaart, A. &
Huffel, S. Van. Improved Method for Accurate and Efficient Quantification of
MRS Data with Use of Prior Knowledge. JOURNAL OF MAGNETIC RESONANCE
vol. 129 (1997).
- Sullivan, D. C. et al. Metrology
standards for quantitative imaging biomarkers1. Radiology 277,
813–825 (2015).